Tag Archives: data center

It Is a Big World for Big Data After All

By E.G. Nadhan, HP

In the Information Week Global CIO blog, Patrick Houston says that big is bad when it comes to data, questioning the appropriateness of the term big data. Houston highlights the risk of the term being taken literally by the not-so-technical folks. Big data will continue to spread with emerging associative terms like big data expertbig data technologies, etc. I also see other reactions to this term like the one in Allison Watterson’s post, “What do you mean big data, little data is hard enough.” So why has it gained this broad adoption so fast?

Here are my top 5 reasons why the term big data has stuck, and why it may be appropriate, after all:

Foundational. It all started with data processing going decades back. Over the years, we have seen:

  • Big Computer – monolithic behemoths – or in today’s terms, legacy platforms
  • Big Network – local and wide area networks
  • Big Connector – the Internet that facilitated meaningful access with a purpose to consumers across the globe
  • Big Communicator – social media that has fostered communication beyond our imagination

It is all leading up to the generation and consumption of big data driven by presence. It was all about data to start with, and we have come back full circle to data again.

PervasiveBig Data will pervasively promote a holistic approach across all architectural elements of cloud computing:

  • Compute – complex data processing algorithms
  • Network – timely transmission of high volumes of data
  • Storage – various media to house <choose your prefix> bytes of data

FamiliarBig is always part of compound associations whether it be a hamburger (Big Mac), Big Brother or The Big Dipper. It is a big deal, shall we say? Data has always been generated and consumed with continued emergence of evolutionary technologies. You say big data and pictures of data rapidly growing like a balloon or spreading like water come to mind. It has something to do with data. There is something big about it.

Synthetic. Thomas C. Redman introduces a term “Informationlization” in the Harvard Business Review blog titled, “Integrate data into product, or get left behind.”  To me, the term big data is also about the synthesis individual pixels on the display device coming together to present a cohesive, meaningful picture.

Simple. You cannot get simpler than a three-letter word paired up with a four-letter word to mean something by itself. Especially when neither one is a TLA (three-letter acronym) for something very difficult to pronounce! Children in their elementary grades start learning these simple words before moving on to complex spelling bees with an abundance of vowels and y and x and q letters. Big data rolls off the tongue easily with a total of three syllables.

As humans, we tend to gravitate towards simplicity, which is why the whole world chimes in and sways back and forth when Sir Paul McCartney sings Hey Jude! decades after the first performance of this immortal piece. The line that sticks in our mind is the simplest line in the whole song – easy to render – one that we hum along with our hearts. Likewise, big data provides the most simplistic interpretation possible for a really complex world out there.

I actually like what Houston proposes – gushing data. However, I am not sure if it would enjoy the attention that big data gets. It represents a domain that needs to be addressed globally across all architectural layers by everyone including the consumers, administrators and orchestrators of data.

Therefore, big data is not just good enough – it is apt.

What about you? Do you have other names in mind? What does big data mean to you?

A version of this blog post originally appeared on the HP Enterprise Services Blog.

HP Distinguished Technologist and Cloud Advisor, 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 @NadhanAtHPwww.hp.com/go/journeyblog

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Facebook – the open source data center

By Mark Skilton, Capgemini

The recent announcement by Facebook of its decision to publish its data center specifications as open source illustrates a new emerging trend in commoditization of compute resources.

Key features of the new facility include:

  • The Oregon facility announced to the world press in April 2011 is 150,000 sq. ft., a $200 million investment. At any one time, the total of Facebook’s 500-million user capacity could be hosted in this one site. Another Facebook data center facility is scheduled to open in 2012 in North Carolina. There may possibly be future data centers in Europe or elsewhere if required by the Palo Alto, Calif.-based company
  • The Oregon data center enables Facebook to reduce its energy consumption per unit of computing power by 38%
  • The data center has a PUE of 1.07, well below the EPA-defined state-of-the-art industry average of 1.5. This means 93% of the energy from the grid makes it into every Open Compute Server.
  • Removed centralized chillers, eliminated traditional inline UPS systems and removed a 480V to 208V transformation
  • Ethernet-powered LED lighting and passive cooling infrastructure reduce energy spent on running the facility
  • New second-level “evaporative cooling system”, a multi-layer method of transforming room temperature and air filtration
  • Launch of the “Open Compute Project” to share the data center design as Open Source. The aim is to encourage collaboration of data center design to improve overall energy consumption and environmental impact. Other observers also see this as a way of reducing component sourcing costs further, as most of the designs are low-cost commodity hardware
  • The servers are 38% more efficient and 24% lower cost

While this can be simply described as a major Cloud services company seeing their data centers as commodity and non-core to their services business, this perhaps is something of a more significant shift in the Cloud Computing industry in general.

Facebook making its data centers specifications open source demonstrates that IaaS (Infrastructure as a Service) utility computing is now seen as a commodity and non-differentiating to companies like Facebook and anyone else who wants cheap compute resources.

What becomes essential is the efficiencies of operation that result in provisioning and delivery of these services are now the key differentiator.

Furthermore, it can be seen that it’s a trend towards what you do with the IaaS storage and compute. How we architect solutions that develop software as a service (SaaS) capabilities becomes the essential differentiator. It is how business models and consumers can maximize these benefits, which increases the importance of architecture and solutions for Cloud. This is key for The Open Group’s vision of “Boundaryless Information Flow™”. It’s how Cloud architecture services are architected, and how architects who design effective Cloud services that use these commodity Cloud resources and capabilities make the difference. Open standards and interoperability are critical to the success of this. How solutions and services are developed to build private, public or hybrid Clouds are the new differentiation. This does not ignore the fact that world-class data centers and infrastructure services are vital of course, but it’s now the way they are used to create value that becomes the debate.

Mark Skilton, Director, Capgemini, is the Co-Chair of The Open Group Cloud Computing Work Group. He has been involved in advising clients and developing of strategic portfolio services in Cloud Computing and business transformation. His recent contributions include the publication of Return on Investment models on Cloud Computing widely syndicated that achieved 50,000 hits on CIO.com and in the British Computer Society 2010 Annual Review. His current activities include development of a new Cloud Computing Model standards and best practices on the subject of Cloud Computing impact on Outsourcing and Off-shoring models and contributed to the second edition of the Handbook of Global Outsourcing and Off-shoring published through his involvement with Warwick Business School UK Specialist Masters Degree Program in Information Systems Management.

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