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Analytics for Human Information: News You Can Use From the Big Data Innovation Summit

ChrisSurdak ‎09-13-2013 09:24 AM - edited ‎02-19-2015 01:54 PM

The HP team is currently enjoying day #2 at the Big Data Innovation Summit in Boston, and it’s a pleasant surprise how well-attended this event has been.  Among the more memorable sessions were those from NASA scientists, lead architects from companies like Groupon, Trip and Sears, and of course our own Jeff Veis, who presented our HAVEn solution architecture in his main-stage presentation.  Judging by the number of people taking smart-phone pictures during the session, and surrounding Jeff after his talk, there is definitely a great deal of interest in what HP is doing to innovate in the area of Big Data. Check out my previous post on HAVen.

To that end, there are a few themes that have come out of yesterday’s sessions that have stuck in my mind and that I thought would be worth sharing here.  First off, the whole focus of “Big Data” seems to be shifting; or perhaps drifting.  Two to three years ago, we were all heavily focused upon the pure bigness of Big Data.  How do I even process hundreds of terabytes?  How do I make that technically feasible?  After all, a trillion records here, a trillion there, it starts to add up!

From the sessions yesterday, we’ve clearly smashed through many of those technical barriers and we’re collectively moving the ball very quickly as far as pure data size is concerned.  Several of the presenters were sharing their use cases where they had trillions of records in their data sets, and billions of updates per day, and they were talking about it as if that were routine; and so it is.

If bigness is no longer such a focus of Big Data where is our focus shifting?  The simple answer appears to be Value.  I can now crunch petabytes of data, so what? What’s the business case?  How does it transform my relationship with my customers? How does that make me more competitive? And most fundamentally, how do I monetize this information?  It is the answers to these questions that now seem elusive.

We are starting to see examples of businesses who are making this shift towards delivering value from their Big Data efforts and many of these results are pretty exciting.  The faster we move past the academic exercise of creating Big Data platforms and on to the business exercise of making money from these platforms, the sooner we will see the real impact of Big Data in our daily lives.

It is also becoming apparent that the “art of the possible” is rapidly changing in the Big Data space.  We are now able to analyze quantities of information that sounded like science fiction two years ago.  There are now lots of examples of companies whose sole purpose is to process data and turn it into information.  Examples from the conference include Klout, Groupon, Twitter and so on.  For these companies, data is a raw material and information and insight is their product. Many of them have become wildly successful in just a few years, manipulating nothing but ones and zeros.  These guys are defining, and redefining, the art of the possible.  And in our constantly-accelerating world, today’s “art of the possible” becomes tomorrow’s “art of the necessary”, and the next day’s “too late.”

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About the Author


Chris Surdak is a Subject Matter Expert on Information Governance, analytics and eDiscovery for HP Autonomy. He has over 20 years of consulting and technology experience, and holds a Juris Doctor from Taft University, an MS from the Wharton School at the University of Pennsylvania, a CISSP Master's Certificate from Villanova and a BS in Mechanical Engineering from Penn State. Chris is author of the Big Data strategy book, "Data Crush," which was recently nominated as International Book of the Year for 2014, by GetAbstract. Chris is also contributing editor and columnist for European Business Review magazine.

on ‎09-18-2013 07:14 AM

Thanks, Chris. 

You're insight is refreshing. I agree completely about the pace of change and and monetezation of new platform design. A true shift in how we create, store, and use data and turn this into useful information is paramount if we want to  monetize this information. 

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