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The Open Group Conference to Emphasize Healthcare as Key Sector for Ecosystem-Wide Interactions

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here

Dana Gardner: Hello, and welcome to a special BriefingsDirect Thought Leadership Interview series, coming to you in conjunction with The Open Group Conference on July 15, in Philadelphia. Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.

Gardner

I’m Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator throughout these discussions on enterprise transformation in the finance, government, and healthcare sector.

We’re here now with a panel of experts to explore how new IT trends are empowering improvements, specifically in the area of healthcare. We’ll learn how healthcare industry organizations are seeking large-scale transformation and what are some of the paths they’re taking to realize that.

We’ll see how improved cross-organizational collaboration and such trends as big data and cloud computing are helping to make healthcare more responsive and efficient.

With that, please join me in welcoming our panel, Jason Uppal, Chief Architect and Acting CEO at clinicalMessage. Welcome, Jason.

Jason Uppal: Thank you, Dana.

Inside of healthcare and inside the healthcare ecosystem, information either doesn’t flow well or it only flows at a great cost.

Gardner: And we’re also joined by Larry Schmidt, Chief Technologist at HP for the Health and Life Sciences Industries. Welcome, Larry.

Larry Schmidt: Thank you.

Gardner: And also, Jim Hietala, Vice President of Security at The Open Group. Welcome back, Jim. [Disclosure: The Open Group and HP are sponsors of BriefingsDirect podcasts.]

Jim Hietala: Thanks, Dana. Good to be with you.

Gardner: Let’s take a look at this very interesting and dynamic healthcare sector, Jim. What, in particular, is so special about healthcare and why do things like enterprise architecture and allowing for better interoperability and communication across organizational boundaries seem to be so relevant here?

Hietala: There’s general acknowledgement in the industry that, inside of healthcare and inside the healthcare ecosystem, information either doesn’t flow well or it only flows at a great cost in terms of custom integration projects and things like that.

Fertile ground

From The Open Group’s perspective, it seems that the healthcare industry and the ecosystem really is fertile ground for bringing to bear some of the enterprise architecture concepts that we work with at The Open Group in order to improve, not only how information flows, but ultimately, how patient care occurs.

Gardner: Larry Schmidt, similar question to you. What are some of the unique challenges that are facing the healthcare community as they try to improve on responsiveness, efficiency, and greater capabilities?

Schmidt: There are several things that have not really kept up with what technology is able to do today.

For example, the whole concept of personal observation comes into play in what we would call “value chains” that exist right now between a patient and a doctor. We look at things like mobile technologies and want to be able to leverage that to provide additional observation of an individual, so that the doctor can make a more complete diagnosis of some sickness or possibly some medication that a person is on.

We want to be able to see that observation in real life, as opposed to having to take that in at the office, which typically winds up happening. I don’t know about everybody else, but every time I go see my doctor, oftentimes I get what’s called white coat syndrome. My blood pressure will go up. But that’s not giving the doctor an accurate reading from the standpoint of providing great observations.

Technology has advanced to the point where we can do that in real time using mobile and other technologies, yet the communication flow, that information flow, doesn’t exist today, or is at best, not easily communicated between doctor and patient.

There are plenty of places that additional collaboration and communication can improve the whole healthcare delivery model.

If you look at the ecosystem, as Jim offered, there are plenty of places that additional collaboration and communication can improve the whole healthcare delivery model.

That’s what we’re about. We want to be able to find the places where the technology has advanced, where standards don’t exist today, and just fuel the idea of building common communication methods between those stakeholders and entities, allowing us to then further the flow of good information across the healthcare delivery model.

Gardner: Jason Uppal, let’s think about what, in addition to technology, architecture, and methodologies can bring to bear here? Is there also a lag in terms of process thinking in healthcare, as well as perhaps technology adoption?

Uppal: I’m going to refer to a presentation that I watched from a very well-known surgeon from Harvard, Dr. Atul Gawande. His point was is that, in the last 50 years, the medical industry has made great strides in identifying diseases, drugs, procedures, and therapies, but one thing that he was alluding to was that medicine forgot the cost, that everything is cost.

At what price?

Today, in his view, we can cure a lot of diseases and lot of issues, but at what price? Can anybody actually afford it?

Uppal

His view is that if healthcare is going to change and improve, it has to be outside of the medical industry. The tools that we have are better today, like collaborative tools that are available for us to use, and those are the ones that he was recommending that we need to explore further.

That is where enterprise architecture is a powerful methodology to use and say, “Let’s take a look at it from a holistic point of view of all the stakeholders. See what their information needs are. Get that information to them in real time and let them make the right decisions.”

Therefore, there is no reason for the health information to be stuck in organizations. It could go with where the patient and providers are, and let them make the best decision, based on the best practices that are available to them, as opposed to having siloed information.

So enterprise-architecture methods are most suited for developing a very collaborative environment. Dr. Gawande was pointing out that, if healthcare is going to improve, it has to think about it not as medicine, but as healthcare delivery.

There are definitely complexities that occur based on the different insurance models and how healthcare is delivered across and between countries.

Gardner: And it seems that not only are there challenges in terms of technology adoption and even operating more like an efficient business in some ways. We also have very different climates from country to country, jurisdiction to jurisdiction. There are regulations, compliance, and so forth.

Going back to you, Larry, how important of an issue is that? How complex does it get because we have such different approaches to healthcare and insurance from country to country?

Schmidt: There are definitely complexities that occur based on the different insurance models and how healthcare is delivered across and between countries, but some of the basic and fundamental activities in the past that happened as a result of delivering healthcare are consistent across countries.

As Jason has offered, enterprise architecture can provide us the means to explore what the art of the possible might be today. It could allow us the opportunity to see how innovation can occur if we enable better communication flow between the stakeholders that exist with any healthcare delivery model in order to give us the opportunity to improve the overall population.

After all, that’s what this is all about. We want to be able to enable a collaborative model throughout the stakeholders to improve the overall health of the population. I think that’s pretty consistent across any country that we might work in.

Ongoing work

Gardner: Jim Hietala, maybe you could help us better understand what’s going on within The Open Group and, even more specifically, at the conference in Philadelphia. There is the Population Health Working Group and there is work towards a vision of enabling the boundaryless information flow between the stakeholders. Any other information and detail you could offer would be great.[Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.]

Hietala: On Tuesday of the conference, we have a healthcare focus day. The keynote that morning will be given by Dr. David Nash, Dean of the Jefferson School of Population Health. He’ll give what’s sure to be a pretty interesting presentation, followed by a reactors’ panel, where we’ve invited folks from different stakeholder constituencies.

Hietala

We are going to have clinicians there. We’re going to have some IT folks and some actual patients to give their reaction to Dr. Nash’s presentation. We think that will be an interesting and entertaining panel discussion.

The balance of the day, in terms of the healthcare content, we have a workshop. Larry Schmidt is giving one of the presentations there, and Jason and myself and some other folks from our working group are involved in helping to facilitate and carry out the workshop.

The goal of it is to look into healthcare challenges, desired outcomes, the extended healthcare enterprise, and the extended healthcare IT enterprise and really gather those pain points that are out there around things like interoperability to surface those and develop a work program coming out of this.

We want to be able to enable a collaborative model throughout the stakeholders to improve the overall health of the population.

So we expect it to be an interesting day if you are in the healthcare IT field or just the healthcare field generally, it would definitely be a day well spent to check it out.

Gardner: Larry, you’re going to be talking on Tuesday. Without giving too much away, maybe you can help us understand the emphasis that you’re taking, the area that you’re going to be exploring.

Schmidt: I’ve titled the presentation “Remixing Healthcare through Enterprise Architecture.” Jason offered some thoughts as to why we want to leverage enterprise architecture to discipline healthcare. My thoughts are that we want to be able to make sure we understand how the collaborative model would work in healthcare, taking into consideration all the constituents and stakeholders that exist within the complete ecosystem of healthcare.

This is not just collaboration across the doctors, patients, and maybe the payers in a healthcare delivery model. This could be out as far as the drug companies and being able to get drug companies to a point where they can reorder their raw materials to produce new drugs in the case of an epidemic that might be occurring.

Real-time model

It would be a real-time model that allows us the opportunity to understand what’s truly happening, both to an individual from a healthcare standpoint, as well as to a country or a region within a country and so on from healthcare. This remixing of enterprise architecture is the introduction to that concept of leveraging enterprise architecture into this collaborative model.

Then, I would like to talk about some of the technologies that I’ve had the opportunity to explore around what is available today in technology. I believe we need to have some type of standardized messaging or collaboration models to allow us to further facilitate the ability of that technology to provide the value of healthcare delivery or betterment of healthcare to individuals. I’ll talk about that a little bit within my presentation and give some good examples.

It’s really interesting. I just traveled from my company’s home base back to my home base and I thought about something like a body scanner that you get into in the airport. I know we’re in the process of eliminating some of those scanners now within the security model from the airports, but could that possibly be something that becomes an element within healthcare delivery? Every time your body is scanned, there’s a possibility you can gather information about that, and allow that to become a part of your electronic medical record.

There is a lot of information available today that could be used in helping our population to be healthier.

Hopefully, that was forward thinking, but that kind of thinking is going to play into the art of the possible, with what we are going to be doing, both in this presentation and talking about that as part of the workshop.

Gardner: Larry, we’ve been having some other discussions with The Open Group around what they call Open Platform 3.0™, which is the confluence of big data, mobile, cloud computing, and social.

One of the big issues today is this avalanche of data, the Internet of things, but also the Internet of people. It seems that the more work that’s done to bring Open Platform 3.0 benefits to bear on business decisions, it could very well be impactful for centers and other data that comes from patients, regardless of where they are, to a medical establishment, regardless of where it is.

So do you think we’re really on the cusp of a significant shift in how medicine is actually conducted?

Schmidt: I absolutely believe that. There is a lot of information available today that could be used in helping our population to be healthier. And it really isn’t only the challenge of the communication model that we’ve been speaking about so far. It’s also understanding the information that’s available to us to take that and make that into knowledge to be applied in order to help improve the health of the population.

As we explore this from an as-is model in enterprise architecture to something that we believe we can first enable through a great collaboration model, through standardized messaging and things like that, I believe we’re going to get into even deeper detail around how information can truly provide empowered decisions to physicians and individuals around their healthcare.

So it will carry forward into the big data and analytics challenges that we have talked about and currently are talking about with The Open Group.

Healthcare framework

Gardner: Jason Uppal, we’ve also seen how in other business sectors, industries have faced transformation and have needed to rely on something like enterprise architecture and a framework like TOGAF® in order to manage that process and make it something that’s standardized, understood, and repeatable.

It seems to me that healthcare can certainly use that, given the pace of change, but that the impact on healthcare could be quite a bit larger in terms of actual dollars. This is such a large part of the economy that even small incremental improvements can have dramatic effects when it comes to dollars and cents.

So is there a benefit to bringing enterprise architect to healthcare that is larger and greater than other sectors because of these economics and issues of scale?

Uppal: That’s a great way to think about this thing. In other industries, applying enterprise architecture to do banking and insurance may be easily measured in terms of dollars and cents, but healthcare is a fundamentally different economy and industry.

It’s not about dollars and cents. It’s about people’s lives, and loved ones who are sick, who could very easily be treated, if they’re caught in time and the right people are around the table at the right time. So this is more about human cost than dollars and cents. Dollars and cents are critical, but human cost is the larger play here.

Whatever systems and methods are developed, they have to work for everybody in the world.

Secondly, when we think about applying enterprise architecture to healthcare, we’re not talking about just the U.S. population. We’re talking about global population here. So whatever systems and methods are developed, they have to work for everybody in the world. If the U.S. economy can afford an expensive healthcare delivery, what about the countries that don’t have the same kind of resources? Whatever methods and delivery mechanisms you develop have to work for everybody globally.

That’s one of the things that a methodology like TOGAF brings out and says to look at it from every stakeholder’s point of view, and unless you have dealt with every stakeholder’s concerns, you don’t have an architecture, you have a system that’s designed for that specific set of audience.

The cost is not this 18 percent of the gross domestic product in the U.S. that is representing healthcare. It’s the human cost, which is many multitudes of that. That’s is one of the areas where we could really start to think about how do we affect that part of the economy, not the 18 percent of it, but the larger part of the economy, to improve the health of the population, not only in the North America, but globally.

If that’s the case, then what really will be the impact on our greater world economy is improving population health, and population health is probably becoming our biggest problem in our economy.

We’ll be testing these methods at a greater international level, as opposed to just at an organization and industry level. This is a much larger challenge. A methodology like TOGAF is a proven and it could be stressed and tested to that level. This is a great opportunity for us to apply our tools and science to a problem that is larger than just dollars. It’s about humans.

All “experts”

Gardner: Jim Hietala, in some ways, we’re all experts on healthcare. When we’re sick, we go for help and interact with a variety of different services to maintain our health and to improve our lifestyle. But in being experts, I guess that also means we are witnesses to some of the downside of an unconnected ecosystem of healthcare providers and payers.

One of the things I’ve noticed in that vein is that I have to deal with different organizations that don’t seem to communicate well. If there’s no central process organizer, it’s really up to me as the patient to pull the lines together between the different services — tests, clinical observations, diagnosis, back for results from tests, sharing the information, and so forth.

Have you done any studies or have anecdotal information about how that boundaryless information flow would be still relevant, even having more of a centralized repository that all the players could draw on, sort of a collaboration team resource of some sort? I know that’s worked in other industries. Is this not a perfect opportunity for that boundarylessness to be managed?

Hietala: I would say it is. We all have experiences with going to see a primary physician, maybe getting sent to a specialist, getting some tests done, and the boundaryless information that’s flowing tends to be on paper delivered by us as patients in all the cases.

So the opportunity to improve that situation is pretty obvious to anybody who’s been in the healthcare system as a patient. I think it’s a great place to be doing work. There’s a lot of money flowing to try and address this problem, at least here in the U.S. with the HITECH Act and some of the government spending around trying to improve healthcare.

We’ll be testing these methods at a greater international level, as opposed to just at an organization and industry level.

You’ve got healthcare information exchanges that are starting to develop, and you have got lots of pain points for organizations in terms of trying to share information and not having standards that enable them to do it. It seems like an area that’s really a great opportunity area to bring lots of improvement.

Gardner: Let’s look for some examples of where this has been attempted and what the success brings about. I’ll throw this out to anyone on the panel. Do you have any examples that you can point to, either named organizations or anecdotal use case scenarios, of a better organization, an architectural approach, leveraging IT efficiently and effectively, allowing data to flow, putting in processes that are repeatable, centralized, organized, and understood. How does that work out?

Uppal: I’ll give you an example. One of the things that happens when a patient is admitted to hospital and in hospital is that they get what’s called a high-voltage care. There is staff around them 24×7. There are lots of people around, and every specialty that you can think of is available to them. So the patient, in about two or three days, starts to feel much better.

When that patient gets discharged, they get discharged to home most of the time. They go from very high-voltage care to next to no care. This is one of the areas where in one of the organizations we work with is able to discharge the patient and, instead of discharging them to the primary care doc, who may not receive any records from the hospital for several days, they get discharged to into a virtual team. So if the patient is at home, the virtual team is available to them through their mobile phone 24×7.

Connect with provider

If, at 3 o’clock in the morning, the patient doesn’t feel right, instead of having to call an ambulance to go to hospital once again and get readmitted, they have a chance to connect with their care provider at that time and say, “This is what the issue is. What do you want me to do next? Is this normal for the medication that I am on, or this is something abnormal that is happening?”

When that information is available to that care provider who may not necessarily have been part of the care team when the patient was in the hospital, that quick readily available information is key for keeping that person at home, as opposed to being readmitted to the hospital.

We all know that the cost of being in a hospital is 10 times more than it is being at home. But there’s also inconvenience and human suffering associated with being in a hospital, as opposed to being at home.

Those are some of the examples that we have, but they are very limited, because our current health ecosystem is a very organization specific, not  patient and provider specific. This is the area there is a huge room for opportunities for healthcare delivery, thinking about health information, not in the context of the organization where the patient is, as opposed to in a cloud, where it’s an association between the patient and provider and health information that’s there.

Extending that model will bring infinite value to not only reducing the cost, but improving the cost and quality of care.

In the past, we used to have emails that were within our four walls. All of a sudden, with Gmail and Yahoo Mail, we have email available to us anywhere. A similar thing could be happening for the healthcare record. This could be somewhere in the cloud’s eco setting, where it’s securely protected and used by only people who have granted access to it.

Those are some of the examples where extending that model will bring infinite value to not only reducing the cost, but improving the cost and quality of care.

Schmidt: Jason touched upon the home healthcare scenario and being able to provide touch points at home. Another place that we see evolving right now in the industry is the whole concept of mobile office space. Both countries, as well as rural places within countries that are developed, are actually getting rural hospitals and rural healthcare offices dropped in by helicopter to allow the people who live in those communities to have the opportunity to talk to a doctor via satellite technologies and so on.

The whole concept of a architecture around and being able to deal with an extension of what truly lines up being telemedicine is something that we’re seeing today. It would be wonderful if we could point to things like standards that allow us to be able to facilitate both the communication protocols as well as the information flows in that type of setting.

Many corporations can jump on the bandwagon to help the rural communities get the healthcare information and capabilities that they need via the whole concept of telemedicine.

That’s another area where enterprise architecture has come into play. Now that we see examples of that working in the industry today, I am hoping that as part of this working group, we’ll get to the point where we’re able to facilitate that much better, enabling innovation to occur for multiple companies via some of the architecture or the architecture work we are planning on producing.

Single view

Gardner: It seems that we’ve come a long way on the business side in many industries of getting a single view of the customer, as it’s called, the customer relationship management, big data, spreading the analysis around among different data sources and types. This sounds like a perfect fit for a single view of the patient across their life, across their care spectrum, and then of course involving many different types of organizations. But the government also needs to have a role here.

Jim Hietala, at The Open Group Conference in Philadelphia, you’re focusing on not only healthcare, but finance and government. Regarding the government and some of the agencies that you all have as members on some of your panels, how well do they perceive this need for enterprise architecture level abilities to be brought to this healthcare issue?

Hietala: We’ve seen encouraging signs from folks in government that are encouraging to us in bringing this work to the forefront. There is a recognition that there needs to be better data flowing throughout the extended healthcare IT ecosystem, and I think generally they are supportive of initiatives like this to make that happen.

Gardner: Of course having conferences like this, where you have a cross pollination between vertical industries, will perhaps allow some of the technical people to talk with some of the government people too and also have a conversation with some of the healthcare people. That’s where some of these ideas and some of the collaboration could also be very powerful.

We’ve seen encouraging signs from folks in government that are encouraging to us in bringing this work to the forefront.

I’m afraid we’re almost out of time. We’ve been talking about an interesting healthcare transition, moving into a new phase or even era of healthcare.

Our panel of experts have been looking at some of the trends in IT and how they are empowering improvement for how healthcare can be more responsive and efficient. And we’ve seen how healthcare industry organizations can take large scale transformation using cross-organizational collaboration, for example, and other such tools as big data, analytics, and cloud computing to help solve some of these issues.

This special BriefingsDirect discussion comes to you in conjunction with The Open Group Conference this July in Philadelphia. Registration to the conference remains open. Follow the conference on Twitter at #ogPHL, and you will hear more about healthcare or Open Platform 3.0 as well as enterprise transformation in the finance, government, and healthcare sectors.

With that, I’d like to thank our panel. We’ve been joined today by Jason Uppal, Chief Architect and Acting CEO at clinicalMessage. Thank you so much, Jason.

Uppal: Thank you, Dana.

Gardner: And also Larry Schmidt, Chief Technologist at HP for the Health and Life Sciences Industries. Thanks, Larry.

Schmidt: You bet, appreciate the time to share my thoughts. Thank you.

Gardner: And then also Jim Hietala, Vice President of Security at The Open Group. Thanks so much.

Hietala: Thank you, Dana.

Gardner: This is Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator throughout these thought leader interviews. Thanks again for listening and come back next time.

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As Platform 3.0 ripens, expect agile access and distribution of actionable intelligence across enterprises, says The Open Group panel

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here

This latest BriefingsDirect discussion, leading into the The Open Group Conference on July 15 in Philadelphia, brings together a panel of experts to explore the business implications of the current shift to so-called Platform 3.0.

Known as the new model through which big data, cloud, and mobile and social — in combination — allow for advanced intelligence and automation in business, Platform 3.0 has so far lacked standards or even clear definitions.

The Open Group and its community are poised to change that, and we’re here now to learn more how to leverage Platform 3.0 as more than a IT shift — and as a business game-changer. It will be a big topic at next week’s conference.

The panel: Dave Lounsbury, Chief Technical Officer at The Open Group; Chris Harding, Director of Interoperability at The Open Group, and Mark Skilton, Global Director in the Strategy Office at Capgemini. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

This special BriefingsDirect thought leadership interview comes in conjunction with The Open Group Conference, which is focused on enterprise transformation in the finance, government, and healthcare sectors. Registration to the conference remains open. Follow the conference on Twitter at #ogPHL. [Disclosure: The Open Group is a sponsor of this and other BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: A lot of people are still wrapping their minds around this notion of Platform 3.0, something that is a whole greater than the sum of the parts. Why is this more than an IT conversation or a shift in how things are delivered? Why are the business implications momentous?

Lounsbury: Well, Dana, there are lot of IT changes or technical changes going on that are bringing together a lot of factors. They’re turning into this sort of super-saturated solution of ideas and possibilities and this emerging idea that this represents a new platform. I think it’s a pretty fundamental change.

