Thursday, January 5, 2012

Big analytics or big bubble?

As a practitioner of predictive analytics over the last 8-10 years, it is fascinating to sit back and observe the way the field is gathering attention and importance. Most recently, NPR did a piece on analytics. The NPR pieces were about Gary Loveman who is now the CEO of Caesar Entertainment - it is a podcast and the link is here. I loved this line from the story:

There are three things that can get you fired from Caesars: Stealing, sexual harassment and running an experiment without a control group.

NPR followed up with other couple of pieces  - one was an opener on Big Data and the other was the search for analytic talent that can make sense of this Big Data. What made the second article somewhat quirky was that it profiled DJ Patil, a mathematician who searches and tracks and ultimately recruits these data geniuses using - you guessed it, data!

So did the WSJ, just yesterday. The WSJ talked about two analytics consulting firms: Mu Sigma and Opera Solutions, getting substantial amounts of venture funding (think large 8-digit numbers) to expand in this space.

This is the point where I start to get really worried about big data and the b-word. Is this big data, social media, mega-analytics a rapidly building bubble that is bound to pop in some way and leave more than a few people disappointed? I have no doubts in my mind that the idea is powerful and transformational - the idea being that predictive analytics sitting on top of data can make better business decisions, drive better customer insights and resource efficiencies and improve life for us in a holistic kind of way.

But when big media gets on the bandwagon and the subject goes from being talked in technical journals to being talked by the WSJ and NPR, I begin to smell some frothiness.

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