Lounsbury

If you look at history, not just the history of IT, but all of human history, you see that step changes in societies and organizations are frequently driven by communication or connectedness. Think about the evolution of speech or the invention of the alphabet or movable-type printing. These technical innovations that we’re seeing are bringing together these vast sources of data about the world around us and doing it in real time.

Further, we’re starting to see a lot of rapid evolution in how you turn data into information and presenting the information in a way such that people can make decisions on it. Given all that we’re starting to realize, we’re on the cusp of another step of connectedness and awareness.

Fundamental changes

This really is going to drive some fundamental changes in the way we organize ourselves. Part of what The Open Group is doing, trying to bring Platform 3.0 together, is to try to get ahead of this and make sure that we understand not just what technical standards are needed, but how businesses will need to adapt and evolve what business processes they need to put in place in order to take maximum advantage of this to see change in the way that we look at the information.

Harding: Enterprises have to keep up with the way that things are moving in order to keep their positions in their industries. Enterprises can’t afford to be working with yesterday’s technology. It’s a case of being able to understand the information that they’re presented, and make the best decisions.

Harding

We’ve always talked about computers being about input, process, and output. Years ago, the input might have been through a teletype, the processing on a computer in the back office, and the output on print-out paper.

Now, we’re talking about the input being through a range of sensors and social media, the processing is done on the cloud, and the output goes to your mobile device, so you have it wherever you are when you need it. Enterprises that stick in the past are probably going to suffer.

Gardner: Mark Skilton, the ability to manage data at greater speed and scale, the whole three Vs — velocity, volume, and value — on its own could perhaps be a game changing shift in the market. The drive of mobile devices into lives of both consumers and workers is also a very big deal.

Of course, cloud has been an ongoing evolution of emphasis towards agility and efficiency in how workloads are supported. But is there something about the combination of how these are coming together at this particular time that, in your opinion, substantiates The Open Group’s emphasis on this as a literal platform shift?

Skilton: It is exactly that in terms of the workloads. The world we’re now into is the multi-workload environment, where you have mobile workloads, storage and compute workloads, and social networking workloads. There are many different types of data and traffic today in different cloud platforms and devices.

Skilton

It has to do with not just one solution, not one subscription model — because we’re now into this subscription-model era … the subscription economy, as one group tends to describe it. Now, we’re looking for not only just providing the security, the infrastructure, to deliver this kind of capability to a mobile device, as Chris was saying. The question is, how can you do this horizontally across other platforms? How can you integrate these things? This is something that is critical to the new order.

So Platform 3.0 addressing this point by bringing this together. Just look at the numbers. Look at the scale that we’re dealing with — 1.7 billion mobile devices sold in 2012, and 6.8 billion subscriptions estimated according to the International Telecommunications Union (ITU) equivalent to 96 percent of the world population.

Massive growth

We had massive growth in scale of mobile data traffic and internet data expansion. Mobile data is increasing 18 percent fold from 2011 to 2016 reaching 130 exabytes annually.  We passed 1 zettabyte of global online data storage back in 2010 and IP data traffic predicted to pass 1.3 zettabytes by 2016, with internet video accounting for 61 percent of total internet data according to Cisco studies.

These studies also predict data center traffic combining network and internet based storage will reach 6.6 zettabytes annually, and nearly two thirds of this will be cloud based by 2016.  This is only going to grow as social networking is reaching nearly one in four people around the world with 1.7 billion using at least one form of social networking in 2013, rising to one in three people with 2.55 billion global audience by 2017 as another extraordinary figure from an eMarketing.com study.

It is not surprising that many industry analysts are seeing growth in technologies of mobility, social computing, big data and cloud convergence at 30 to 40 percent and the shift to B2C commerce passing $1 trillion in 2012 is just the start of a wider digital transformation.

These numbers speak volumes in terms of the integration, interoperability, and connection of the new types of business and social realities that we have today.

Gardner: Why should IT be thinking about this as a fundamental shift, rather than a modest change?

Lounsbury: A lot depends on how you define your IT organization. It’s useful to separate the plumbing from the water. If we think of the water as the information that’s flowing, it’s how we make sure that the water is pure and getting to the places where you need to have the taps, where you need to have the water, etc.

But the plumbing also has to be up to the job. It needs to have the capacity. It needs to have new tools to filter out the impurities from the water. There’s no point giving someone data if it’s not been properly managed or if there’s incorrect information.

What’s going to happen in IT is not only do we have to focus on the mechanics of the plumbing, where we see things like the big database that we’ve seen in the open-source  role and things like that nature, but there’s the analytics and the data stewardship aspects of it.

We need to bring in mechanisms, so the data is valid and kept up to date. We need to indicate its freshness to the decision makers. Furthermore, IT is going to be called upon, whether as part of the enterprise IP or where end users will drive the selection of what they’re going to do with analytic tools and recommendation tools to take the data and turn it into information. One of the things you can’t do with business decision makers is overwhelm them with big rafts of data and expect them to figure it out.

You really need to present the information in a way that they can use to quickly make business decisions. That is an addition to the role of IT that may not have been there traditionally — how you think about the data and the role of what, in the beginning, was called data scientist and things of that nature.

Shift in constituency

Skilton: I’d just like to add to Dave’s excellent points about, the shape of data has changed, but also about why should IT get involved. We’re seeing that there’s a shift in the constituency of who is using this data.

We have the Chief Marketing Officer and the Chief Procurement Officer and other key line of business managers taking more direct control over the uses of information technology that enable their channels and interactions through mobile, social and data analytics. We’ve got processes that were previously managed just by IT and are now being consumed by significant stakeholders and investors in the organization.

We have to recognize in IT that we are the masters of our own destiny. The information needs to be sorted into new types of mobile devices, new types of data intelligence, and ways of delivering this kind of service.

I read recently in MIT Sloan Management Review an article that asked what is the role of the CIO. There is still the critical role of managing the security, compliance, and performance of these systems. But there’s also a socialization of IT, and this is where  the  positioning architectures which are cross platform is key to  delivering real value to the business users in the IT community.

Gardner: How do we prevent this from going off the rails?

Harding: This a very important point. And to add to the difficulties, it’s not only that a whole set of different people are getting involved with different kinds of information, but there’s also a step change in the speed with which all this is delivered. It’s no longer the case, that you can say, “Oh well, we need some kind of information system to manage this information. We’ll procure it and get a program written” that a year later that would be in place in delivering reports to it.

Now, people are looking to make sense of this information on the fly if possible. It’s really a case of having the platforms be the standard technology platform and also the systems for using it, the business processes, understood and in place.

Then, you can do all these things quickly and build on learning from what people have gone in the past, and not go out into all sorts of new experimental things that might not lead anywhere. It’s a case of building up the standard platform in the industry best practice. This is where The Open Group can really help things along by being a recipient and a reflector of best practice and standard.

Skilton: Capgemini has been doing work in this area. I break it down into four levels of scalability. It’s the platform scalability of understanding what you can do with your current legacy systems in introducing cloud computing or big data, and the infrastructure that gives you this, what we call multiplexing of resources. We’re very much seeing this idea of introducing scalable platform resource management, and you see that a lot with the heritage of virtualization.

Going into networking and the network scalability, a lot of the customers have who inherited their old telecommunications networks are looking to introduce new MPLS type scalable networks. The reason for this is that it’s all about connectivity in the field. I meet a number of clients who are saying, “We’ve got this cloud service,” or “This service is in a certain area of my country. If I move to another parts of the country or I’m traveling, I can’t get connectivity.” That’s the big issue of scaling.

Another one is application programming interfaces (APIs). What we’re seeing now is an explosion of integration and application services using API connectivity, and these are creating huge opportunities of what Chris Anderson of Wired used to call the “long tail effect.” It is now a reality in terms of building that kind of social connectivity and data exchange that Dave was talking about.

Finally, there are the marketplaces. Companies needs to think about what online marketplaces they need for digital branding, social branding, social networks, and awareness of your customers, suppliers, and employees. Customers can see that these four levels are where they need to start thinking about for IT strategy, and Platform 3.0 is right on this target of trying to work out what are the strategies of each of these new levels of scalability.

Gardner: We’re coming up on The Open Group Conference in Philadelphia very shortly. What should we expect from that? What is The Open Group doing vis-à-vis Platform 3.0, and how can organizations benefit from seeing a more methodological or standardized approach to some way of rationalizing all of this complexity? [Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.]

Lounsbury: We’re still in the formational stages of  “third platform” or Platform 3.0 for The Open Group as an industry. To some extent, we’re starting pretty much at the ground floor with that in the Platform 3.0 forum. We’re leveraging a lot of the components that have been done previously by the work of the members of The Open Group in cloud, services-oriented architecture (SOA), and some of the work on the Internet of things.

First step

Our first step is to bring those things together to make sure that we’ve got a foundation to depart from. The next thing is that, through our Platform 3.0 Forum and the Steering Committee, we can ask people to talk about what their scenarios are for adoption of Platform 3.0?

That can range from things like the technological aspects of it and what standards are needed, but also to take a clue from our previous cloud working group. What are the best business practices in order to understand and then adopt some of these Platform 3.0 concepts to get your business using them?

What we’re really working toward in Philadelphia is to set up an exchange of ideas among the people who can, from the buy side, bring in their use cases from the supply side, bring in their ideas about what the technology possibilities are, and bring those together and start to shape a set of tracks where we can create business and technical artifacts that will help businesses adopt the Platform 3.0 concept.

Harding: We certainly also need to understand the business environment within which Platform 3.0 will be used. We’ve heard already about new players, new roles of various kinds that are appearing, and the fact that the technology is there and the business is adapting to this to use technology in new ways.

For example, we’ve heard about the data scientist. The data scientist is a new kind of role, a new kind of person, that is playing a particular part in all this within enterprises. We’re also hearing about marketplaces for services, new ways in which services are being made available and combined.

We really need to understand the actors in this new kind of business scenario. What are the pain points that people are having? What are the problems that need to be resolved in order to understand what kind of shape the new platform will have? That is one of the key things that the Platform 3.0 Forum members will be getting their teeth into.

Gardner: Looking to the future, when we think about the ability of the data to be so powerful when processed properly, when recommendations can be delivered to the right place at the right time, but we also recognize that there are limits to a manual or even human level approach to that, scientist by scientist, analysis by analysis.

When we think about the implications of automation, it seems like there were already some early examples of where bringing cloud, data, social, mobile, interactions, granularity of interactions together, that we’ve begun to see that how a recommendation engine could be brought to bear. I’m thinking about the Siri capability at Apple and even some of the examples of the Watson Technology at IBM.

So to our panel, are there unknown unknowns about where this will lead in terms of having extraordinary intelligence, a super computer or data center of super computers, brought to bear almost any problem instantly and then the result delivered directly to a center, a smart phone, any number of end points?

It seems that the potential here is mind boggling. Mark Skilton, any thoughts?

Skilton: What we’re talking about is the next generation of the Internet.  The advent of IPv6 and the explosion in multimedia services, will start to drive the next generation of the Internet.

I think that in the future, we’ll be talking about a multiplicity of information that is not just about services at your location or your personal lifestyle or your working preferences. We’ll see a convergence of information and services across multiple devices and new types of “co-presence services” that interact with your needs and social networks to provide predictive augmented information value.

When you start to get much more information about the context of where you are, the insight into what’s happening, and the predictive nature of these, it becomes something that becomes much more embedding into everyday life and in real time in context of what you are doing.

I expect to see much more intelligent applications coming forward on mobile devices in the next 5 to 10 years driven by this interconnected explosion of real time processing data, traffic, devices and social networking we describe in the scope of platform 3.0. This will add augmented intelligence and is something that’s really exciting and a complete game changer. I would call it the next killer app.

First-mover benefits

Gardner: There’s this notion of intelligence brought to bear rapidly in context, at a manageable cost. This seems to me a big change for businesses. We could, of course, go into the social implications as well, but just for businesses, that alone to me would be an incentive to get thinking and acting on this. So any thoughts about where businesses that do this well would be able to have significant advantage and first mover benefits?

Harding: Businesses always are taking stock. They understand their environments. They understand how the world that they live in is changing and they understand what part they play in it. It will be down to individual businesses to look at this new technical possibility and say, “So now this is where we could make a change to our business.” It’s the vision moment where you see a combination of technical possibility and business advantage that will work for your organization.

It’s going to be different for every business, and I’m very happy to say this, it’s something that computers aren’t going to be able to do for a very long time yet. It’s going to really be down to business people to do this as they have been doing for centuries and millennia, to understand how they can take advantage of these things.

So it’s a very exciting time, and we’ll see businesses understanding and developing their individual business visions as the starting point for a cycle of business transformation, which is what we’ll be very much talking about in Philadelphia. So yes, there will be businesses that gain advantage, but I wouldn’t point to any particular business, or any particular sector and say, “It’s going to be them” or “It’s going to be them.”

Gardner: Dave Lounsbury, a last word to you. In terms of some of the future implications and vision, where could this could lead in the not too distant future?

Lounsbury: I’d disagree a bit with my colleagues on this, and this could probably be a podcast on its own, Dana. You mentioned Siri, and I believe IBM just announced the commercial version of its Watson recommendation and analysis engine for use in some customer-facing applications.

I definitely see these as the thin end of the wedge on filling that gap between the growth of data and the analysis of data. I can imagine in not in the next couple of years, but in the next couple of technology cycles, that we’ll see the concept of recommendations and analysis as a service, to bring it full circle to cloud. And keep in mind that all of case law is data and all of the medical textbooks ever written are data. Pick your industry, and there is huge amount of knowledge base that humans must currently keep on top of.

This approach and these advances in the recommendation engines driven by the availability of big data are going to produce profound changes in the way knowledge workers produce their job. That’s something that businesses, including their IT functions, absolutely need to stay in front of to remain competitive in the next decade or so.

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Filed under ArchiMate®, Business Architecture, Cloud, Cloud/SOA, Conference, Data management, Enterprise Architecture, Platform 3.0, Professional Development, TOGAF®

Why is Cloud Adoption Taking so Long?

By Chris Harding, The Open Group

At the end of last year, Gartner predicted that cloud computing would become an integral part of IT in 2013 (http://www.gartner.com/DisplayDocument?doc_cd=230929). This looks a pretty safe bet. The real question is, why is it taking so long?

Cloud Computing

Cloud computing is a simple concept. IT resources are made available, within an environment that enables them to be used, via a communications network, as a service. It is used within enterprises to enable IT departments to meet users’ needs more effectively, and by external providers to deliver better IT services to their enterprise customers.

There are established vendors of products to fit both of these scenarios. The potential business benefits are well documented. There are examples of real businesses gaining those benefits, such as Netflix as a public cloud user (see http://www.zdnet.com/the-biggest-cloud-app-of-all-netflix-7000014298/ ), and Unilever and Lufthansa as implementers of private cloud (see http://www.computerweekly.com/news/2240114043/Unilever-and-Lufthansa-Systems-deploy-Azure-Private-cloud ).

Slow Pace of Adoption

Yet we are still talking of cloud computing becoming an integral part of IT. In the 2012 Open Group Cloud ROI survey, less than half of the respondents’ organizations were using cloud computing, although most of the rest were investigating its use. (See http://www.opengroup.org/sites/default/files/contentimages/Documents/cloud_roi_formal_report_12_19_12-1.pdf ). Clearly, cloud computing is not being used for enterprise IT as a matter of routine.

Cloud computing is now at least seven years old. Amazon’s “Elastic Compute Cloud” was launched in August 2006, and there are services that we now regard as cloud computing, though they may not have been called that, dating from before then. Other IT revolutions – personal computers, for example – have reached the point of being an integral part of IT in half the time. Why has it taken Cloud so long?

The Reasons

One reason is that using Cloud requires a high level of trust. You can lock your PC in your office, but you cannot physically secure your cloud resources. You must trust the cloud service provider. Such trust takes time to earn.

Another reason is that, although it is a simple concept, cloud computing is described in a rather complex way. The widely-accepted NIST definition (see http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf ) has three service models and four deployment models, giving a total of twelve distinct delivery combinations. Each combination has different business drivers, and the three service models are based on very different technical capabilities. Real products, of course, often do not exactly correspond to the definition, and their vendors describe them in product-specific terms. This complexity often leads to misunderstanding and confusion.

A third reason is that you cannot “mix and match” cloud services from different providers. The market is consolidating, with a few key players emerging as dominant at the infrastructure and platform levels. Each of them has its own proprietary interfaces. There are no real vendor-neutral standards. A recent Information Week article on Netflix (http://www.informationweek.co.uk/cloud-computing/platform/how-netflix-is-ruining-cloud-computing/240151650 ) describes some of the consequences. Customers are beginning to talk of “vendor lock-in” in a way that we haven’t seen since the days of mainframes.

The Portability and Interoperability Guide

The Open Group Cloud Computing Portability and Interoperability Guide addresses this last problem, by providing recommendations to customers on how best to achieve portability and interoperability when working with current cloud products and services. It also makes recommendations to suppliers and standards bodies on how standards and best practice should evolve to enable greater portability and interoperability in the future.

The Guide tackles the complexity of its subject by defining a simple Distributed Computing Reference Model. This model shows how cloud services fit into the mix of products and services used by enterprises in distributed computing solutions today. It identifies the major components of cloud-enabled solutions, and describes their portability and interoperability interfaces.

Platform 3.0

Cloud is not the only new game in town. Enterprises are looking at mobile computing, social computing, big data, sensors, and controls as new technologies that can transform their businesses. Some of these – mobile and social computing, for example – have caught on faster than Cloud.

Portability and interoperability are major concerns for these technologies too. There is a need for a standard platform to enable enterprises to use all of the new technologies, individually and in combination, and “mix and match” different products. This is the vision of the Platform 3.0 Forum, recently formed by The Open Group. The distributed computing reference model is an important input to this work.

The State of the Cloud

It is now at least becoming routine to consider cloud computing when architecting a new IT solution. The chances of it being selected however appear to be less than fifty-fifty, in spite of its benefits. The reasons include those mentioned above: lack of trust, complexity, and potential lock-in.

The Guide removes some of the confusion caused by the complexity, and helps enterprises assess their exposure to lock-in, and take what measures they can to prevent it.

The growth of cloud computing is starting to be constrained by lack of standards to enable an open market with free competition. The Guide contains recommendations to help the industry and standards bodies produce the standards that are needed.

Let’s all hope that the standards do appear soon. Cloud is, quite simply, a good idea. It is an important technology paradigm that has the potential to transform businesses, to make commerce and industry more productive, and to benefit society as a whole, just as personal computing did. Its adoption really should not be taking this long.

The Open Group Cloud Computing Portability and Interoperability Guide is available from The Open Group bookstore at https://www2.opengroup.org/ogsys/catalog/G135

Dr. Chris Harding is Director for Interoperability and SOA at The Open Group. He has been with The Open Group for more than ten years, and is currently responsible for managing and supporting its work on interoperability, including SOA and interoperability aspects of Cloud Computing, and the Platform 3.0 Forum. He is a member of the BCS, the IEEE and the AEA, and is a certified TOGAF® practitioner.

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Questions for the Upcoming Platform 3.0™ Tweet Jam

By Patty Donovan, The Open Group

Last week, we announced our upcoming tweet jam on Thursday, June 6 at 9:00 a.m. PT/12:00 p.m. ET/5:00 p.m. BST, which will examine how convergent technologies such as Big Data, Social, Mobile and The Internet of Things are impacting today’s business operations. We will also discuss the opportunities available to those organizations who keep pace with this rapid pace of change and how they might take steps to get there.

The discussion will be moderated by Dana Gardner (@Dana_Gardner), ZDNet – Briefings Direct, and we welcome both members of The Open Group and interested participants alike to join the session.

The discussion will be guided by these five questions:

- Does your organization see a convergence of emerging technologies such as social networking, mobile, cloud and the internet of things?

- How has this convergence affected your business?

- Are these changes causing you to change your IT platform; if so how?

- How is the data created by this convergence affecting business models or how you make business decisions?

- What new IT capabilities are needed to support new business models and decision making?

To join the discussion, please follow the #ogp3 and #ogChat hashtag during the allotted discussion time.

For more information about the tweet jam, guidelines and general background information, please visit our previous blog post.

If you have any questions prior to the event or would like to join as a participant, please direct them to Rob Checkal (rob.checkal at hotwirepr dot com) or leave a comment below. We anticipate a lively chat and hope you will be able to join us!

patricia donovanPatricia Donovan is Vice President, Membership & Events, at The Open Group and a member of its executive management team. In this role she is involved in determining the company’s strategic direction and policy as well as the overall management of that business area. Patricia joined The Open Group in 1988 and has played a key role in the organization’s evolution, development and growth since then. She also oversees the company’s marketing, conferences and member meetings. She is based in the U.S.

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Filed under Cloud, Cloud/SOA, Data management, Platform 3.0, Tweet Jam

Why should your business care about Platform 3.0™? A Tweet Jam

By Patty Donovan, The Open Group

On Thursday, June 6, The Open Group will host a tweet jam examining Platform 3.0™ and why businesses require it to remain relevant in today’s fast paced internet enabled business environment. Over recent years a number of convergent technologies have emerged which have the potential to disrupt the way we engage with each other in both our personal business lives. Many of us are familiar with the buzz words including Mobile, Social, Big Data, Cloud Computing, the Internet of Things, Machine-to-Machine (M2M) and Cosumerization of IT (CoIT) – but what do they mean for our current operating business environments and what should businesses be doing to ensure that they keep pace?

Gartner was the first to recognize this convergence of trends representing a number of architectural shifts which it called a ‘Nexus of Forces’. This Nexus was presented as both an opportunity in terms of innovation of new IT products and services and a threat for those who do not keep pace with evolution, rendering current Business Architectures obsolete.

Rather than tackle this challenge solo, The Open Group is working with a number of IT experts, analysts and thought leaders to better understand the opportunities available to businesses and the steps they need to take to get them there.

Please join us on Thursday, June 6 at 9:00 a.m. PT/12:00 p.m. ET/5:00 p.m. BST for a tweet jam, moderated by Dana Gardner (@Dana_Gardner), ZDNet – Briefings Direct, that will discuss and debate the issues around Platform 3.0™. Key areas that will be addressed during the discussion include: the specific technical trends (Big Data, Cloud, Consumerization of IT, etc.), and ways businesses can use them – and are already using them – to increase their business opportunity. We welcome Open Group members and interested participants from all backgrounds to join the session and interact with our panel thought leaders led by David Lounsbury, CTO and Chris Harding, Director of Interoperability from The Open Group. To access the discussion, please follow the #ogp3 and #ogChat hashtag during the allotted discussion time.

- Does your organization see a convergence of emerging technologies such as social networking, mobile, cloud and the internet of things?

- How has this convergence affected your business?

- Are these changes causing you to change your IT platform; if so how?

- How is the data created by this convergence affecting business models or how you make business decisions?

- What new IT capabilities are needed to support new business models and decision making?

And for those of you who are unfamiliar with tweet jams, here is some background information:

What Is a Tweet Jam?

A tweet jam is a one hour “discussion” hosted on Twitter. The purpose of the tweet jam is to share knowledge and answer questions on Platform 3.0™. Each tweet jam is led by a moderator and a dedicated group of experts to keep the discussion flowing. The public (or anyone using Twitter interested in the topic) is encouraged to join the discussion.

Participation Guidance

Whether you’re a newbie or veteran Twitter user, here are a few tips to keep in mind:

  • Have your first #ogChat or #ogp3 tweet be a self-introduction: name, affiliation, occupation.
  • Start all other tweets with the question number you’re responding to and the #ogChat or #ogp3 hashtag.
    • Sample: “There are already a number of organizations taking advantage of Platform 3.0 technology trends #ogp3”
    • Please refrain from product or service promotions. The goal of a tweet jam is to encourage an exchange of knowledge and stimulate discussion.
    • While this is a professional get-together, we don’t have to be stiff! Informality will not be an issue!
    • A tweet jam is akin to a public forum, panel discussion or Town Hall meeting – let’s be focused and thoughtful.

If you have any questions prior to the event or would like to join as a participant, please direct them to Rob Checkal (rob.checkal at hotwirepr dot com). We anticipate a lively chat and hope you will be able to join!

patricia donovanPatricia Donovan is Vice President, Membership & Events, at The Open Group and a member of its executive management team. In this role she is involved in determining the company’s strategic direction and policy as well as the overall management of that business area. Patricia joined The Open Group in 1988 and has played a key role in the organization’s evolution, development and growth since then. She also oversees the company’s marketing, conferences and member meetings. She is based in the U.S.

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Filed under Cloud, Cloud/SOA, Data management, Platform 3.0, Tweet Jam

The Interconnectedness of All Things

By Stuart Boardman, KPN

My admiration for Douglas Adams only seems to increase with the years.

Adams, in his quiet way, conveyed quite a few useful insights into both human behavior and how the world (and the universe) works – or seems to work – or seems at times not to work. One of his little masterpieces was “the interconnectedness of all things,” which was the insight that inspired the work of Dirk Gently, owner and sole operative of the Holistic Detective Agency. This wasn’t some piece of cosmic mysticism, but essentially a rather practical insistence on looking at the pieces of the puzzle as an interconnected whole, even when one doesn’t yet know what the completed puzzle will look like. Here’s how Dirk expressed it:

“I’m very glad you asked me that, Mrs. Rawlinson. The term `holistic’ refers to my conviction that what we are concerned with here is the fundamental interconnectedness of all things. I do not concern myself with such petty things as fingerprint powder, telltale pieces of pocket fluff and inane footprints. I see the solution to each problem as being detectable in the pattern and web of the whole. The connections between causes and effects are often much more subtle and complex than we with our rough and ready understanding of the physical world might naturally suppose, Mrs. Rawlinson.

Let me give you an example. If you go to an acupuncturist with toothache, he sticks a needle instead into your thigh. Do you know why he does that, Mrs. Rawlinson?

No, neither do I, Mrs. Rawlinson, but we intend to find out. A pleasure talking to you, Mrs. Rawlinson. Goodbye.”

Cloud, SOA, Enterprise Mobility, Social Media/Enterprise/Business, The Internet of Things, Big Data (you name it) – each in its own way is part of an overall tendency. The general trend is for enterprises to become increasingly involved in increasingly broad ecosystems. As a trend, it predates that list of Internet phenomena but it’s clear that they are dramatically accelerating the pace. Not only do they individually contribute to that trend but collectively they add another factor of both complexity and urgency to the picture. They are interconnected by cause and effect and by usage. Unfortunately that interconnectedness doesn’t (yet) involve very much interoperability.

Readers of this blog will know that The Open Group is starting a new initiative, Platform 3.0  which will be looking at these technologies as a whole and at how they might be considered to collectively represent some new kind of virtual computing platform. There’s an ongoing discussion of what the scope of such an initiative should be, to what extent it should concentrate on the technologies, to what extent on purely business aspects and to what extent we should concentrate on the whole, as opposed to the sum of the parts. One can also see this as one overarching phenomenon in which making a distinction between business and technology may not actually be meaningful.

Although no one (as far as I know) denies that each of these has its own specifics and deserves individual examination, people are starting to understand that we need to go with Dirk Gently and look at the “pattern and web of the whole”.

Open Group members and conference presenters have been pointing this out for a couple of years now but, like it or not, it often takes an analyst firm like Gartner to notice it for everyone else to start taking it seriously. What these organizations like to do is to pin labels on things. Give it a name, and you can kid yourself you know what it is. That fact in and of itself makes it easier for people – especially those who don’t like dealing with stuff you actually have to think about. It’s an example of the 42 problem I wrote about elsewhere.

Gartner frequently talks about the “Nexus of Forces.” Those of you who are not Trekkies may not understand why I fall over laughing at that one. For your benefit, the Nexus was this sort of cloud thing, which if you were able to jump into it, enabled you to live out your most treasured but unrealistic dreams. And in the Star Trek movie this was a big problem, because out there in the real world everything was going seriously pear shaped.

In my view, it’s crucial to tackle the general tendency. Organizations and in particular commercial organizations become part of what Jack Martin Leith calls a “Business Ecosystem”(jump to slide 11 in the link for the definition). If one goes back, say, ten years (maybe less), this tendency already manifested itself on the business side through the “outsourcing” of significant parts of the organization’s business processes to other organizations – partners. The result wasn’t simply a value chain but a value network, sometimes known as Extended Enterprise. Ten years later we see that Cloud can have the same effect on how even the processes retained within the organization are carried out. Social and mobile take this further and also take it out into the wider enterprise and out into that business ecosystem. Cloud, social and mobile involve technological interconnectedness. Social and mobile also involve business interconnectedness (one could argue that Cloud does too and I wouldn’t feel the need to disagree). The business of an enterprise becomes increasingly bound up with the business of other enterprises and as a result can be affected by changes and developments well outside its own range of control.

We know that the effects of these various technologies are interconnected at multiple levels, so it becomes increasingly important to understand how they will work together – or fail to work together. Or to put it more constructively, we need strategies and standards to ensure that they do work together to the extent that we can control them. We also need to understand what all the things are that we can’t control but might just jump out and bite us. There are already enough anti-patterns for the use of social media. Add to that the multi-channel implications of mobility, stir in a dose of Cloud and a bunch of machines exchanging messages without being able to ask each other, “excuse me, what did you mean by that?” It’s easy to see how things might go pear shaped while we’re having fun in the Nexus.

Does this lead to an unmanageable scope for Platform 3.0? I don’t think so. We’ll probably have to prioritize the work. Everyone has their own knowledge, experience and interests, so we may well do things of different granularity in parallel. That all needs to be discussed. But from my perspective, one of the first priorities will be to understand that interconnectedness, so we can work out where the needle needs to go to get rid of the pain.

Stuart Boardman is a Senior Business Consultant with KPN where he co-leads the Enterprise Architecture practice as well as the Cloud Computing solutions group. He is co-lead of The Open Group Cloud Computing Work Group’s Security for the Cloud and SOA project and a founding member of both The Open Group Cloud Computing Work Group and The Open Group SOA Work Group. Stuart is the author of publications by the Information Security Platform (PvIB) in The Netherlands and of his previous employer, CGI. He is a frequent speaker at conferences on the topics of Cloud, SOA, and Identity. 

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Filed under Enterprise Architecture, Platform 3.0

3 Steps to Proactively Address Board-Level Security Concerns

By E.G. Nadhan, HP

Last month, I shared the discussions that ensued in a Tweet Jam conducted by The Open Group on Big Data and Security where the key takeaway was: Protecting Data is Good.  Protecting Information generated from Big Data is priceless.  Security concerns around Big Data continue to the extent that it has become a Board-level concern as explained in this article in ComputerWorldUK.  Board-level concerns must be addressed proactively by enterprises.  To do so, enterprises must provide the business justification for such proactive steps needed to address such board-level concerns.

Nadhan blog image

At The Open Group Conference in Sydney in April, the session on “Which information risks are shaping our lives?” by Stephen Singam, Chief Technology Officer, HP Enterprise Security Services, Australia provides great insight on this topic.  In this session, Singam analyzes the current and emerging information risks while recommending a proactive approach to address them head-on with adversary-centric solutions.

The 3 steps that enterprises must take to proactively address security concerns are below:

Computing the cost of cyber-crime

The HP Ponemon 2012 Cost of Cyber Crime Study revealed that cyber attacks have more than doubled in a three year period with the financial impact increasing by nearly 40 percent. Here are the key takeaways from this research:

  • Cyber-crimes continue to be costly. The average annualized cost of cyber-crime for 56 organizations is $8.9 million per year, with a range of $1.4 million to $46 million.
  • Cyber attacks have become common occurrences. Companies experienced 102 successful attacks per week and 1.8 successful attacks per company per week in 2012.
  • The most costly cyber-crimes are those caused by denial of service, malicious insiders and web-based attacks.

When computing the cost of cyber-crime, enterprises must address direct, indirect and opportunity costs that result from the loss or theft of information, disruption to business operations, revenue loss and destruction of property, plant and equipment. The following phases of combating cyber-crime must also be factored in to comprehensively determine the total cost:

  1. Detection of patterns of behavior indicating an impending attack through sustained monitoring of the enabling infrastructure
  2. Investigation of the security violation upon occurrence to determine the underlying root cause and take appropriate remedial measures
  3. Incident response to address the immediate situation at hand, communicate the incidence of the attack raise all applicable alerts
  4. Containment of the attack by controlling its proliferation across the enterprise
  5. Recovery from the damages incurred as a result of the attack to ensure ongoing business operations based upon the business continuity plans in place

Identifying proactive steps that can be taken to address cyber-crime

  1. “Better get security right,” says HP Security Strategist Mary Ann Mezzapelle in her keynote on Big Data and Security at The Open Group Conference in Newport Beach. Asserting that proactive risk management is the most effective approach, Mezzapelle challenged enterprises to proactively question the presence of shadow IT, data ownership, usage of security tools and standards while taking a comprehensive approach to security end-to-end within the enterprise.
  2. Art Gilliland suggested that learning from cyber criminals and understanding their methods in this ZDNet article since the very frameworks enterprises strive to comply with (such as ISO and PCI) set a low bar for security that adversaries capitalize on.
  3. Andy Ellis discussed managing risk with psychology instead of brute force in his keynote at the 2013 RSA Conference.
  4. At the same conference, in another keynote, world re-knowned game-designer and inventor of SuperBetter, Jane McGonigal suggested the application of the “collective intelligence” that gaming generates can combat security concerns.
  5. In this interview, Bruce Schneier, renowned security guru and author of several books including LIARS & Outliers, suggested “Bad guys are going to invent new stuff — whether we want them to or not.” Should we take a cue from Hollywood and consider the inception of OODA loop into the security hacker’s mind?

The Balancing Act.

Can enterprises afford to take such proactive steps? Or more importantly, can they afford not to?

Enterprises must define their risk management strategy and determine the proactive steps that are best in alignment with their business objectives and information security standards.  This will enable organizations to better assess the cost of execution for such measures.  While the actual cost is likely to vary by enterprise, inaction is not an acceptable alternative.  Like all other critical corporate initiatives, these proactive measures must receive the board-level attention they deserve.

Enterprises must balance the cost of executing such proactive measures against the potential cost of data loss and reputational harm. This will ensure that the right proactive measures are taken with executive support.

How about you?  Has your enterprise taken the steps to assess the cost of cybercrime?  Have you considered various proactive steps to combat cybercrime?  Share your thoughts with me in the comments section below.

NadhanHP Distinguished Technologist, E.G.Nadhan has over 25 years of experience in the IT industry across the complete spectrum of selling, delivering and managing enterprise level solutions for HP customers. He is the founding co-chair for The Open Group SOCCI project and is also the founding co-chair for the Open Group Cloud Computing Governance project. Twitter handle @NadhanAtHP.

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Why Business Needs Platform 3.0

By Chris Harding, The Open Group

The Internet gives businesses access to ever-larger markets, but it also brings more competition. To prosper, they must deliver outstanding products and services. Often, this means processing the ever-greater, and increasingly complex, data that the Internet makes available. The question they now face is, how to do this without spending all their time and effort on information technology.

Web Business Success

The success stories of giants such as Amazon are well-publicized, but there are other, less well-known companies that have profited from the Web in all sorts of ways. Here’s an example. In 2000 an English illustrator called Jacquie Lawson tried creating greetings cards on the Internet. People liked what she did, and she started an e-business whose website is now ranked by Alexa as number 2712 in the world, and #1879 in the USA. This is based on website traffic and is comparable, to take a company that may be better known, with toyota.com, which ranks slightly higher in the USA (#1314) but somewhat lower globally (#4838).

A company with a good product can grow fast. This also means, though, that a company with a better product, or even just better marketing, can eclipse it just as quickly. Social networking site Myspace was once the most visited site in the US. Now it is ranked by Alexa as #196, way behind Facebook, which is #2.

So who ranks as #1? You guessed it – Google. Which brings us to the ability to process large amounts of data, where Google excels.

The Data Explosion

The World-Wide Web probably contains over 13 billion pages, yet you can often find the information that you want in seconds. This is made possible by technology that indexes this vast amount of data – measured in petabytes (millions of gigabytes) – and responds to users’ queries.

The data on the world-wide-web originally came mostly from people, typing it in by hand. In future, we will often use data that is generated by sensors in inanimate objects. Automobiles, for example, can generate data that can be used to optimize their performance or assess the need for maintenance or repair.

The world population is measured in billions. It is estimated that the Internet of Things, in which data is collected from objects, could enable us to track 100 trillion objects in real time – ten thousand times as many things as there are people, tirelessly pumping out information. The amount of available data of potential value to businesses is set to explode yet again.

A New Business Generation

It’s not just the amount of data to be processed that is changing. We are also seeing changes in the way data is used, the way it is processed, and the way it is accessed. Following The Open Group conference in January, I wrote about the convergence of social, Cloud, and mobile computing with Big Data. These are the new technical trends that are taking us into the next generation of business applications.

We don’t yet know what all those applications will be – who in the 1990’s would have predicted greetings cards as a Web application – but there are some exciting ideas. They range from using social media to produce market forecasts to alerting hospital doctors via tablets and cellphones when monitors detect patient emergencies. All this, and more, is possible with technology that we have now, if we can use it.

The Problem

But there is a problem. Although there is technology that enables businesses to use social, Cloud, and mobile computing, and to analyze and process massive amounts of data of different kinds, it is not necessarily easy to use. A plethora of products is emerging, with different interfaces, and with no ability to work with each other.  This is fine for geeks who love to play with new toys, but not so good for someone who wants to realize a new business idea and make money.

The new generation of business applications cannot be built on a mish-mash of unstable products, each requiring a different kind of specialist expertise. It needs a solid platform, generally understood by enterprise architects and software engineers, who can translate the business ideas into technical solutions.

The New Platform

Former VMware CEO and current Pivotal Initiative leader Paul Maritz describes the situation very well in his recent blog on GigaOM. He characterizes the new breed of enterprises, that give customers what they want, when they want it and where they want it, by exploiting the opportunities provided by new technologies, as consumer grade. Paul says that, “Addressing these opportunities will require new underpinnings; a new platform, if you like. At the core of this platform, which needs to be Cloud-independent to prevent lock-in, will be new approaches to handling big and fast (real-time) data.”

The Open Group has announced its new Platform 3.0 Forum to help the industry define a standard platform to meet this need. As The Open Group CTO Dave Lounsbury says in his blog, the new Forum will advance The Open Group vision of Boundaryless Information Flow™ by helping enterprises to take advantage of these convergent technologies. This will be accomplished by identifying a set of new platform capabilities, and architecting and standardizing an IT platform by which enterprises can reap the business benefits of Platform 3.0.

Business Focus

A business set up to design greetings cards should not spend its time designing communications networks and server farms. It cannot afford to spend time on such things. Someone else will focus on its core business and take its market.

The Web provided a platform that businesses of its generation could build on to do what they do best without being overly distracted by the technology. Platform 3.0 will do this for the new generation of businesses.

Help It Happen!

To find out more about the Platform 3.0 Forum, and take part in its formation, watch out for the Platform 3.0 web meetings that will be announced by e-mail and twitter, and on our home page.

Dr. Chris Harding is Director for Interoperability and SOA at The Open Group. He has been with The Open Group for more than ten years, and is currently responsible for managing and supporting its work on interoperability, including SOA and interoperability aspects of Cloud Computing, and the Platform 3.0 Forum. He is a member of the BCS, the IEEE and the AEA, and is a certified TOGAF practitioner.

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Business Architecture Tweet Jam – March 19

By Patty Donovan, The Open Group

On Tuesday, March 19 at 2:00 p.m. PT/9:00 p.m. BST/Wednesday, March 20 at 8:00 a.m. EDT (Sydney, Australia), The Open Group will host a tweet jam examining the topic of Business Architecture.

Today, Business Architecture is shaping and fostering enterprise transformation initiatives and continuous improvement throughout companies of all sizes. In The Open Group’s 2013 Predictions, Steve Philp, marketing Director for Open CA and Open CITS at The Open Group predicted that Business Architecture would continue to grow in prominence and visibility among executives. According to Steve’s prediction, “there are a number of key technology areas for 2013 where business architects will be called upon to engage with the business such as Cloud Computing, Big Data and social networking.” Steve also predicted that “the need to have competent Business Architects is a high priority in both the developed and emerging markets and the demand for Business Architects currently exceeds the supply.” Steve’s sentiments mirror an industry-wide perspective: It’s certain that Business Architecture will impact enterprises, but to what extent?

This tweet jam, sponsored by The Open Group, will take a step back and allow participants to discuss what the nascent topic of Business Architecture actually means. How is Business Architecture defined? What is the role of the business architect and how does Business Architecture relate to Enterprise Architecture?

Please join us for our upcoming Business Architecture tweet jam where leading experts will discuss this evolving topic.

And for those of you who are unfamiliar with tweet jams, here is some background information:

What Is a Tweet Jam?

A tweet jam is a one hour “discussion” hosted on Twitter. The purpose of the tweet jam is to share knowledge and answer questions on Business Architecture. Each tweet jam is led by a moderator and a dedicated group of experts to keep the discussion flowing. The public (or anyone using Twitter interested in the topic) is encouraged to join the discussion.

Participation Guidance

Whether you’re a newbie or veteran Twitter user, here are a few tips to keep in mind:

  • Have your first #ogChat tweet be a self-introduction: name, affiliation, occupation.
  • Start all other tweets with the question number you’re responding to and the #ogChat hashtag.
    • Sample: “Q1 Business Architecture has different meanings to different people within my organization #ogChat”
    • Please refrain from product or service promotions. The goal of a tweet jam is to encourage an exchange of knowledge and stimulate discussion.
    • While this is a professional get-together, we don’t have to be stiff! Informality will not be an issue!
    • A tweet jam is akin to a public forum, panel discussion or Town Hall meeting – let’s be focused and thoughtful.

If you have any questions prior to the event or would like to join as a participant, please direct them to Rod McLeod (rmcleod at bateman-group dot com). We anticipate a lively chat and hope you will be able to join!

patricia donovanPatricia Donovan is Vice President, Membership & Events, at The Open Group and a member of its executive management team. In this role she is involved in determining the company’s strategic direction and policy as well as the overall management of that business area. Patricia joined The Open Group in 1988 and has played a key role in the organization’s evolution, development and growth since then. She also oversees the company’s marketing, conferences and member meetings. She is based in the U.S.

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Beyond Big Data

By Chris Harding, The Open Group

The big bang that started The Open Group Conference in Newport Beach was, appropriately, a presentation related to astronomy. Chris Gerty gave a keynote on Big Data at NASA, where he is Deputy Program Manager of the Open Innovation Program. He told us how visualizing deep space and its celestial bodies created understanding and enabled new discoveries. Everyone who attended felt inspired to explore the universe of Big Data during the rest of the conference. And that exploration – as is often the case with successful space missions – left us wondering what lies beyond.

The Big Data Conference Plenary

The second presentation on that Monday morning brought us down from the stars to the nuts and bolts of engineering. Mechanical devices require regular maintenance to keep functioning. Processing the mass of data generated during their operation can improve safety and cut costs. For example, airlines can overhaul aircraft engines when it needs doing, rather than on a fixed schedule that has to be frequent enough to prevent damage under most conditions, but might still fail to anticipate failure in unusual circumstances. David Potter and Ron Schuldt lead two of The Open Group initiatives, Quantum Lifecycle management (QLM) and the Universal Data Element Framework (UDEF). They explained how a semantic approach to product lifecycle management can facilitate the big-data processing needed to achieve this aim.

Chris Gerty was then joined by Andras Szakal, vice-president and chief technology officer at IBM US Federal IMT, Robert Weisman, chief executive officer of Build The Vision, and Jim Hietala, vice-president of Security at The Open Group, in a panel session on Big Data that was moderated by Dana Gardner of Interarbor Solutions. As always, Dana facilitated a fascinating discussion. Key points made by the panelists included: the trend to monetize data; the need to ensure veracity and usefulness; the need for security and privacy; the expectation that data warehouse technology will exist and evolve in parallel with map/reduce “on-the-fly” analysis; the importance of meaningful presentation of the data; integration with cloud and mobile technology; and the new ways in which Big Data can be used to deliver business value.

More on Big Data

In the afternoons of Monday and Tuesday, and on most of Wednesday, the conference split into streams. These have presentations that are more technical than the plenary, going deeper into their subjects. It’s a pity that you can’t be in all the streams at once. (At one point I couldn’t be in any of them, as there was an important side meeting to discuss the UDEF, which is in one of the areas that I support as forum director). Fortunately, there were a few great stream presentations that I did manage to get to.

On the Monday afternoon, Tom Plunkett and Janet Mostow of Oracle presented a reference architecture that combined Hadoop and NoSQL with traditional RDBMS, streaming, and complex event processing, to enable Big Data analysis. One application that they described was to trace the relations between particular genes and cancer. This could have big benefits in disease prediction and treatment. Another was to predict the movements of protesters at a demonstration through analysis of communications on social media. The police could then concentrate their forces in the right place at the right time.

Jason Bloomberg, president of Zapthink – now part of Dovel – is always thought-provoking. His presentation featured the need for governance vitality to cope with ever changing tools to handle Big Data of ever increasing size, “crowdsourcing” to channel the efforts of many people into solving a problem, and business transformation that is continuous rather than a one-time step from “as is” to “to be.”

Later in the week, I moderated a discussion on Architecting for Big Data in the Cloud. We had a well-balanced panel made up of TJ Virdi of Boeing, Mark Skilton of Capgemini and Tom Plunkett of Oracle. They made some excellent points. Big Data analysis provides business value by enabling better understanding, leading to better decisions. The analysis is often an iterative process, with new questions emerging as answers are found. There is no single application that does this analysis and provides the visualization needed for understanding, but there are a number of products that can be used to assist. The role of the data scientist in formulating the questions and configuring the visualization is critical. Reference models for the technology are emerging but there are as yet no commonly-accepted standards.

The New Enterprise Platform

Jogging is a great way of taking exercise at conferences, and I was able to go for a run most mornings before the meetings started at Newport Beach. Pacific Coast Highway isn’t the most interesting of tracks, but on Tuesday morning I was soon up in Castaways Park, pleasantly jogging through the carefully-nurtured natural coastal vegetation, with views over the ocean and its margin of high-priced homes, slipways, and yachts. I reflected as I ran that we had heard some interesting things about Big Data, but it is now an established topic. There must be something new coming over the horizon.

The answer to what this might be was suggested in the first presentation of that day’s plenary, Mary Ann Mezzapelle, security strategist for HP Enterprise Services, talked about the need to get security right for Big Data and the Cloud. But her scope was actually wider. She spoke of the need to secure the “third platform” – the term coined by IDC to describe the convergence of social, cloud and mobile computing with Big Data.

Securing Big Data

Mary Ann’s keynote was not about the third platform itself, but about what should be done to protect it. The new platform brings with it a new set of security threats, and the increasing scale of operation makes it increasingly important to get the security right. Mary Ann presented a thoughtful analysis founded on a risk-based approach.

She was followed by Adrian Lane, chief technology officer at Securosis, who pointed out that Big Data processing using NoSQL has a different architecture from traditional relational data processing, and requires different security solutions. This does not necessarily mean new techniques; existing techniques can be used in new ways. For example, Kerberos may be used to secure inter-node communications in map/reduce processing. Adrian’s presentation completed the Tuesday plenary sessions.

Service Oriented Architecture

The streams continued after the plenary. I went to the Distributed Services Architecture stream, which focused on SOA.

Bill Poole, enterprise architect at JourneyOne in Australia, described how to use the graphical architecture modeling language ArchiMate® to model service-oriented architectures. He illustrated this using a case study of a global mining organization that wanted to consolidate its two existing bespoke inventory management applications into a single commercial off-the-shelf application. It’s amazing how a real-world case study can make a topic come to life, and the audience certainly responded warmly to Bill’s excellent presentation.

Ali Arsanjani, chief technology officer for Business Performance and Service Optimization, and Heather Kreger, chief technology officer for International Standards, both at IBM, described the range of SOA standards published by The Open Group and available for use by enterprise architects. Ali was one of the brains that developed the SOA Reference Architecture, and Heather is a key player in international standards activities for SOA, where she has helped The Open Group’s Service Integration Maturity Model and SOA Governance Framework to become international standards, and is working on an international standard SOA reference architecture.

Cloud Computing

To start Wednesday’s Cloud Computing streams, TJ Virdi, senior enterprise architect at The Boeing Company, discussed use of TOGAF® to develop an Enterprise Architecture for a Cloud ecosystem. A large enterprise such as Boeing may use many Cloud service providers, enabling collaboration between corporate departments, partners, and regulators in a complex ecosystem. Architecting for this is a major challenge, and The Open Group’s TOGAF for Cloud Ecosystems project is working to provide guidance.

Stuart Boardman of KPN gave a different perspective on Cloud ecosystems, with a case study from the energy industry. An ecosystem may not necessarily be governed by a single entity, and the participants may not always be aware of each other. Energy generation and consumption in the Netherlands is part of a complex international ecosystem involving producers, consumers, transporters, and traders of many kinds. A participant may be involved in several ecosystems in several ways: a farmer for example, might consume energy, have wind turbines to produce it, and also participate in food production and transport ecosystems.

Penelope Gordon of 1-Plug Corporation explained how choice and use of business metrics can impact Cloud service providers. She worked through four examples: a start-up Software-as-a-Service provider requiring investment, an established company thinking of providing its products as cloud services, an IT department planning to offer an in-house private Cloud platform, and a government agency seeking budget for government Cloud.

Mark Skilton, director at Capgemini in the UK, gave a presentation titled “Digital Transformation and the Role of Cloud Computing.” He covered a very broad canvas of business transformation driven by technological change, and illustrated his theme with a case study from the pharmaceutical industry. New technology enables new business models, giving competitive advantage. Increasingly, the introduction of this technology is driven by the business, rather than the IT side of the enterprise, and it has major challenges for both sides. But what new technologies are in question? Mark’s presentation had Cloud in the title, but also featured social and mobile computing, and Big Data.

The New Trend

On Thursday morning I took a longer run, to and round Balboa Island. With only one road in or out, its main street of shops and restaurants is not a through route and the island has the feel of a real village. The SOA Work Group Steering Committee had found an excellent, and reasonably priced, Italian restaurant there the previous evening. There is a clear resurgence of interest in SOA, partly driven by the use of service orientation – the principle, rather than particular protocols – in Cloud Computing and other new technologies. That morning I took the track round the shoreline, and was reminded a little of Dylan Thomas’s “fishing boat bobbing sea.” Fishing here is for leisure rather than livelihood, but I suspected that the fishermen, like those of Thomas’s little Welsh village, spend more time in the bar than on the water.

I thought about how the conference sessions had indicated an emerging trend. This is not a new technology but the combination of four current technologies to create a new platform for enterprise IT: Social, Cloud, and Mobile computing, and Big Data. Mary Ann Mezzapelle’s presentation had referenced IDC’s “third platform.” Other discussions had mentioned Gartner’s “Nexus of forces,” the combination of Social, Cloud and Mobile computing with information that Gartner says is transforming the way people and businesses relate to technology, and will become a key differentiator of business and technology management. Mark Skilton had included these same four technologies in his presentation. Great minds, and analyst corporations, think alike!

I thought also about the examples and case studies in the stream presentations. Areas as diverse as healthcare, manufacturing, energy and policing are using the new technologies. Clearly, they can deliver major business benefits. The challenge for enterprise architects is to maximize those benefits through pragmatic architectures.

Emerging Standards

On the way back to the hotel, I remarked again on what I had noticed before, how beautifully neat and carefully maintained the front gardens bordering the sidewalk are. I almost felt that I was running through a public botanical garden. Is there some ordinance requiring people to keep their gardens tidy, with severe penalties for anyone who leaves a lawn or hedge unclipped? Is a miserable defaulter fitted with a ball and chain, not to be removed until the untidy vegetation has been properly trimmed, with nail clippers? Apparently not. People here keep their gardens tidy because they want to. The best standards are like that: universally followed, without use or threat of sanction.

Standards are an issue for the new enterprise platform. Apart from the underlying standards of the Internet, there really aren’t any. The area isn’t even mapped out. Vendors of Social, Cloud, Mobile, and Big Data products and services are trying to stake out as much valuable real estate as they can. They have no interest yet in boundaries with neatly-clipped hedges.

This is a stage that every new technology goes through. Then, as it matures, the vendors understand that their products and services have much more value when they conform to standards, just as properties have more value in an area where everything is neat and well-maintained.

It may be too soon to define those standards for the new enterprise platform, but it is certainly time to start mapping out the area, to understand its subdivisions and how they inter-relate, and to prepare the way for standards. Following the conference, The Open Group has announced a new Forum, provisionally titled Open Platform 3.0, to do just that.

The SOA and Cloud Work Groups

Thursday was my final day of meetings at the conference. The plenary and streams presentations were done. This day was for working meetings of the SOA and Cloud Work Groups. I also had an informal discussion with Ron Schuldt about a new approach for the UDEF, following up on the earlier UDEF side meeting. The conference hallways, as well as the meeting rooms, often see productive business done.

The SOA Work Group discussed a certification program for SOA professionals, and an update to the SOA Reference Architecture. The Open Group is working with ISO and the IEEE to define a standard SOA reference architecture that will have consensus across all three bodies.

The Cloud Work Group had met earlier to further the TOGAF for Cloud ecosystems project. Now it worked on its forthcoming white paper on business performance metrics. It also – though this was not on the original agenda – discussed Gartner’s Nexus of Forces, and the future role of the Work Group in mapping out the new enterprise platform.

Mapping the New Enterprise Platform

At the start of the conference we looked at how to map the stars. Big Data analytics enables people to visualize the universe in new ways, reach new understandings of what is in it and how it works, and point to new areas for future exploration.

As the conference progressed, we found that Big Data is part of a convergence of forces. Social, mobile, and Cloud Computing are being combined with Big Data to form a new enterprise platform. The development of this platform, and its roll-out to support innovative applications that deliver more business value, is what lies beyond Big Data.

At the end of the conference we were thinking about mapping the new enterprise platform. This will not require sophisticated data processing and analysis. It will take discussions to create a common understanding, and detailed committee work to draft the guidelines and standards. This work will be done by The Open Group’s new Open Platform 3.0 Forum.

The next Open Group conference is in the week of April 15, in Sydney, Australia. I’m told that there’s some great jogging there. More importantly, we’ll be reflecting on progress in mapping Open Platform 3.0, and thinking about what lies ahead. I’m looking forward to it already.

Dr. Chris Harding is Director for Interoperability and SOA at The Open Group. He has been with The Open Group for more than ten years, and is currently responsible for managing and supporting its work on interoperability, including SOA and interoperability aspects of Cloud Computing. He is a member of the BCS, the IEEE and the AEA, and is a certified TOGAF practitioner.

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Complexity from Big Data and Cloud Trends Makes Architecture Tools like ArchiMate and TOGAF More Powerful, Says Expert Panel

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here: Complexity from Big Data and Cloud Trends Makes Architecture Tools like ArchiMate and TOGAF More Powerful, Says Expert Panel, or read the transcript here.

We recently assembled a panel of Enterprise Architecture (EA) experts to explain how such simultaneous and complex trends as big data, Cloud Computing, security, and overall IT transformation can be helped by the combined strengths of The Open Group Architecture Framework (TOGAF®) and the ArchiMate® modeling language.

The panel consisted of Chris Forde, General Manager for Asia-Pacific and Vice President of Enterprise Architecture at The Open Group; Iver Band, Vice Chair of The Open Group ArchiMate Forum and Enterprise Architect at The Standard, a diversified financial services company; Mike Walker, Senior Enterprise Architecture Adviser and Strategist at HP and former Director of Enterprise Architecture at DellHenry Franken, the Chairman of The Open Group ArchiMate Forum and Managing Director at BIZZdesign, and Dave Hornford, Chairman of the Architecture Forum at The Open Group and Managing Partner at Conexiam. I served as the moderator.

This special BriefingsDirect thought leadership interview series comes to you in conjunction with The Open Group Conference recently held in Newport Beach, California. The conference focused on “Big Data — he transformation we need to embrace today.” [Disclosure: The Open Group and HP are sponsors ofBriefingsDirect podcasts.]

Here are some excerpts:

Gardner: Is there something about the role of the enterprise architect that is shifting?

Walker: There is less of a focus on the traditional things we come to think of EA such as standards, governance and policies, but rather into emerging areas such as the soft skills, Business Architecture, and strategy.

To this end I see a lot in the realm of working directly with the executive chain to understand the key value drivers for the company and rationalize where they want to go with their business. So we’re moving into a business-transformation role in this practice.

At the same time, we’ve got to be mindful of the disruptive external technology forces coming in as well. EA can’t just divorce from the other aspects of architecture as well. So the role that enterprise architects play becomes more and more important and elevated in the organization.

Two examples of this disruptive technology that are being focused on at the conference are Big Data and Cloud Computing. Both are providing impacts to our businesses not because of some new business idea but because technology is available to enhance or provide new capabilities to our business. The EA’s still do have to understand these new technology innovations and determine how they will apply to the business.

We need to get really good enterprise architects, it’s difficult to find good ones. There is a shortage right now especially given that a lot of focus is being put on the EA department to really deliver sound architectures.

Not standalone

Gardner: We’ve been talking a lot here about Big Data, but usually that’s not just a standalone topic. It’s Big Data and Cloud, Cloud, mobile and security.

So with these overlapping and complex relationships among multiple trends, why is EA and things like the TOGAF framework and the ArchiMate modeling language especially useful?

Band: One of the things that has been clear for a while now is that people outside of IT don’t necessarily have to go through the technology function to avail themselves of these technologies any more. Whether they ever had to is really a question as well.

One of things that EA is doing, and especially in the practice that I work in, is using approaches like the ArchiMate modeling language to effect clear communication between the business, IT, partners and other stakeholders. That’s what I do in my daily work, overseeing our major systems modernization efforts. I work with major partners, some of which are offshore.

I’m increasingly called upon to make sure that we have clear processes for making decisions and clear ways of visualizing the different choices in front of us. We can’t always unilaterally dictate the choice, but we can make the conversation clearer by using frameworks like the TOGAF standard and the ArchiMate modeling language, which I use virtually every day in my work.

Hornford: The fundamental benefit of these tools is the organization realizing its capability and strategy. I just came from a session where a fellow quoted a Harvard study, which said that around a third of executives thought their company was good at executing on its strategy. He highlighted that this means that two-thirds are not good at executing on their strategy.

If you’re not good at executing on your strategy and you’ve got Big Data, mobile, consumerization of IT and Cloud, where are you going? What’s the correct approach? How does this fit into what you were trying to accomplish as an enterprise?

An enterprise architect that is doing their job is bringing together the strategy, goals and objectives of the organization. Also, its capabilities with the techniques that are available, whether it’s offshoring, onshoring, Cloud, or Big Data, so that the organization is able to move forward to where it needs to be, as opposed to where it’s going to randomly walk to.

Forde: One of the things that has come out in several of the presentations is this kind of capability-based planning, a technique in EA to get their arms around this thing from a business-driver perspective. Just to polish what Dave said a little bit, it’s connecting all of those things. We see enterprises talking about a capability-based view of things on that basis.

Gardner: Let’s get a quick update. The TOGAF framework, where are we and what have been the highlights from this particular event?

Minor upgrade

Hornford: In the last year, we’ve published a minor upgrade for TOGAF version 9.1 which was based upon cleaning up consistency in the language in the TOGAF documentation. What we’re working on right now is a significant new release, the next release of the TOGAF standard, which is dividing the TOGAF documentation to make it more consumable, more consistent and more useful for someone.

Today, the TOGAF standard has guidance on how to do something mixed into the framework of what you should be doing. We’re peeling those apart. So with that peeled apart, we won’t have guidance that is tied to classic application architecture in a world of Cloud.

What we find when we have done work with the Banking Industry Architecture Network (BIAN) for banking architecture, Sherwood Applied Business Security Architecture (SABSA) for security architecture, and the TeleManagement Forum, is that the concepts in the TOGAF framework work across industries and across trends. We need to move the guidance into a place so that we can be far nimbler on how to tie Cloud with my current strategy, how to tie consumerization of IT with on-shoring?

Franken: The ArchiMate modeling language turned two last year, and the ArchiMate 1.0 standard is the language to model out the core of your EA. The ArchiMate 2.0 standard added two specifics to it to make it better aligned also to the process of EA.

According to the TOGAF standard, this is being able to model out the motivation, why you’re doing EA, stakeholders and the goals that drive us. The second extension to the ArchiMate standard is being able to model out its planning and migration.

So with the core EA and these two extensions, together with the TOGAF standard process working, you have a good basis on getting EA to work in your organization.

Gardner: Mike, fill us in on some of your thoughts about the role of information architecture vis-à-vis the larger business architect and enterprise architect roles.

Walker: Information architecture is an interesting topic in that it hasn’t been getting a whole lot of attention until recently.

Information architecture is an aspect of Enterprise Architecture that enables an information strategy or business solution through the definition of the company’s business information assets, their sources, structure, classification and associations that will prescribe the required application architecture and technical capabilities.

Information architecture is the bridge between the Business Architecture world and the application and technology architecture activities.

The reason I say that is because information architecture is a business-driven discipline that details the information strategy of the company. As we know, and from what we’ve heard at the conference keynotes like in the case of NASA, Big Data, and security presentations, the preservation and classification of that information is vital to understanding what your architecture should be.

Least matured

From an industry perspective, this is one of the least matured, as far as being incorporated into a formal discipline. The TOGAF standard actually has a phase dedicated to it in data architecture. Again, there are still lots of opportunities to grow and incorporate additional methods, models and tools by the enterprise information management discipline.

Enterprise information management not only it captures traditional topic areas like master data management (MDM), metadata and unstructured types of information architecture but also focusing on the information governance, and the architecture patterns and styles implemented in MDM, Big Data, etc. There is a great deal of opportunity there.

From the role of information architects, I’m seeing more and more traction in the industry as a whole. I’ve dealt with an entire group that’s focused on information architecture and building up an enterprise information management practice, so that we can take our top line business strategies and understand what architectures we need to put there.

This is a critical enabler for global companies, because oftentimes they’re restricted by regulation, typically handled at a government or regional area. This means we have to understand that we build our architecture. So it’s not about the application, but rather the data that it processes, moves, or transforms.

Gardner: Up until not too long ago, the conventional thinking was that applications generate data. Then you treat the data in some way so that it can be used, perhaps by other applications, but that the data was secondary to the application.

But there’s some shift in that thinking now more toward the idea that the data is the application and that new applications are designed to actually expand on the data’s value and deliver it out to mobile tiers perhaps. Does that follow in your thinking that the data is actually more prominent as a resource perhaps on par with applications?

Walker: You’re spot on, Dana. Before the commoditization of these technologies that resided on premises, we could get away with starting at the application layer and work our way back because we had access to the source code or hardware behind our firewalls. We could throw servers out, and we used to put the firewalls in front of the data to solve the problem with infrastructure. So we didn’t have to treat information as a first-class citizen. Times have changed, though.

Information access and processing is now democratized and it’s being pushed as the first point of presentment. A lot of times this is on a mobile device and even then it’s not the corporate’s mobile device, but your personal device. So how do you handle that data?

It’s the same way with Cloud, and I’ll give you a great example of this. I was working as an adviser for a company, and they were looking at their Cloud strategy. They had made a big bet on one of the big infrastructures and Cloud-service providers. They looked first at what the features and functions that that Cloud provider could provide, and not necessarily the information requirements. There were two major issues that they ran into, and that was essentially a showstopper. They had to pull off that infrastructure.

The first one was that in that specific Cloud provider’s terms of service around intellectual property (IP) ownership. Essentially, that company was forced to cut off their IP rights.

Big business

As you know, IP is a big business these days, and so that was a showstopper. It actually broke the core regulatory laws around being able to discover information.

So focusing on the applications to make sure it meets your functional needs is important. However, we should take a step back and look at the information first and make sure that for the people in your organization who can’t say no, their requirements are satisfied.

Gardner: Data architecture is it different from EA and Business Architecture, or is it a subset? What’s the relationship, Dave?

Hornford: Data architecture is part of an EA. I won’t use the word subset, because a subset starts to imply that it is a distinct thing that you can look at on its own. You cannot look at your Business Architecture without understanding your information architecture. When you think about Big Data, cool. We’ve got this pile of data in the corner. Where did it come from? Can we use it? Do we actually have legitimate rights, as Mike highlighted, to use this information? Are we allowed to mix it and who mixes it?

When we look at how our business is optimized, they normally optimize around work product, what the organization is delivering. That’s very easy. You can see who consumes your work product. With information, you often have no idea who consumes your information. So now we have provenance, we have source and as we move for global companies, we have the trends around consumerization, Cloud and simply tightening cycle time.

Gardner: Of course, the end game for a lot of the practitioners here is to create that feedback loop of a lifecycle approach, rapid information injection and rapid analysis that could be applied. So what are some of the ways that these disciplines and tools can help foster that complete lifecycle?

Band: The disciplines and tools can facilitate the right conversations among different stakeholders. One of the things that we’re doing at The Standard is building cadres equally balanced between people in business and IT.

We’re training them in information management, going through a particular curriculum, and having them study for an information management certification that introduces a lot of these different frameworks and standard concepts.

Creating cadres

We want to create these cadres to be able to solve tough and persistent information management problems that affect all companies in financial services, because information is a shared asset. The purpose of the frameworks is to ensure proper stewardship of that asset across disciplines and across organizations within an enterprise.

Hornford: The core is from the two standards that we have, the ArchiMate standard and the TOGAF standard. The TOGAF standard has, from its early roots, focused on the components of EA and how to build a consistent method of understanding of what I’m trying to accomplish, understanding where I am, and where I need to be to reach my goal.

When we bring in the ArchiMate standard, I have a language, a descriptor, a visual descriptor that allows me to cross all of those domains in a consistent description, so that I can do that traceability. When I pull in this lever or I have this regulatory impact, what does it hit me with, or if I have this constraint, what does it hit me with?

If I don’t do this, if I don’t use the framework of the TOGAF standard, or I don’t use the discipline of formal modeling in the ArchiMate standard, we’re going to do it anecdotally. We’re going to trip. We’re going to fall. We’re going to have a non-ending series of surprises, as Mike highlighted.

“Oh, terms of service. I am violating the regulations. Beautiful. Let’s take that to our executive and tell him right as we are about to go live that we have to stop, because we can’t get where we want to go, because we didn’t think about what it took to get there.” And that’s the core of EA in the frameworks.

Walker: To build on what Dave has just talked about and going back to your first question Dana, the value statement on TOGAF from a business perspective. The businesses value of TOGAF is that they get a repeatable and a predictable process for building out our architectures that properly manage risks and reliably produces value.

The TOGAF framework provides a methodology to ask what problems you’re trying to solve and where you are trying to go with your business opportunities or challenges. That leads to Business Architecture, which is really a rationalization in technical or architectural terms the distillation of the corporate strategy.

From there, what you want to understand is information — how does that translate, what information architecture do we need to put in place? You get into all sorts of things around risk management, etc., and then it goes on from there, until what we were talking about earlier about information architecture.

If the TOGAF standard is applied properly you can achieve the same result every time, That is what interests business stakeholders in my opinion. And the ArchiMate modeling language is great because, as we talked about, it provides very rich visualizations so that people cannot only show a picture, but tie information together. Different from other aspects of architecture, information architecture is less about the boxes and more about the lines.

Quality of the individuals

Forde: Building on what Dave was saying earlier and also what Iver was saying is that while the process and the methodology and the tools are of interest, it’s the discipline and the quality of the individuals doing the work

Iver talked about how the conversation is shifting and the practice is improving to build communications groups that have a discipline to operate around. What I am hearing is implied, but actually I know what specifically occurs, is that we end up with assets that are well described and reusable.

And there is a point at which you reach a critical mass that these assets become an accelerator for decision making. So the ability of the enterprise and the decision makers in the enterprise at the right level to respond is improved, because they have a well disciplined foundation beneath them.

A set of assets that are reasonably well-known at the right level of granularity for them to absorb the information and the conversation is being structured so that the technical people and the business people are in the right room together to talk about the problems.

This is actually a fairly sophisticated set of operations that I am discussing and doesn’t happen overnight, but is definitely one of the things that we see occurring with our members in certain cases.

Hornford: I want to build on that what Chris said. It’s actually the word “asset.” While he was talking, I was thinking about how people have talked about information as an asset. Most of us don’t know what information we have, how it’s collected, where it is, but we know we have got a valuable asset.

I’ll use an analogy. I have a factory some place in the world that makes stuff. Is that an asset? If I know that my factory is able to produce a particular set of goods and it’s hooked into my supply chain here, I’ve got an asset. Before that, I just owned a thing.

I was very encouraged listening to what Iver talked about. We’re building cadres. We’re building out this approach and I have seen this. I’m not using that word, but now I’m stealing that word. It’s how people build effective teams, which is not to take a couple of specialists and put them in an ivory tower, but it’s to provide the method and the discipline of how we converse about it, so that we can have a consistent conversation.

When I tie it with some of the tools from the Architecture Forum and the ArchiMate Forum, I’m able to consistently describe it, so that I now have an asset I can identify, consume and produce value from.

Business context

Forde: And this is very different from data modeling. We are not talking about entity relationship, junk at the technical detail, or third normal form and that kind of stuff. We’re talking about a conversation that’s occurring around the business context of what needs to go on supported by the right level of technical detail when you need to go there in order to clarify.

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The Open Group Panel Explores How the Big Data Era Now Challenges the IT Status Quo

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here: The Open Group panel explores how the Big Data era now challenges the IT status quo, or view the on-demand video recording on this discussion here: http://new.livestream.com/opengroup/events/1838807.

We recently assembled a panel of experts to explore how Big Data changes the status quo for architecting the enterprise. The bottom line from the discussion is that large enterprises should not just wade into Big Data as an isolated function, but should anticipate the strategic effects and impacts of Big Data — as well the simultaneous complicating factors of Cloud Computing and mobile– as soon as possible.

The panel consisted of Robert Weisman, CEO and Chief Enterprise Architect at Build The Vision; Andras Szakal, Vice President and CTO of IBM’s Federal Division; Jim Hietala, Vice President for Security at The Open Group, and Chris Gerty, Deputy Program Manager at the Open Innovation Program at NASA. I served as the moderator.

And this special thought leadership interview series comes to you in conjunction with The Open Group Conference recently held in Newport Beach, California. The conference focused on “Big Data — he transformation we need to embrace today.”

Threaded factors

An interesting thread for me throughout the conference was to factor where Big Data begins and plain old data, if you will, ends. Of course, it’s going to vary quite a bit from organization to organization.

But Gerty from NASA, part of our panel, provided a good example: It’s when you run out of gas with your old data methods, and your ability to deal with the data — and it’s not just the size of the data itself.

Therefore, Big Data means do things differently — not just to manage the velocity and the volume and the variety of the data, but to really think about data fundamentally and differently. And, we need to think about security, risk and governance. If it’s a “boundaryless organization” when it comes your data, either as a product or service or a resource, that control and management of which data should be exposed, which should be opened, and which should be very closely guarded all need to be factored, determined and implemented.

Here are some excerpts from the on-stage discussion:

Dana Gardner: You mentioned that Big Data to you is not a factor of the size, because NASA’s dealing with so much. It’s when you run out of steam, as it were, with the methodologies. Maybe you could explain more. When do you know that you’ve actually run out of steam with the methodologies?

Gerty: When we collect data, we have some sort of goal in minds of what we might get out of it. When we put the pieces from the data together, it either maybe doesn’t fit as well as you thought or you are successful and you continue to do the same thing, gathering archives of information.

Gardner: Andras, does that square with where you are in your government interactions — that data now becomes a different type of resource, and that you need to know when to do things differently?At that point, where you realize there might even something else that you want to do with the data, different than what you planned originally, that’s when we have to pivot a little bit and say, “Now I need to treat this as a living archive. It’s a ‘it may live beyond me’ type of thing.” At that point, I think you treat it as setting up the infrastructure for being used later, whether it’d be by you or someone else. That’s an important transition to make and might be what one could define as Big Data.

Szakal: The importance of data hasn’t changed. The data itself, the veracity of the data, is still important. Transactional data will always need to exist. The difference is that you have certainly the three or four Vs, depending on how you look at it, but the importance of data is in its veracity, and your ability to understand or to be able to use that data before the data’s shelf life runs out.

Gardner: Bob, we’ve seen the price points on storage go down so dramatically. We’ve seem people just decide to hold on to data that they wouldn’t have before, simply because they can and they can afford to do so. That means we need to try to extract value and use that data. From the perspective of an enterprise architect, how are things different now, vis-à-vis this much larger set of data and variety of data, when it comes to planning and executing as architects?Some data has a shelf life that’s long lived. Other data has very little shelf life, and you would use different approaches to being able to utilize that information. It’s ultimately not about the data itself, but it’s about gaining deep insight into that data. So it’s not storing data or manipulating data, but applying those analytical capabilities to data.

Weisman: One of the major issues is that normally organizations are holding two orders of magnitude more data then they need. It’s an huge overhead, both in terms of the applications architecture that has a code basis, larger than it should be, and also from the technology architecture that is supporting a horrendous number of servers and a whole bunch of technology stuff that they don’t need.

The issue for the architect is to figure out as what data is useful, institute a governance process, so that you can have data lifecycle management, have a proper disposition,  focus the organization on information data and knowledge that is basically going to provide business value to the organization, and help them innovate and have a competitive advantage.

Can’t afford it

And in terms of government, just improve service delivery, because there’s waste right now on information infrastructure, and we can’t afford it anymore.

Gardner: So it’s difficult to know what to keep and what not to keep. I’ve actually spoken to a few people lately who want to keep everything, just because they want to mine it, and they are willing to spend the money and effort to do that.

Jim Hietala, when people do get to this point of trying to decide what to keep, what not to keep, and how to architect properly for that, they also need to factor in security. It shouldn’t become later in the process. It should come early. What are some of the precepts that you think are important in applying good security practices to Big Data?

Hietala: One of the big challenges is that many of the big-data platforms weren’t built from the get-go with security in mind. So some of the controls that you’ve had available in your relational databases, for instance, you move over to the Big Data platforms and the access control authorizations and mechanisms are not there today.

Gardner: There are a lot of unknown unknowns out there, as we discovered with our tweet chat last month. Some people think that the data is just data, and you apply the same security to it. Do you think that’s the case with Big Data? Is it just another follow-through of what you always did with data in the first place?Planning the architecture, looking at bringing in third-party controls to give you the security mechanisms that you are used to in your older platforms, is something that organizations are going to have to do. It’s really an evolving and emerging thing at this point.

Hietala: I would say yes, at a conceptual level, but it’s like what we saw with virtualization. When there was a mad rush to virtualize everything, many of those traditional security controls didn’t translate directly into the virtualized world. The same thing is true with Big Data.

When you’re talking about those volumes of data, applying encryption, applying various security controls, you have to think about how those things are going to scale? That may require new solutions from new technologies and that sort of thing.

Gardner: Chris Gerty, when it comes to that governance, security, and access control, are there any lessons that you’ve learned that you are aware of in terms of the best of openness, but also with the ability to manage the spigot?

Gerty: Spigot is probably a dangerous term to use, because it implies that all data is treated the same. The sooner that you can tag the data as either sensitive or not, mostly coming from the person or team that’s developed or originated the data, the better.

Kicking the can

Once you have it on a hard drive, once you get crazy about storing everything, if you don’t know where it came from, you’re forced to put it into a secure environment. And that’s just kicking the can down the road. It’s really a disservice to people who might use the data in a useful way to address their problems.

We constantly have satellites that are made for one purpose. They send all the data down. It’s controlled either for security or for intellectual property (IP), so someone can write a paper. Then, after the project doesn’t get funded or it just comes to a nice graceful close, there is that extra step, which is almost a responsibility of the originators, to make it useful to the rest of the world.

Gardner: Let’s look at Big Data through the lens of some other major trends right now. Let’s start with Cloud. You mentioned that at NASA, you have your own private Cloud that you’re using a lot, of course, but you’re also now dabbling in commercial and public Clouds. Frankly, the price points that these Cloud providers are offering for storage and data services are pretty compelling.

So we should expect more data to go to the Cloud. Bob, from your perspective, as organizations and architects have to think about data in this hybrid Cloud on-premises off-premises, moving back and forth, what do you think enterprise architects need to start thinking about in terms of managing that, planning for the right destination of data, based on the right mix of other requirements?

Weisman: It’s a good question. As you said, the price point is compelling, but the security and privacy of the information is something else that has to be taken into account. Where is that information going to reside? You have to have very stringent service-level agreements (SLAs) and in certain cases, you might say it’s a price point that’s compelling, but the risk analysis that I have done means that I’m going to have to set up my own private Cloud.

Gardner: Andras, how do the Cloud and Big Data come together in a way that’s intriguing to you?Right now, everybody’s saying is the public Cloud is going to be the way to go. Vendors are going to have to be very sensitive to that and many are, at this point in time, addressing a lot of the needs of some of the large client basis. So it’s not one-size-fits-all and it’s more than just a price for service. Architecture can bring down the price pretty dramatically, even within an enterprise.

Szakal: Actually it’s a great question. We could take the rest of the 22 minutes talking on this one question. I helped lead the President’s Commission on Big Data that Steve Mills from IBM and — I forget the name of the executive from SAP — led. We intentionally tried to separate Cloud from Big Data architecture, primarily because we don’t believe that, in all cases, Cloud is the answer to all things Big Data. You have to define the architecture that’s appropriate for your business needs.

However, it also depends on where the data is born. Take many of the investments IBM has made into enterprise market management, for example, Coremetrics, several of these services that we now offer for helping customers understand deep insight into how their retail market or supply chain behaves.

Born in the Cloud

All of that information is born in the Cloud. But if you’re talking about actually using Cloud as infrastructure and moving around huge sums of data or constructing some of these solutions on your own, then some of the ideas that Bob conveyed are absolutely applicable.

I think it becomes prohibitive to do that and easier to stand up a hybrid environment for managing the amount of data. But I think that you have to think about whether your data is real-time data, whether it’s data that you could apply some of these new technologies like Hadoop to, Hadoop MapReduce-type solutions, or whether it’s traditional data warehousing.

Data warehouses are going to continue to exist and they’re going to continue to evolve technologically. You’re always going to use a subset of data in those data warehouses, and it’s going to be an applicable technology for many years to come.

Gardner: So suffice it to say, an enterprise architect who is well versed in both Cloud infrastructure requirements, technologies, and methods, as well as Big Data, will probably be in quite high demand. That specialization in one or the other isn’t as valuable as being able to cross-pollinate between them.

Szakal: Absolutely. It’s enabling our architects and finding deep individuals who have this unique set of skills, analytics, mathematics, and business. Those individuals are going to be the future architects of the IT world, because analytics and Big Data are going to be integrated into everything that we do and become part of the business processing.

Gardner: Well, that’s a great segue to the next topic that I am interested in, and it’s around mobility as a trend and also application development. The reason I lump them together is that I increasingly see developers being tasked with mobile first.

When you create a new app, you have to remember that this is going to run in the mobile tier and you want to make sure that the requirements, the UI, and the complexity of that app don’t go beyond the ability of the mobile app and the mobile user. This is interesting to me, because data now has a different relationship with apps.

We used to think of apps as creating data and then the data would be stored and it might be used or integrated. Now, we have applications that are simply there in order to present the data and we have the ability now to present it to those mobile devices in the mobile tier, which means it goes anywhere, everywhere all the time.

Let me start with you Jim, because it’s security and risk, but it’s also just rethinking the way we use data in a mobile tier. If we can do it safely, and that’s a big IF, how important should it be for organizations to start thinking about making this data available to all of these devices and just pour out into that mobile tier as possible?

Hietala: In terms of enabling the business, it’s very important. There are a lot of benefits that accrue from accessing your data from whatever device you happen to be on. To me, it is that question of “if,” because now there’s a whole lot of problems to be solved relative to the data floating around anywhere on Android, iOS, whatever the platform is, and the organization being able to lock down their data on those devices, forgetting about whether it’s the organization device or my device. There’s a set of issues around that that the security industry is just starting to get their arms around today.

Mobile ability

Gardner: Chris, any thoughts about this mobile ability that the data gets more valuable the more you can use it and apply it, and then the more you can apply it, the more data you generate that makes the data more valuable, and we start getting into that positive feedback loop?

Gerty: Absolutely. It’s almost an appreciation of what more people could do and get to the problem. We’re getting to the point where, if it’s available on your desktop, you’re going to find a way to make it available on your device.

That same security questions probably need to be answered anyway, but making it mobile compatible is almost an acknowledgment that there will be someone who wants to use it. So let me go that extra step to make it compatible and see what I get from them. It’s more of a cultural benefit that you get from making things compatible with mobile.

Gardner: Any thoughts about what developers should be thinking by trying to bring the fruits of Big Data through these analytics to more users rather than just the BI folks or those that are good at SQL queries? Does this change the game by actually making an application on a mobile device, simple, powerful but accessing this real time updated treasure trove of data?

Gerty: I always think of the astronaut on the moon. He’s got a big, bulky glove and he might have a heads-up display in front of him, but he really needs to know exactly a certain piece of information at the right moment, dealing with bandwidth issues, dealing with the environment, foggy helmet wherever.

It’s very analogous to what the day-to-day professional will use trying to find out that quick e-mail he needs to know or which meeting to go to — which one is more important — and it all comes down to putting your developer in the shoes of the user. So anytime you can get interaction between the two, that’s valuable.

Weisman: From an Enterprise Architecture point of view my background is mainly defense and government, but defense mobile computing has been around for decades. So you’ve always been dealing with that.

The main thing is that in many cases, if they’re coming up with information, the whole presentation layer is turning into another architecture domain with information visualization and also with your security controls, with an integrated identity management capability.

It’s like you were saying about astronaut getting it right. He doesn’t need to know everything that’s happening in the world. He needs to know about his heads-up display, the stuff that’s relevant to him.

So it’s getting the right information to person in an authorized manner, in a way that he can visualize and make sense of that information, be it straight data, analytics, or whatever. The presentation layer, ergonomics, visual communication are going to become very important in the future for that. There are also a lot of problems. Rather than doing it at the application level, you’re doing it entirely in one layer.

Governance and security

Gardner: So clearly the implications of data are cutting across how we think about security, how we think about UI, how we factor in mobility. What we now think about in terms of governance and security, we have to do differently than we did with older data models.

Jim Hietala, what about the impact on spurring people towards more virtualized desktop delivery, if you don’t want to have the date on that end device, if you want solve some of the issues about control and governance, and if you want to be able to manage just how much data gets into that UI, not too much not too little.

Do you think that some of these concerns that we’re addressing will push people to look even harder, maybe more aggressive in how they go to desktop and application virtualization, as they say, keep it on the server, deliver out just the deltas?

Hietala: That’s an interesting point. I’ve run across a startup in the last month or two that is doing is that. The whole value proposition is to virtualize the environment. You get virtual gold images. You don’t have to worry about what’s actually happening on the physical device and you know when the devices connect. The security threat goes away. So we may see more of that as a solution to that.

Gardner: Andras, do you see that that some of the implications of Big Data, far fetched as it may be, are propelling people to cultivate their servers more and virtualize their apps, their data, and their desktop right up to the end devices?

Szakal: Yeah, I do. I see IBM providing solutions for virtual desktop, but I think it was really a security question you were asking. You’re certainly going to see an additional number of virtualized desktop environments.

Ultimately, our network still is not stable enough or at a high enough bandwidth to really make that useful exercise for all but the most menial users in the enterprise. From a security point of view, there is a lot to be still solved.

And part of the challenge in the Cloud environment that we see today is the proliferation of virtual machines (VMs) and the inability to actually contain the security controls within those machines and across these machines from an enterprise perspective. So we’re going to see more solutions proliferate in this area and to try to solve some of the management issues, as well as the security issues, but we’re a long ways away from that.

Gerty: Big Data, by itself, isn’t magical. It doesn’t have the answers just by being big. If you need more, you need to pry deeper into it. That’s the example. They realized early enough that they were able to make something good.

Gardner: Jim Hietala, any thoughts about examples that illustrate where we’re going and why this is so important?

Hietala: Being a security guy, I tend to talk about scare stories, horror stories. One example from last year that struck me. One of the major retailers here in the U.S. hit the news for having predicted, through customer purchase behavior, when people were pregnant.

They could look and see, based upon buying 20 things, that if you’re buying 15 of these and your purchase behavior has changed, they can tell that. The privacy implications to that are somewhat concerning.

An example was that this retailer was sending out coupons related to somebody being pregnant. The teenage girl, who was pregnant hadn’t told her family yet. The father found it. There was alarm in the household and at the local retailer store, when the father went and confronted them.

Privacy implications

There are privacy implications from the use of Big Data. When you get powerful new technology in marketing people’s hands, things sometimes go awry. So I’d throw that out just as a cautionary tale that there is that aspect to this. When you can see across people’s buying transactions, things like that, there are privacy considerations that we’ll have to think about, and that we really need to think about as an industry and a society.

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Open Group Panel Explores Changing Field of Risk Management and Analysis in the Era of Big Data

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here: The Open Group Panel Explores Changing Field of Risk Management and Analysis in Era of Big Data

This is a transcript of a sponsored podcast discussion on the threats from and promise of Big Data in securing enterprise information assets in conjunction with the The Open Group Conference in Newport Beach.

Dana Gardner: Hello, and welcome to a special thought leadership interview series coming to you in conjunction with The Open Group Conference on January 28 in Newport Beach, California.

I’m Dana Gardner, Principal Analyst at Interarbor Solutions, and I’ll be your host and moderator throughout these business transformation discussions. The conference itself is focusing on Big Data the transformation we need to embrace today.

We’re here now with a panel of experts to explore new trends and solutions in the area of risk management and analysis. We’ll learn how large enterprises are delivering risk assessments and risk analysis, and we’ll see how Big Data can be both an area to protect from in form of risks, but also as a tool for better understanding and mitigating risks.

With that, please join me in welcoming our panel. We’re here with Jack Freund, PhD, the Information Security Risk Assessment Manager at TIAA-CREF. Welcome, Jack.

Jack Freund: Hello Dana, how are you?

Gardner: I’m great. Glad you could join us.

We are also here with Jack Jones, Principal of CXOWARE. He has more than nine years of experience as a Chief Information Security Officer, is the inventor of the Factor Analysis Information Risk (FAIR) framework. Welcome, Jack.

Jack Jones: Thank you. And we’re also here with Jim Hietala, Vice President, Security for The Open Group. Welcome, Jim.

Jim Hietala: Thanks, Dana.

Gardner: All right, let’s start out with looking at this from a position of trends. Why is the issue of risk analysis so prominent now? What’s different from, say, five years ago? And we’ll start with you, Jack Jones.

Jones: The information security industry has struggled with getting the attention of and support from management and businesses for a long time, and it has finally come around to the fact that the executives care about loss exposure — the likelihood of bad things happening and how bad those things are likely to be.

It’s only when we speak of those terms or those issues in terms of risk, that we make sense to those executives. And once we do that, we begin to gain some credibility and traction in terms of getting things done.

Gardner: So we really need to talk about this in the terms that a business executive would appreciate, not necessarily an IT executive.

Effects on business

Jones: Absolutely. They’re tired of hearing about vulnerabilities, hackers, and that sort of thing. It’s only when we can talk in terms of the effect on the business that it makes sense to them.

Gardner: Jack Freund, I should also point out that you have more than 14 years in enterprise IT experience. You’re a visiting professor at DeVry University and you chair a risk-management subcommittee for ISACA? Is that correct?

Freund: ISACA, yes.

Gardner: And do you agree?

Freund: The problem that we have as a profession, and I think it’s a big problem, is that we have allowed ourselves to escape the natural trend that the other IT professionals have already taken.

There was a time, years ago, when you could code in the basement, and nobody cared much about what you were doing. But now, largely speaking, developers and systems administrators are very focused on meeting the goals of the organization.

Security has been allowed to miss that boat a little. We have been allowed to hide behind this aura of a protector and of an alerter of terrible things that could happen, without really tying ourselves to the problem that the organizations are facing and how can we help them succeed in what they’re doing.

Gardner: Jim Hietala, how do you see things that are different now than a few years ago when it comes to risk assessment?

Hietala: There are certainly changes on the threat side of the landscape. Five years ago, you didn’t really have hacktivism or this notion of an advanced persistent threat (APT).

That highly skilled attacker taking aim at governments and large organizations didn’t really exist -– or didn’t exist to the degree it does today. So that has changed.

You also have big changes to the IT platform landscape, all of which bring new risks that organizations need to really think about. The mobility trend, the Cloud trend, the big-data trend that we are talking about today, all of those things bring new risk to the organization.

As Jack Jones mentioned, business executives don’t want to hear about, “I’ve got 15 vulnerabilities in the mobility part of my organization.” They want to understand what’s the risk of bad things happening because of mobility, what we’re doing about it, and what’s happening to risk over time?

So it’s a combination of changes in the threats and attackers, as well as just changes to the IT landscape, that we have to take a different look at how we measure and present risk to the business.

Gardner: Because we’re at a big-data conference, do you share my perception, Jack Jones, that Big Data can be a source of risk and vulnerability, but also the analytics and the business intelligence (BI) tools that we’re employing with Big Data can be used to alert you to risks or provide a strong tool for better understanding your true risk setting or environment.

Crown jewels

Jones: You are absolutely right. You think of Big Data and, by definition, it’s where your crown jewels, and everything that leads to crown jewels from an information perspective, are going to be found. It’s like one-stop shopping for the bad guy, if you want to look at it in that context. It definitely needs to be protected. The architecture surrounding it and its integration across a lot of different platforms and such, can be leveraged and probably result in a complex landscape to try and secure.

There are a lot of ways into that data and such, but at least if you can leverage that same Big Data architecture, it’s an approach to information security. With log data and other threat and vulnerability data and such, you should be able to make some significant gains in terms of how well-informed your analyses and your decisions are, based on that data.

Gardner: Jack Freund, do you share that? How does Big Data fit into your understanding of the evolving arena of risk assessment and analysis?

Freund: If we fast-forward it five years, and this is even true today, a lot of people on the cutting edge of Big Data will tell you the problem isn’t so much building everything together and figuring out what it can do. They are going to tell you that the problem is what we do once we figure out everything that we have. This is the problem that we have traditionally had on a much smaller scale in information security. When everything is important, nothing is important.

Gardner: To follow up on that, where do you see the gaps in risk analysis in large organizations? In other words, what parts of organizations aren’t being assessed for risk and should be?

Freund: The big problems that exist largely today in the way that risk assessments are done, is the focus on labels. We want to quickly address the low, medium, and high things and know where they are. But the problem is that there are inherent problems in the way that we think about those labels, without doing any of the analysis legwork.

I think that’s what’s really missing is that true analysis. If the system goes offline, do we lose money? If the system becomes compromised, what are the cost-accounting things that will happen that allow us to figure out how much money we’re going to lose.

That analysis work is largely missing. That’s the gap. The gap is if the control is not in place, then there’s a risk that must be addressed in some fashion. So we end up with these very long lists of horrible, terrible things that can be done to us in all sorts of different ways, without any relevance to the overall business of the organization.

Every day, our organizations are out there selling products, offering services, which is and of itself, its own risky venture. So tying what we do from an information security perspective to that is critical for not just the success of the organization, but the success of our profession.

Gardner: So we can safely say that large companies are probably pretty good at a cost-benefit analysis or they wouldn’t be successful. Now, I guess we need to ask them to take that a step further and do a cost-risk analysis, but in business terms, being mindful that their IT systems might be a much larger part of that than they had at once considered. Is that fair, Jack?

Risk implications

Jones: Businesses have been making these decisions, chasing the opportunity, but generally, without any clear understanding of the risk implications, at least from the information security perspective. They will have us in the corner screaming and throwing red flags in there, and talking about vulnerabilities and threats from one thing or another.

But, we come to the table with red, yellow, and green indicators, and on the other side of the table, they’ve got numbers. Well, here is what we expect to earn in revenue from this initiative, and the information security people are saying it’s crazy. How do you normalize the quantitative revenue gain versus red, yellow, and green?

Gardner: Jim Hietala, do you see it in the same red, yellow, green or are there some other frameworks or standard methodologies that The Open Group is looking at to make this a bit more of a science?

Hietala: Probably four years ago, we published what we call the Risk Taxonomy Standard which is based upon FAIR, the management framework that Jack Jones invented. So, we’re big believers in bringing that level of precision to doing risk analysis. Having just gone through training for FAIR myself, as part of the standards effort that we’re doing around certification, I can say that it really brings a level of precision and a depth of analysis to risk analysis that’s been lacking frequently in IT security and risk management.

Gardner: We’ve talked about how organizations need to be mindful that their risks are higher and different than in the past and we’ve talked about how standardization and methodologies are important, helping them better understand this from a business perspective, instead of just a technology perspective.

But, I’m curious about a cultural and organizational perspective. Whose job should this fall under? Who is wearing the white hat in the company and can rally the forces of good and make all the bad things managed? Is this a single person, a cultural, an organizational mission? How do you make this work in the enterprise in a real-world way? Let’s go to you, Jack Freund.

Freund: The profession of IT risk management is changing. That profession will have to sit between the business and information security inclusive of all the other IT functions that make that happen.

In order to be successful sitting between these two groups, you have to be able to speak the language of both of those groups. You have to be able to understand profit and loss and capital expenditure on the business side. On the IT risk side, you have to be technical enough to do all those sorts of things.

But I think the sum total of those two things is probably only about 50 percent of the job of IT risk management today. The other 50 percent is communication. Finding ways to translate that language and to understand the needs and concerns of each side of that relationship is really the job of IT risk management.

To answer your question, I think it’s absolutely the job of IT risk management to do that. From my own experiences with the FAIR framework, I can say that using FAIR is the Rosetta Stone for speaking between those two groups.

Necessary tools

It gives you the tools necessary to speak in the insurance and risk terms that business appreciate. And it gives you the ability to be as technical and just nerdy, if you will, as you need to be in order to talk to IT security and the other IT functions in order to make sure everybody is on the same page and everyone feels like their concerns are represented in the risk-assessment functions that are happening.

Gardner: Jack Jones, can you add to that?

Jones: I agree with what Jack said wholeheartedly. I would add, though, that integration or adoption of something like this is a lot easier the higher up in the organization you go.

For CFOs traditionally, their neck is most clearly on the line for risk-related issues within most organizations. At least in my experience, if you get their ear on this and present the information security data analyses to them, they jump on board, they drive it through the organization, and it’s just brain-dead easy.

If you try to drive it up through the ranks, maybe you get an enthusiastic supporter in the information security organization, especially if it’s below the CISO level, and they try a grassroots sort of effort to bring it in, it’s a tougher thing. It can still work. I’ve seen it work very well, but, it’s a longer row to hoe.

Gardner: There have been a lot of research, studies, and surveys on data breaches. What are some of the best sources, or maybe not so good sources, for actually measuring this? How do you know if you’re doing it right? How do you know if you’re moving from yellow to green, instead of to red? To you, Jack Freund.

Freund: There are a couple of things in that question. The first is there’s this inherent assumption in a lot of organizations that we need to move from yellow to green, and that may not be the case. So, becoming very knowledgeable about the risk posture and the risk tolerance of the organization is a key.

That’s part of the official mindset of IT security. When you graduate an information security person today, they are minted knowing that there are a lot of bad things out there, and their goal in life is to reduce them. But, that may not be the case. The case may very well be that things are okay now, but we have bigger things to fry over here that we’re going to focus on. So, that’s one thing.

The second thing, and it’s a very good question, is how we know that we’re getting better? How do we trend that over time? Overall, measuring that value for the organization has to be able to show a reduction of a risk or at least reduction of risk to the risk-tolerance levels of the organization.

Calculating and understanding that requires something that I always phrase as we have to become comfortable with uncertainty. When you are talking about risk in general, you’re talking about forward-looking statements about things that may or may not happen. So, becoming comfortable with the fact that they may or may not happen means that when you measure them today, you have to be willing to be a little bit squishy in how you’re representing that.

In FAIR and in other academic works, they talk about using ranges to do that. So, things like high, medium, and low, could be represented in terms of a minimum, maximum, and most likely. And that tends to be very, very effective. People can respond to that fairly well.

Gathering data

Jones: With regard to the data sources, there are a lot of people out there doing these sorts of studies, gathering data. The problem that’s hamstringing that effort is the lack of a common set of definitions, nomenclature, and even taxonomy around the problem itself.

You will have one study that will have defined threat, vulnerability, or whatever differently from some other study, and so the data can’t be normalized. It really harms the utility of it. I see data out there and I think, “That looks like that can be really useful.” But, I hesitate to use it because I don’t understand. They don’t publish their definitions, approach, and how they went after it.

There’s just so much superficial thinking in the profession on this that we now have dug under the covers. Too often, I run into stuff that just can’t be defended. It doesn’t make sense, and therefore the data can’t be used. It’s an unfortunate situation.

I do think we’re heading in a positive direction. FAIR can provide a normalizing structure for that sort of thing. The VERIS framework, which by the way, is also derived in part from FAIR, also has gained real attraction in terms of the quality of the research they have done and the data they’re generating. We’re headed in the right direction, but we’ve got a long way to go.

Gardner: Jim Hietala, we’re seemingly looking at this on a company-by-company basis. But, is there a vertical industry slice or industry-wide slice where we could look at what’s happening to everyone and put some standard understanding, or measurement around what’s going on in the overall market, maybe by region, maybe by country?

Hietala: There are some industry-specific initiatives and what’s really needed, as Jack Jones mentioned, are common definitions for things like breach, exposure, loss, all those, so that the data sources from one organization can be used in another, and so forth. I think about the financial services industry. I know that there is some information sharing through an organization called the FS-ISAC about what’s happening to financial services organizations in terms of attacks, loss, and those sorts of things.

There’s an opportunity for that on a vertical-by-vertical basis. But, like Jack said, there is a long way to go on that. In some industries, healthcare for instance, you are so far from that, it’s ridiculous. In the US here, the HIPAA security rule says you must do a risk assessment. So, hospitals have done annual risk assessments, will stick the binder on the shelf, and they don’t think much about information security in between those annual risk assessments. That’s a generalization, but various industries are at different places on a continuum of maturity of their risk management approaches.

Gardner: As we get better with having a common understanding of the terms and the measurements and we share more data, let’s go back to this notion of how to communicate this effectively to those people that can use it and exercise change management as a result. That could be the CFO, the CEO, what have you, depending on the organization.

Do you have any examples? Can we look to an organization that’s done this right, and examine their practices, the way they’ve communicated it, some of the tools they’ve used and say, “Aha, they’re headed in the right direction maybe we could follow a little bit.” Let’s start with you, Jack Freund.

Freund: I have worked and consulted for various organizations that have done risk management at different levels. The ones that have embraced FAIR tend to be the ones that overall feel that risk is an integral part of their business strategy. And I can give a couple of examples of scenarios that have played out that I think have been successful in the way they have been communicated.

Coming to terms

The key to keep in mind with this is that one of the really important things is that when you’re a security professional, you’re again trained to feel like you need results. But, the results for the IT risk management professional are different. The results are “I’ve communicated this effectively, so I am done.” And then whatever the results are, are the results that needed to be. And that’s a really hard thing to come to terms with.

I’ve been involved in large-scale efforts to assess risk for a Cloud venture. We needed to move virtually every confidential record that we have to the Cloud in order to be competitive with the rest of our industry. If our competitors are finding ways to utilize the Cloud before us, we can lose out. So, we need to find a way to do that, and to be secure and compliant with all the laws and regulations and such.

Through that scenario, one of the things that came out was that key ownership became really, really important. We had the opportunity to look at the various control structures and we analyzed them using FAIR. What we ended up with was sort of a long-tail risk. Most people will probably do their job right over a long enough period of time. But, over that same long period of time, the odds of somebody making a mistake not in your favor are probably likely, but, not significantly enough so that you can’t make the move.

But, the problem became that the loss side, the side that typically gets ignored with traditional risk-assessment methodologies, was so significant that the organization needed to make some judgment around that, and they needed to have a sense of what we needed to do in order to minimize that.

That became a big point of discussion for us and it drove the conversation away from bad things could happen. We didn’t bury the lead. The lead was that this is the most important thing to this organization in this particular scenario.

So, let’s talk about things we can do. Are we comfortable with it? Do we need to make any sort of changes? What are some control opportunities? How much do they cost? This is a significantly more productive conversation than just, “Here is a bunch of bad things that happen. I’m going to cross my arms and say no.”

Gardner: Jack Jones, examples at work?

Jones: In an organization that I’ve been working with recently, their board of directors said they wanted a quantitative view of information security risk. They just weren’t happy with the red, yellow, green. So, they came to us, and there were really two things that drove them there. One was that they were looking at cyber insurance. They wanted to know how much cyber insurance they should take out, and how do you figure that out when you’ve got a red, yellow, green scale?

They were able to do a series of analyses on a population of the scenarios that they thought were relevant in their world, get an aggregate view of their annualized loss exposure, and make a better informed decision about that particular problem.

Gardner: I’m curious how prevalent cyber insurance is, and is that going to be a leveling effect in the industry where people speak a common language the equivalent of actuarial tables, but for security in enterprise and cyber security?

Jones: One would dream and hope, but at this point, what I’ve seen out there in terms of the basis on which insurance companies are setting their premiums and such is essentially the same old “risk assessment” stuff that the industry has been doing poorly for years. It’s not based on data or any real analysis per se, at least what I’ve run into. What they do is set their premiums high to buffer themselves and typically cover as few things as possible. The question of how much value it’s providing the customers becomes a problem.

Looking to the future

Gardner: We’re coming up on our time limit. So, let’s quickly look to the future. Is there such thing as risk management as a service? Can we outsource this? Is there a way in which moving more of IT into Cloud or hybrid models would mitigate risk, because the Cloud provider would standardize? Then, many players in that environment, those who were buying those services, would be under that same umbrella? Let’s start with you Jim Hietala. What’s the future of this and what do the Cloud trends bring to the table?

Hietala: I’d start with a maxim that comes out of the financial services industry, which is that you can outsource the function, but you still own the risk. That’s an unfortunate reality. You can throw things out in the Cloud, but it doesn’t absolve you from understanding your risk and then doing things to manage it to transfer it if there’s insurance or whatever the case may be.

That’s just a reality. Organizations in the risky world we live in are going to have to get more serious about doing effective risk analysis. From The Open Group standpoint, we see this as an opportunity area.

As I mentioned, we’ve standardized the taxonomy piece of FAIR. And we really see an opportunity around the profession going forward to help the risk-analysis community by further standardizing FAIR and launching a certification program for a FAIR-certified risk analyst. That’s in demand from large organizations that are looking for evidence that people understand how to apply FAIR and use it in doing risk analyses.

Gardner: Jack Freund, looking into your crystal ball, how do you see this discipline evolving?

Freund: I always try to consider things as they exist within other systems. Risk is a system of systems. There are a series of pressures that are applied, and a series of levers that are thrown in order to release that sort of pressure.

Risk will always be owned by the organization that is offering that service. If we decide at some point that we can move to the Cloud and all these other things, we need to look to the legal system. There is a series of pressures that they are going to apply, and who is going to own that, and how that plays itself out.

If we look to the Europeans and the way that they’re managing risk and compliance, they’re still as strict as we in United States think that they may be about things, but there’s still a lot of leeway in a lot of the ways that laws are written. You’re still being asked to do things that are reasonable. You’re still being asked to do things that are standard for your industry. But, we’d still like the ability to know what that is, and I don’t think that’s going to go away anytime soon.

Judgment calls

We’re still going to have to make judgment calls. We’re still going to have to do 100 things with a budget for 10 things. Whenever that happens, you have to make a judgment call. What’s the most important thing that I care about? And that’s why risk management exists, because there’s a certain series of things that we have to deal with. We don’t have the resources to do them all, and I don’t think that’s going to change over time. Regardless of whether the landscape changes, that’s the one that remains true.

Gardner: The last word to you, Jack Jones. It sounds as if we’re continuing down the path of being mostly reactive. Is there anything you can see on the horizon that would perhaps tip the scales, so that the risk management and analysis practitioners can really become proactive and head things off before they become a big problem?

Jones: If we were to take a snapshot at any given point in time of an organization’s loss exposure, how much risk they have right then, that’s a lagging indicator of the decisions they’ve made in the past, and their ability to execute against those decisions.

We can do some great root-cause analysis around that and ask how we got there. But, we can also turn that coin around and ask how good we are at making well-informed decisions, and then executing against them, the asking what that implies from a risk perspective downstream.

If we understand the relationship between our current state, and past and future states, we have those linkages defined, especially, if we have an analytic framework underneath it. We can do some marvelous what-if analysis.

What if this variable changed in our landscape? Let’s run a few thousand Monte Carlo simulations against that and see what comes up. What does that look like? Well, then let’s change this other variable and then see which combination of dials, when we turn them, make us most robust to change in our landscape.

But again, we can’t begin to get there, until we have this foundational set of definitions, frameworks, and such to do that sort of analysis. That’s what we’re doing with FAIR, but without some sort of framework like that, there’s no way you can get there.

Gardner: I am afraid we’ll have to leave it there. We’ve been talking with a panel of experts on how new trends and solutions are emerging in the area of risk management and analysis. And we’ve seen how new tools for communication and using Big Data to understand risks are also being brought to the table.

This special BriefingsDirect discussion comes to you in conjunction with The Open Group Conference in Newport Beach, California. I’d like to thank our panel: Jack Freund, PhD, Information Security Risk Assessment Manager at TIAA-CREF. Thanks so much Jack.

Freund: Thank you, Dana.

Gardner: We’ve also been speaking with Jack Jones, Principal at CXOWARE.

Jones: Thank you. Thank you, pleasure to be here.

Gardner: And last, Jim Hietala, the Vice President for Security at The Open Group. Thanks.

Hietala: Thanks, Dana.

Gardner: This is Dana Gardner, Principal Analyst at Interarbor Solutions; your host and moderator through these thought leadership interviews. Thanks again for listening and come back next time.

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On Demand Broadcasts from Day One at The Open Group Conference in Newport Beach

By The Open Group Conference Team

Since not everyone could make the trip to The Open Group Conference in Newport Beach, we’ve put together a recap of day one’s plenary speakers. Stay tuned for more recaps coming soon!

Big Data at NASA

In his talk titled, “Big Data at NASA,” Chris Gerty, deputy program manager, Open Innovation Program, National Aeronautics and Space Administration (NASA), discussed how Big Data is being interpreted by the next generation of rocket scientists. Chris presented a few lessons learned from his experiences at NASA:

  1. A traditional approach is not always the best approach. A tried and proven method may not translate. Creating more programs for more data to store on bigger hard drives is not always effective. We need to address the never-ending challenges that lie ahead in the shift of society to the information age.
  2. A plan for openness. Based on a government directive, Chris’ team looked to answer questions by asking the right people. For example, NASA asked the people gathering data on a satellite to determine what data was the most important, which enabled NASA to narrow focus and solve problems. Furthermore, by realizing what can also be useful to the public and what tools have already been developed by the public, open source development can benefit the masses. Through collaboration, governments and citizens can work together to solve some of humanity’s biggest problems.
  3. Embrace the enormity of the universe. Look for Big Data where no one else is looking by putting sensors and information gathering tools. If people continue to be scared of Big Data, we will be resistant to gathering more of it. By finding Big Data where it has yet to be discovered, we can solve problems and innovate.

To view Chris’s presentation, please watch the broadcasted session here: http://new.livestream.com/opengroup/Gerty-NPB13

Bringing Order to the Chaos

David Potter, chief technical officer at Promise Innovation and Ron Schuldt, senior partner at UDEF-IT, LLC discussed how The Open Group’s evolving Quantum Lifecycle Management (QLM) standard coupled with its complementary Universal Data Element Framework (UDEF) standard help bring order to the terminology chaos that faces Big Data implementations.

The QLM standard provides a framework for the aggregation of lifecycle data from a multiplicity of sources to add value to the decision making process. Gathering mass amounts of data is useless if it cannot be analyzed. The QLM framework provides a means to interpret the information gathered for business intelligence. The UDEF allows each piece of data to be paired with an unambiguous key to provide clarity. By partnering with the UDEF, the QLM framework is able to separate itself from domain-specific semantic models. The UDEF also provides a ready-made key for international language support. As an open standard, the UDEF is data model independent and as such supports normalization across data models.

One example of successful implementation is by Compassion International. The organization needed to find a balance between information that should be kept internal (e.g., payment information) and information that should be shared with its international sponsors. In this instance, UDEF was used as a structured process for harmonizing the terms used in IT systems between funding partners.

The beauty of the QLM framework and UDEF integration is that they are flexible and can be applied to any product, domain and industry.

To view David and Ron’s presentation, please watch the broadcasted session here: http://new.livestream.com/opengroup/potter-NPB13

Big Data – Panel Discussion

Moderated by Dana Gardner, Interarbor Solution, Robert Weisman , Build The Vision, Andras Szakal, IBM, Jim Hietala, The Open Group, and Chris Gerty, NASA, discussed the implications of Big Data and what it means for business architects and enterprise architects.

Big Data is not about the size but about analyzing that data. Robert mentioned that most organizations store more data than they need or use, and from an enterprise architect’s perspective, it’s important to focus on the analysis of the data and to provide information that will ultimately aid it in some way. When it comes to security, Jim explained that newer Big Data platforms are not built with security in mind. While data is data, many security controls don’t translate to new platforms or scale with the influx of data.

Cloud Computing is Big Data-ready, and price can be compelling, but there are significant security and privacy risks. Robert brought up the argument over public and private Cloud adoption, and said, “It’s not one size fits all.” But can Cloud and Big Data come together? Andras explained that Cloud is not the almighty answer to Big Data. Every organization needs to find the Enterprise Architecture that fits its needs.

The fruits of Big Data can be useful to more than just business intelligence professionals. With the trend of mobility and application development in mind, Chris suggested that developers keep users in mind. Big Data can be used to tell us many different things, but it’s about finding out what is most important and relevant to users in a way that is digestible.

Finally, the panel discussed how Big Data bringing about big changes in almost every aspect of an organization. It is important not to generalize, but customize. Every enterprise needs its own set of architecture to fit its needs. Each organization finds importance in different facets of the data gathered, and security is different at every organization. With all that in mind, the panel agreed that focusing on the analytics is the key.

To view the panel discussion, please watch the broadcasted session here: http://new.livestream.com/opengroup/events/1838807

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Protecting Data is Good. Protecting Information Generated from Big Data is Priceless

By E.G. Nadhan, HP

This was the key message that came out of The Open Group® Big Data Security Tweet Jam on Jan 22 at 9:00 a.m. PT, which addressed several key questions centered on Big Data and security. Here is my summary of the observations made in the context of these questions.

Q1. What is Big Data security? Is it different from data security?

Big data security is more about information security. It is typically external to the corporate perimeter. IT is not prepared today to adequately monitor its sheer volume in brontobytes of data. The time period of long-term storage could violate compliance mandates. Note that storing Big Data in the Cloud changes the game with increased risks of leaks, loss, breaches.

Information resulting from the analysis of the data is even more sensitive and therefore, higher risk – especially when it is Personally Identifiable Information on the Internet of devices requiring a balance between utility and privacy.

At the end of the day, it is all about governance or as they say, “It’s the data, stupid! Govern it.”

Q2. Any thoughts about security systems as producers of Big Data, e.g., voluminous systems logs?

Data gathered from information security logs is valuable but rules for protecting it are the same. Security logs will be a good source to detect patterns of customer usage.

Q3. Most BigData stacks have no built in security. What does this mean for securing Big Data?

There is an added level of complexity because it goes across apps, network plus all end points. Having standards to establish identity, metadata, trust would go a long way. The quality of data could also be a security issue — has it been tampered with, are you being gamed etc. Note that enterprises have varying needs of security around their business data.

Q4. How is the industry dealing with the social and ethical uses of consumer data gathered via Big Data?

Big Data is still nascent and ground rules for handling the information are yet to be established. Privacy issue will be key when companies market to consumers. Organizations are seeking forgiveness rather than permission. Regulatory bodies are getting involved due to consumer pressure. Abuse of power from access to big data is likely to trigger more incentives to attack or embarrass. Note that ‘abuse’ to some is just business to others.

Q5. What lessons from basic data security and cloud security can be implemented in Big Data security?

Security testing is even more vital for Big Data. Limit access to specific devices, not just user credentials. Don’t assume security via obscurity for sensors producing bigdata inputs – they will be targets.

Q6. What are some best practices for securing Big Data? What are orgs doing now and what will organizations be doing 2-3 years from now?

Current best practices include:

  • Treat Big Data as your most valuable asset
  • Encrypt everything by default, proper key management, enforcement of policies, tokenized logs
  • Ask your Cloud and Big Data providers the right questions – ultimately, YOU are responsible for security
  • Assume data needs verification and cleanup before it is used for decisions if you are unable to establish trust with data source

Future best practices:

  • Enterprises treat Information like data today and will respect it as the most valuable asset in the future
  • CIOs will eventually become Chief Officer for Information

Q7. We’re nearing the end of today’s tweet tam. Any last thoughts on Big Data security?

Adrian Lane who participated in the tweet jam will be keynoting at The Open Group Conference in Newport Beach next week and wrote a good best practices paper on securing Big Data.

I have been part of multiple tweet chats specific to security as well as one on Information Optimization. Recently, I also conducted the first Open Group Web Jam internal to The Cloud Work Group.  What I liked about this Big Data Security Tweet Jam is that it brought two key domains together highlighting the intersection points. There was great contribution from subject matter experts forcing participants to think about one domain in the context of the other.

In a way, this post is actually synthesizing valuable information from raw data in the tweet messages – and therefore needs to be secured!

What are your thoughts on the observations made in this tweet jam? What measures are you taking to secure Big Data in your enterprise?

I really enjoyed this tweet jam and would strongly encourage you to actively participate in upcoming tweet jams hosted by The Open Group.  You get to interact with a wide spectrum of knowledgeable practitioners listed in this summary post.

NadhanHP Distinguished Technologist and Cloud Advisor, E.G.Nadhan has more than 25 years of experience in the IT industry across the complete spectrum of selling, delivering and managing enterprise level solutions for HP customers. He is the founding co-chair for The Open Group SOCCI project, and is also the founding co-chair for the Open Group Cloud Computing Governance project. Connect with Nadhan on: Twitter, Facebook, LinkedIn and Journey Blog.

 

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The Open Group Conference Plenary Speaker Sees Big-Data Analytics as a Way to Bolster Quality, Manufacturing and Business Processes

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here: The Open Group Keynoter Sees Big-Data Analytics as a Way to Bolster Quality, Manufacturing and Business Processes

This is a transcript of a sponsored podcast discussion on Big Data analytics and its role in business processes, in conjunction with the The Open Group Conference in Newport Beach.

Dana Gardner: Hello, and welcome to a special thought leadership interview series coming to you in conjunction with The Open Group® Conference on January 28 in Newport Beach, California.

I’m Dana Gardner, Principal Analyst at Interarbor Solutions, and I’ll be your host and moderator throughout these business transformation discussions. The conference will focus on big data and the transformation we need to embrace today.

We are here now with one of the main speakers at the conference; Michael Cavaretta, PhD, Technical Leader of Predictive Analytics for Ford Research and Advanced Engineering in Dearborn, Michigan.

We’ll see how Ford has exploited the strengths of big data analytics by directing them internally to improve business results. In doing so, they scour the metrics from the company’s best processes across myriad manufacturing efforts and through detailed outputs from in-use automobiles, all to improve and help transform their business.

Cavaretta has led multiple data-analytic projects at Ford to break down silos inside the company to best define Ford’s most fruitful datasets. Ford has successfully aggregated customer feedback, and extracted all the internal data to predict how best new features in technologies will improve their cars.

As a lead-in to his Open Group presentation, Michael and I will now explore how big data is fostering business transformation by allowing deeper insights into more types of data efficiently, and thereby improving processes, quality control, and customer satisfaction.

With that, please join me in welcoming Michael Cavaretta. Welcome to BriefingsDirect, Michael.

Michael Cavaretta: Thank you very much.

Gardner: Your upcoming presentation for The Open Group Conference is going to describe some of these new approaches to big data and how that offers some valuable insights into internal operations, and therefore making a better product. To start, what’s different now in being able to get at this data and do this type of analysis from, say, five years ago?

Cavaretta: The biggest difference has to do with the cheap availability of storage and processing power, where a few years ago people were very much concentrated on filtering down the datasets that were being stored for long-term analysis. There has been a big sea change with the idea that we should just store as much as we can and take advantage of that storage to improve business processes.

Gardner: That sounds right on the money, but how do we get here? How do we get to the point where we could start using these benefits from a technology perspective, as you say, better storage, networks, being able to move big dataset, that sort of thing, to wrenching out benefits. What’s the process behind the benefit?

Cavaretta: The process behind the benefits has to do with a sea change in the attitude of organizations, particularly IT within large enterprises. There’s this idea that you don’t need to spend so much time figuring out what data you want to store and worry about the cost associated with it, and more about data as an asset. There is value in being able to store it, and being able to go back and extract different insights from it. This really comes from this really cheap storage, access to parallel processing machines, and great software.

Gardner: It seems to me that for a long time, the mindset was that data is simply the output from applications, with applications being primary and the data being almost an afterthought. It seems like we sort flipped that. The data now is perhaps as important, even more important, than the applications. Does that seem to hold true?

Cavaretta: Most definitely, and we’ve had a number of interesting engagements where people have thought about the data that’s being collected. When we talk to them about big data, storing everything at the lowest level of transactions, and what could be done with that, their eyes light up and they really begin to get it.

Gardner: I suppose earlier, when cost considerations and technical limitations were at work, we would just go for a tip of the iceberg level. Now, as you say, we can get almost all the data. So, is this a matter of getting at more data, different types of data, bringing in unstructured data, all the above? How much you are really going after here?

Cavaretta: I like to talk to people about the possibility that big data provides and I always tell them that I have yet to have a circumstance where somebody is giving me too much data. You can pull in all this information and then answer a variety of questions, because you don’t have to worry that something has been thrown out. You have everything.

You may have 100 questions, and each one of the questions uses a very small portion of the data. Those questions may use different portions of the data, a very small piece, but they’re all different. If you go in thinking, “We’re going to answer the top 20 questions and we’re just going to hold data for that,” that leaves so much on the table, and you don’t get any value out of it.

Gardner: I suppose too that we can think about small samples or small datasets and aggregate them or join them. We have new software capabilities to do that efficiently, so that we’re able to not just look for big honking, original datasets, but to aggregate, correlate, and look for a lifecycle level of data. Is that fair as well?

Cavaretta: Definitely. We’re a big believer in mash-ups and we really believe that there is a lot of value in being able to take even datasets that are not specifically big-data sizes yet, and then not go deep, not get more detailed information, but expand the breadth. So it’s being able to augment it with other internal datasets, bridging across different business areas as well as augmenting it with external datasets.

A lot of times you can take something that is maybe a few hundred thousand records or a few million records, and then by the time you’re joining it, and appending different pieces of information onto it, you can get the big dataset sizes.

Gardner: Just to be clear, you’re unique. The conventional wisdom for big data is to look at what your customers are doing, or just the external data. You’re really looking primarily at internal data, while also availing yourself of what external data might be appropriate. Maybe you could describe a little bit about your organization, what you do, and why this internal focus is so important for you.

Cavaretta: I’m part of a larger department that is housed over in the research and advanced-engineering area at Ford Motor Company, and we’re about 30 people. We work as internal consultants, kind of like Capgemini or Ernst & Young, but only within Ford Motor Company. We’re responsible for going out and looking for different opportunities from the business perspective to bring advanced technologies. So, we’ve been focused on the area of statistical modeling and machine learning for I’d say about 15 years or so.

And in this time, we’ve had a number of engagements where we’ve talked with different business customers, and people have said, “We’d really like to do this.” Then, we’d look at the datasets that they have, and say, “Wouldn’t it be great if we would have had this. So now we have to wait six months or a year.”

These new technologies are really changing the game from that perspective. We can turn on the complete fire-hose, and then say that we don’t have to worry about that anymore. Everything is coming in. We can record it all. We don’t have to worry about if the data doesn’t support this analysis, because it’s all there. That’s really a big benefit of big-data technologies.

Gardner: If you’ve been doing this for 15 years, you must be demonstrating a return on investment (ROI) or a value proposition back to Ford. Has that value proposition been changing? Do you expect it to change? What might be your real value proposition two or three years from now?

Cavaretta: The real value proposition definitely is changing as things are being pushed down in the company to lower-level analysts who are really interested in looking at things from a data-driven perspective. From when I first came in to now, the biggest change has been when Alan Mulally came into the company, and really pushed the idea of data-driven decisions.

Before, we were getting a lot of interest from people who are really very focused on the data that they had internally. After that, they had a lot of questions from their management and from upper level directors and vice-president saying, “We’ve got all these data assets. We should be getting more out of them.” This strategic perspective has really changed a lot of what we’ve done in the last few years.

Gardener: As I listen to you Michael, it occurs to me that you are applying this data-driven mentality more deeply. As you pointed out earlier, you’re also going after all the data, all the information, whether that’s internal or external.

In the case of an automobile company, you’re looking at the factory, the dealers, what drivers are doing, what the devices within the automobile are telling you, factoring that back into design relatively quickly, and then repeating this process. Are we getting to the point where this sort of Holy Grail notion of a total feedback loop across the lifecycle of a major product like an automobile is really within our grasp? Are we getting there, or is this still kind of theoretical. Can we pull it altogether and make it a science?

Cavaretta: The theory is there. The question has more to do with the actual implementation and the practicality of it. We still are talking a lot of data where even with new advanced technologies and techniques that’s a lot of data to store, it’s a lot of data to analyze, there’s a lot of data to make sure that we can mash-up appropriately.

And, while I think the potential is there and I think the theory is there. There is also a work in being able to get the data from multiple sources. So everything which you can get back from the vehicle, fantastic. Now if you marry that up with internal data, is it survey data, is it manufacturing data, is it quality data? What are the things do you want to go after first? We can’t do everything all at the same time.

Our perspective has been let’s make sure that we identify the highest value, the greatest ROI areas, and then begin to take some of the major datasets that we have and then push them and get more detail. Mash them up appropriately and really prove up the value for the technologists.

Gardner: Clearly, there’s a lot more to come in terms of where we can take this, but I suppose it’s useful to have a historic perspective and context as well. I was thinking about some of the early quality gurus like Deming and some of the movement towards quality like Six Sigma. Does this fall within that same lineage? Are we talking about a continuum here over that last 50 or 60 years, or is this something different?

Cavaretta: That’s a really interesting question. From the perspective of analyzing data, using data appropriately, I think there is a really good long history, and Ford has been a big follower of Deming and Six Sigma for a number of years now.

The difference though, is this idea that you don’t have to worry so much upfront about getting the data. If you’re doing this right, you have the data right there, and this has some great advantages. You’ll have to wait until you get enough history to look for somebody’s patterns. Then again, it also has some disadvantage, which is you’ve got so much data that it’s easy to find things that could be spurious correlations or models that don’t make any sense.

The piece that is required is good domain knowledge, in particular when you are talking about making changes in the manufacturing plant. It’s very appropriate to look at things and be able to talk with people who have 20 years of experience to say, “This is what we found in the data. Does this match what your intuition is?” Then, take that extra step.

Gardner: Tell me a little about sort a day in the life of your organization and your team to let us know what you do. How do you go about making more data available and then reaching some of these higher-level benefits?

Cavaretta: We’re very much focused on interacting with the business. Most of all, we do have to deal with working on pilot projects and working with our business customers to bring advanced analytics and big data technologies to bear against these problems. So we work in kind of what we call push-and-pull model.

We go out and investigate technologies and say these are technologies that Ford should be interested in. Then, we look internally for business customers who would be interested in that. So, we’re kind of pushing the technologies.

From the pull perspective, we’ve had so many successful engagements in such good contacts and good credibility within the organization that we’ve had people come to us and say, “We’ve got a problem. We know this has been in your domain. Give us some help. We’d love to be able to hear your opinions on this.”

So we’ve pulled from the business side and then our job is to match up those two pieces. It’s best when we will be looking at a particular technology and we have somebody come to us and we say, “Oh, this is a perfect match.”

Those types of opportunities have been increasing in the last few years, and we’ve been very happy with the number of internal customers that have really been very excited about the areas of big data.

Gardner: Because this is The Open Group conference and an audience that’s familiar with the IT side of things, I’m curious as to how this relates to software and software development. Of course there are so many more millions of lines of code in automobiles these days, software being more important than just about everything. Are you applying a lot of what you are doing to the software side of the house or are the agile and the feedback loops and the performance management issues a separate domain, or it’s your crossover here?

Cavaretta: There’s some crossover. The biggest area that we’ve been focused on has been picking information, whether internal business processes or from the vehicle, and then being able to bring it back in to derive value. We have very good contacts in the Ford IT group, and they have been fantastic to work with in bringing interesting tools and technology to bear, and then looking at moving those into production and what’s the best way to be able to do that.

A fantastic development has been this idea that we’re using some of the more agile techniques in this space and Ford IT has been pushing this for a while. It’s been fantastic to see them work with us and be able to bring these techniques into this new domain. So we’re pushing the envelope from two different directions.

Gardner: It sounds like you will be meeting up at some point with a complementary nature to your activities.

Cavaretta: Definitely.

Gardner: Let’s move on to this notion of the “Internet of things,” a very interesting concept that lot of people talk about. It seems relevant to what we’ve been discussing. We have sensors in these cars, wireless transfer of data, more-and-more opportunity for location information to be brought to bear, where cars are, how they’re driven, speed information, all sorts of metrics, maybe making those available through cloud providers that assimilate this data.

So let’s not go too deep, because this is a multi-hour discussion all on its own, but how is this notion of the Internet of things being brought to bear on your gathering of big data and applying it to the analytics in your organization?

Cavaretta: It is a huge area, and not only from the internal process perspective —  RFID tags within the manufacturing plans, as well as out on the plant floor, and then all of the information that’s being generated by the vehicle itself.

The Ford Energi generates about 25 gigabytes of data per hour. So you can imagine selling couple of million vehicles in the near future with that amount of data being generated. There are huge opportunities within that, and there are also some interesting opportunities having to do with opening up some of these systems for third-party developers. OpenXC is an initiative that we have going on to add at Research and Advanced Engineering.

We have a lot of data coming from the vehicle. There’s huge number of sensors and processors that are being added to the vehicles. There’s data being generated there, as well as communication between the vehicle and your cell phone and communication between vehicles.

There’s a group over at Ann Arbor Michigan, the University of Michigan Transportation Research Institute (UMTRI), that’s investigating that, as well as communication between the vehicle and let’s say a home system. It lets the home know that you’re on your way and it’s time to increase the temperature, if it’s winter outside, or cool it at the summer time. The amount of data that’s been generated there is invaluable information and could be used for a lot of benefits, both from the corporate perspective, as well as just the very nature of the environment.

Gardner: Just to put a stake in the ground on this, how much data do cars typically generate? Do you have a sense of what now is the case, an average?

Cavaretta: The Energi, according to the latest information that I have, generates about 25 gigabytes per hour. Different vehicles are going to generate different amounts, depending on the number of sensors and processors on the vehicle. But the biggest key has to do with not necessarily where we are right now but where we will be in the near future.

With the amount of information that’s being generated from the vehicles, a lot of it is just internal stuff. The question is how much information should be sent back for analysis and to find different patterns? That becomes really interesting as you look at external sensors, temperature, humidity. You can know when the windshield wipers go on, and then to be able to take that information, and mash that up with other external data sources too. It’s a very interesting domain.

Gardner: So clearly, it’s multiple gigabytes per hour per vehicle and probably going much higher.

Cavaretta: Easily.

Gardner: Let’s move forward now for those folks who have been listening and are interested in bringing this to bear on their organizations and their vertical industries, from the perspective of skills, mindset, and culture. Are there standards, certification, or professional organizations that you’re working with in order to find the right people?

It’s a big question. Let’s look at what skills do you target for your group, and what ways you think that you can improve on that. Then, we’ll get into some of those larger issues about culture and mindset.

Cavaretta: The skills that we have in our department, in particular on our team, are in the area of computer science, statistics, and some good old-fashioned engineering domain knowledge. We’ve really gone about this from a training perspective. Aside from a few key hires, it’s really been an internally developed group.

The biggest advantage that we have is that we can go out and be very targeted with the amount of training that we have. There are such big tools out there, especially in the open-source realm, that we can spin things up with relatively low cost and low risk, and do a number of experiments in the area. That’s really the way that we push the technologies forward.

Gardner: Why The Open Group? Why is that a good forum for your message, and for your research here?

Cavaretta: The biggest reason is the focus on the enterprise, where there are a lot of advantages and a lot of business cases, looking at large enterprises and where there are a lot of systems, companies that can take a relatively small improvement, and it can make a large difference on the bottom-line.

Talking with The Open Group really gives me an opportunity to be able to bring people on board with the idea that you should be looking at a difference in mindset. It’s not “Here’s a way that data is being generated, look, try and conceive of some questions that we can use, and we’ll store that too.” Let’s just take everything, we’ll worry about it later, and then we’ll find the value.

Gardner: I’m sure the viewers of your presentation on January 28 will be gathering a lot of great insights. A lot of the people that attend The Open Group conferences are enterprise architects. What do you think those enterprise architects should be taking away from this? Is there something about their mindset that should shift in recognizing the potential that you’ve been demonstrating?

Cavaretta: It’s important for them to be thinking about data as an asset, rather than as a cost. You even have to spend some money, and it may be a little bit unsafe without really solid ROI at the beginning. Then, move towards pulling that information in, and being able to store it in a way that allows not just the high-level data scientist to get access to and provide value, but people who are interested in the data overall. Those are very important pieces.

The last one is how do you take a big-data project, how do you take something where you’re not storing in the traditional business intelligence (BI) framework that an enterprise can develop, and then connect that to the BI systems and look at providing value to those mash-ups. Those are really important areas that still need some work.

Gardner: Another big constituency within The Open Group community are those business architects. Is there something about mindset and culture, getting back to that topic, that those business-level architects should consider? Do you really need to change the way you think about planning and resource allocation in a business setting, based on the fruits of things that you are doing with big data?

Cavaretta: I really think so. The digital asset that you have can be monetized to change the way the business works, and that could be done by creating new assets that then can be sold to customers, as well as improving the efficiencies of the business.

This idea that everything is going to be very well-defined and there is a lot of work that’s being put into  making sure that data has high quality, I think those things need to be changed somewhat. As you’re pulling the data in, as you are thinking about long-term storage, it’s more the access to the information, rather than the problem in just storing it.

Gardner: Interesting that you brought up that notion that the data becomes a product itself and even a profit center perhaps.

Cavaretta: Exactly. There are many companies, especially large enterprises, that are looking at their data assets and wondering what can they do to monetize this, not only to just pay for the efficiency improvement but as a new revenue stream.

Gardner: We’re almost out of time. For those organizations that want to get started on this, are there any 20/20 hindsights or Monday morning quarterback insights you can provide. How do you get started? Do you appoint a leader? Do you need a strategic roadmap, getting this culture or mindset shifted, pilot programs? How would you recommend that people might begin the process of getting into this?

Cavaretta: We’re definitely a huge believer in pilot projects and proof of concept, and we like to develop roadmaps by doing. So get out there. Understand that it’s going to be messy. Understand that it maybe going to be a little bit more costly and the ROI isn’t going to be there at the beginning.

But get your feet wet. Start doing some experiments, and then, as those experiments turn from just experimentation into really providing real business value, that’s the time to start looking at a more formal aspect and more formal IT processes. But you’ve just got to get going at this point.

Gardner: I would think that the competitive forces are out there. If you are in a competitive industry, and those that you compete against are doing this and you are not, that could spell some trouble.

Cavaretta:  Definitely.

Gardner: We’ve been talking with Michael Cavaretta, PhD, Technical Leader of Predictive Analytics at Ford Research and Advanced Engineering in Dearborn, Michigan. Michael and I have been exploring how big data is fostering business transformation by allowing deeper insights into more types of data and all very efficiently. This is improving processes, updating quality control and adding to customer satisfaction.

Our conversation today comes as a lead-in to Michael’s upcoming plenary presentation. He is going to be talking on January 28 in Newport Beach California, as part of The Open Group conference.

You will hear more from Michael and others, the global leaders on big data that are going to be gathering to talk about business transformation from big data at this conference. So a big thank you to Michael for joining us in this fascinating discussion. I really enjoyed it and I look forward to your presentation on the 28.

Cavaretta: Thank you very much.

Gardner: And I would encourage our listeners and readers to attend the conference or follow more of the threads in social media from the event. Again, it’s going to be happening from January 27 to January 30 in Newport Beach, California.

This is Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator through the thought leadership interviews. Thanks again for listening, and come back next time.

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How Should we use Cloud?

By Chris Harding, The Open Group

How should we use Cloud? This is the key question at the start of 2013.

The Open Group® conferences in recent years have thrown light on, “What is Cloud?” and, “Should we use Cloud?” It is time to move on.

Cloud as a Distributed Processing Platform

The question is an interesting one, because the answer is not necessarily, “Use Cloud resources just as you would use in-house resources.” Of course, you can use Cloud processing and storage to replace or supplement what you have in-house, and many companies are doing just that. You can also use the Cloud as a distributed computing platform, on which a single application instance can use multiple processing and storage resources, perhaps spread across many countries.

It’s a bit like contracting a company to do a job, rather than hiring a set of people. If you hire a set of people, you have to worry about who will do what when. Contract a company, and all that is taken care of. The company assembles the right people, schedules their work, finds replacements in case of sickness, and moves them on to other things when their contribution is complete.

This doesn’t only make things easier, it also enables you to tackle bigger jobs. Big Data is the latest technical phenomenon. Big Data can be processed effectively by parceling the work out to multiple computers. Cloud providers are beginning to make the tools to do this available, using distributed file systems and map-reduce. We do not yet have, “Distributed Processing as a Service” – but that will surely come.

Distributed Computing at the Conference

Big Data is the main theme of the Newport Beach conference. The plenary sessions have keynote presentations on Big Data, including the crucial aspect of security, and there is a Big Data track that explores in depth its use in Enterprise Architecture.

There are also Cloud tracks that explore the business aspects of using Cloud and the use of Cloud in Enterprise Architecture, including a session on its use for Big Data.

Service orientation is generally accepted as a sound underlying principle for systems using both Cloud and in-house resources. The Service Oriented Architecture (SOA) movement focused initially on its application within the enterprise. We are now looking to apply it to distributed systems of all kinds. This may require changes to specific technology and interfaces, but not to the fundamental SOA approach. The Distributed Services Architecture track contains presentations on the theory and practice of SOA.

Distributed Computing Work in The Open Group

Many of the conference presentations are based on work done by Open Group members in the Cloud Computing, SOA and Semantic Interoperability Work Groups, and in the Architecture, Security and Jericho Forums. The Open Group enables people to come together to develop standards and best practices for the benefit of the architecture community. We have active Work Groups and Forums working on artifacts such as a Cloud Computing Reference Architecture, a Cloud Portability and Interoperability Guide, and a Guide to the use of TOGAF® framework in Cloud Ecosystems.

The Open Group Conference in Newport Beach

Our conferences provide an opportunity for members and non-members to discuss ideas together. This happens not only in presentations and workshops, but also in informal discussions during breaks and after the conference sessions. These discussions benefit future work at The Open Group. They also benefit the participants directly, enabling them to bring to their enterprises ideas that they have sounded out with their peers. People from other companies can often bring new perspectives.

Most enterprises now know what Cloud is. Many have identified specific opportunities where they will use it. The challenge now for enterprise architects is determining how best to do this, either by replacing in-house systems, or by using the Cloud’s potential for distributed processing. This is the question for discussion at The Open Group Conference in Newport Beach. I’m looking forward to an interesting conference!

Dr. Chris Harding is Director for Interoperability and SOA at The Open Group. He has been with The Open Group for more than ten years, and is currently responsible for managing and supporting its work on interoperability, including SOA and interoperability aspects of Cloud Computing. He is a member of the BCS, the IEEE and the AEA, and is a certified TOGAF practitioner.

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#ogChat Summary – Big Data and Security

By Patty Donovan, The Open Group

The Open Group hosted a tweet jam (#ogChat) to discuss Big Data security. In case you missed the conversation, here is a recap of the event.

The Participants

A total of 18 participants joined in the hour-long discussion, including:

Q1 What is #BigData #security? Is it different from #data security? #ogChat

Participants seemed to agree that while Big Data security is similar to data security, it is more extensive. Two major factors to consider: sensitivity and scalability.

  • @dustinkirkland At the core it’s the same – sensitive data – but the difference is in the size and the length of time this data is being stored. #ogChat
  • @jim_hietala Q1: Applying traditional security controls to BigData environments, which are not just very large info stores #ogChat
  • @TheTonyBradley Q1. The value of analyzing #BigData is tied directly to the sensitivity and relevance of that data–making it higher risk. #ogChat
  • @AdrianLane Q1 Securing #BigData is different. Issues of velocity, scale, elasticity break many existing security products. #ogChat
  • @editingwhiz #Bigdata security is standard information security, only more so. Meaning sampling replaced by complete data sets. #ogchat
  • @Dana_Gardner Q1 Not only is the data sensitive, the analysis from the data is sensitive. Secret. On the QT. Hush, hush. #BigData #data #security #ogChat
    • @Technodad @Dana_Gardner A key point. Much #bigdata will be public – the business value is in cleanup & analysis. Focus on protecting that. #ogChat

Q2 Any thoughts about #security systems as producers of #BigData, e.g., voluminous systems logs? #ogChat

  • Most agreed that security systems should be setting an example for producing secure Big Data environments.
  • @dustinkirkland Q2. They should be setting the example. If the data is deemed important or sensitive, then it should be secured and encrypted. #ogChat
  • @TheTonyBradley Q2. Data is data. Data gathered from information security logs is valuable #BigData, but rules for protecting it are the same. #ogChat
  • @elinormills Q2 SIEM is going to be big. will drive spending. #ogchat #bigdata #security
  • @jim_hietala Q2: Well instrumented IT environments generate lots of data, and SIEM/audit tools will have to be managers of this #BigData #ogchat
  • @dustinkirkland @theopengroup Ideally #bigdata platforms will support #tokenization natively, or else appdevs will have to write it into apps #ogChat

Q3 Most #BigData stacks have no built in #security. What does this mean for securing #BigData? #ogChat

The lack of built-in security hoists a target on the Big Data. While not all enterprise data is sensitive, housing it insecurely runs the risk of compromise. Furthermore, security solutions not only need to be effective, but also scalable as data will continue to get bigger.

  • @elinormills #ogchat big data is one big hacker target #bigdata #security
    • @editingwhiz @elinormills #bigdata may be a huge hacker target, but will hackers be able to process the chaff out of it? THAT takes $$$ #ogchat
    • @elinormills @editingwhiz hackers are innovation leaders #ogchat
    • @editingwhiz @elinormills Yes, hackers are innovation leaders — in security, but not necessarily dataset processing. #eweeknews #ogchat
  • @jim_hietala Q3:There will be a strong market for 3rd party security tools for #BigData – existing security technologies can’t scale #ogchat
  • @TheTonyBradley Q3. When you take sensitive info and store it–particularly in the cloud–you run the risk of exposure or compromise. #ogChat
  • @editingwhiz Not all enterprises have sensitive business data they need to protect with their lives. We’re talking non-regulated, of course. #ogchat
  • @TheTonyBradley Q3. #BigData is sensitive enough. The distilled information from analyzing it is more sensitive. Solutions need to be effective. #ogChat
  • @AdrianLane Q3 It means identifying security products that don’t break big data – i.e. they scale or leverage #BigData #ogChat
    • @dustinkirkland @AdrianLane #ogChat Agreed, this is where certifications and partnerships between the 3rd party and #bigdata vendor are essential.

Q4 How is the industry dealing with the social and ethical uses of consumer data gathered via #BigData? #ogChat #privacy

Participants agreed that the industry needs to improve when it comes to dealing with the social and ethical used of consumer data gathered through Big Data. If the data is easily accessible, hackers will be attracted. No matter what, the cost of a breach is far greater than any preventative solution.

  • @dustinkirkland Q4. #ogChat Sadly, not well enough. The recent Instagram uproar was well publicized but such abuse of social media rights happens every day.
    • @TheTonyBradley @dustinkirkland True. But, they’ll buy the startups, and take it to market. Fortune 500 companies don’t like to play with newbies. #ogChat
    • @editingwhiz Disagree with this: Fortune 500s don’t like to play with newbies. We’re seeing that if the IT works, name recognition irrelevant. #ogchat
    • @elinormills @editingwhiz @thetonybradley ‘hacker’ covers lot of ground, so i would say depends on context. some of my best friends are hackers #ogchat
    • @Technodad @elinormills A core point- data from sensors will drive #bigdata as much as enterprise data. Big security, quality issues there. #ogChat
  • @Dana_Gardner Q4 If privacy is a big issue, hacktivism may crop up. Power of #BigData can also make it socially onerous. #data #security #ogChat
  • @dustinkirkland Q4. The cost of a breach is far greater than the cost (monetary or reputation) of any security solution. Don’t risk it. #ogChat

Q5 What lessons from basic #datasecurity and #cloud #security can be implemented in #BigData security? #ogChat

The principles are the same, just on a larger scale. The biggest risks come from cutting corners due to the size and complexity of the data gathered. As hackers (like Anonymous) get better, so does security regardless of the data size.

  • @TheTonyBradley Q5. Again, data is data. The best practices for securing and protecting it stay the same–just on a more massive #BigData scale. #ogChat
  • @Dana_Gardner Q5 Remember, this is in many ways unchartered territory so expect the unexpected. Count on it. #BigData #data #security #ogChat
  • @NadhanAtHP A5 @theopengroup – Security Testing is even more vital when it comes to #BigData and Information #ogChat
  • @TheTonyBradley Q5. Anonymous has proven time and again that most existing data security is trivial. Need better protection for #BigData. #ogChat

Q6 What are some best practices for securing #BigData? What are orgs doing now, and what will orgs be doing 2-3 years from now? #ogChat

While some argued encrypting everything is the key, and others encouraged pressure on big data providers, most agreed that a multi-step security infrastructure is necessary. It’s not just the data that needs to be secured, but also the transportation and analysis processes.

  • @dustinkirkland Q6. #ogChat Encrypting everything, by default, at least at the fs layer. Proper key management. Policies. Logs. Hopefully tokenized too.
  • @dustinkirkland Q6. #ogChat Ask tough questions of your #cloud or #bigdata provider. Know what they are responsible for and who has access to keys. #ogChat
    • @elinormills Agreed–> @dustinkirkland Q6. #ogChat Ask tough questions of your #cloud or #bigdataprovider. Know what they are responsible for …
  • @Dana_Gardner Q6 Treat most #BigData as a crown jewel, see it as among most valuable assets. Apply commensurate security. #data #security #ogChat
  • @elinormills Q6 govt level crypto minimum, plus protect all endpts #ogchat #bigdata #security
  • @TheTonyBradley Q6. Multi-faceted issue. Must protect raw #BigData, plus processing, analyzing, transporting, and resulting distilled analysis. #ogChat
  • @Technodad If you don’t establish trust with data source, you need to assume data needs verification, cleanup before it is used for decisions. #ogChat

A big thank you to all the participants who made this such a great discussion!

patricia donovanPatricia Donovan is Vice President, Membership & Events, at The Open Group and a member of its executive management team. In this role she is involved in determining the company’s strategic direction and policy as well as the overall management of that business area. Patricia joined The Open Group in 1988 and has played a key role in the organization’s evolution, development and growth since then. She also oversees the company’s marketing, conferences and member meetings. She is based in the U.S.

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Questions for the Upcoming Big Data Security Tweet Jam on Jan. 22

By Patty Donovan, The Open Group

Last week, we announced our upcoming tweet jam on Tuesday, January 22 at 9:00 a.m. PT/12:00 p.m. ET/5:00 p.m. BST, which will examine the impact of Big Data on security and how it will change the security landscape.

Please join us next Tuesday, January 22! The discussion will be moderated by Dana Gardner (@Dana_Gardner), ZDNet – Briefings Direct. We welcome Open Group members and interested participants from all backgrounds to join the session. Our panel of experts will include:

  • Elinor Mills, former CNET reporter and current director of content and media strategy at Bateman Group (@elinormills)
  • Jaikumar Vijayan, Computerworld (@jaivijayan)
  • Chris Preimesberger, eWEEK (@editingwhiz)
  • Tony Bradley, PC World (@TheTonyBradley)
  • Michael Santarcangelo, Security Catalyst Blog (@catalyst)

The discussion will be guided by these six questions:

  1. What is #BigData security? Is it different from #data #security? #ogChat
  2. Any thoughts about #security systems as producers of #BigData, e.g., voluminous systems logs? #ogChat
  3. Most #BigData stacks have no built in #security. What does this mean for securing BigData? #ogChat
  4. How is the industry dealing with the social and ethical uses of consumer data gathered via #BigData? #ogChat #privacy
  5. What lessons from basic data security and #cloud #security can be implemented in #BigData #security? #ogChat
  6. What are some best practices for securing #BigData? #ogChat

To join the discussion, please follow the #ogChat hashtag during the allotted discussion time. Other hashtags we recommend you use during the event include:

  • Information Security: #InfoSec
  • Security: #security
  • BYOD: #BYOD
  • Big Data: #BigData
  • Privacy: #privacy
  • Mobile: #mobile
  • Compliance: #compliance

For more information about the tweet jam, guidelines and general background information, please visit our previous blog post: http://blog.opengroup.org/2013/01/15/big-data-security-tweet-jam/

If you have any questions prior to the event or would like to join as a participant, please direct them to Rod McLeod (rmcleod at bateman-group dot com), or leave a comment below. We anticipate a lively chat and hope you will be able to join us!

patricia donovanPatricia Donovan is Vice President, Membership & Events, at The Open Group and a member of its executive management team. In this role she is involved in determining the company’s strategic direction and policy as well as the overall management of that business area. Patricia joined The Open Group in 1988 and has played a key role in the organization’s evolution, development and growth since then. She also oversees the company’s marketing, conferences and member meetings. She is based in the U.S.

 

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Big Data Security Tweet Jam

By Patty Donovan, The Open Group

On Tuesday, January 22, The Open Group will host a tweet jam examining the topic of Big Data and its impact on the security landscape.

Recently, Big Data has been dominating the headlines, analyzing everything about the topic from how to manage and process it, to the way it will impact your organization’s IT roadmap. As 2012 came to a close, analyst firm, Gartner predicted that data will help drive IT spending to $3.8 trillion in 2014. Knowing the phenomenon is here to stay, enterprises face a new and daunting challenge of how to secure Big Data. Big Data security also raises other questions, such as: Is Big Data security different from data security? How will enterprises handle Big Data security? What is the best approach to Big Data security?

It’s yet to be seen if Big Data will necessarily revolutionize enterprise security, but it certainly will change execution – if it hasn’t already. Please join us for our upcoming Big Data Security tweet jam where leading security experts will discuss the merits of Big Data security.

Please join us on Tuesday, January 22 at 9:00 a.m. PT/12:00 p.m. ET/5:00 p.m. GMT for a tweet jam, moderated by Dana Gardner (@Dana_Gardner), ZDNet – Briefings Direct, that will discuss and debate the issues around big data security. Key areas that will be addressed during the discussion include: data security, privacy, compliance, security ethics and, of course, Big Data. We welcome Open Group members and interested participants from all backgrounds to join the session and interact with our panel of IT security experts, analysts and thought leaders led by Jim Hietala (@jim_hietala) and Dave Lounsbury (@Technodad) of The Open Group. To access the discussion, please follow the #ogChat hashtag during the allotted discussion time.

And for those of you who are unfamiliar with tweet jams, here is some background information:

What Is a Tweet Jam?

A tweet jam is a one hour “discussion” hosted on Twitter. The purpose of the tweet jam is to share knowledge and answer questions on Big Data security. Each tweet jam is led by a moderator and a dedicated group of experts to keep the discussion flowing. The public (or anyone using Twitter interested in the topic) is encouraged to join the discussion.

Participation Guidance

Whether you’re a newbie or veteran Twitter user, here are a few tips to keep in mind:

  • Have your first #ogChat tweet be a self-introduction: name, affiliation, occupation.
  • Start all other tweets with the question number you’re responding to and the #ogChat hashtag.
    • Sample: “Q1 enterprises will have to make significant adjustments moving forward to secure Big Data environments #ogChat”
    • Please refrain from product or service promotions. The goal of a tweet jam is to encourage an exchange of knowledge and stimulate discussion.
    • While this is a professional get-together, we don’t have to be stiff! Informality will not be an issue!
    • A tweet jam is akin to a public forum, panel discussion or Town Hall meeting – let’s be focused and thoughtful.

If you have any questions prior to the event or would like to join as a participant, please direct them to Rod McLeod (rmcleod at bateman-group dot com). We anticipate a lively chat and hope you will be able to join!

 

patricia donovanPatricia Donovan is Vice President, Membership & Events, at The Open Group and a member of its executive management team. In this role she is involved in determining the company’s strategic direction and policy as well as the overall management of that business area. Patricia joined The Open Group in 1988 and has played a key role in the organization’s evolution, development and growth since then. She also oversees the company’s marketing, conferences and member meetings. She is based in the U.S.

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