Unstructured Data: The Other Side of Analytics

Steve Andriole

Everyone is obsessed with “analytics.”  I cannot keep up with what the technology pundits and consultants are telling me about analytics, no matter how hard I try.  (I just Googled “big data analytics” and got 107,000,000 results in 0.29 seconds.)

If you listen to these people, you will absolutely, positively believe that without huge investments in analytics immediately, your company will at any moment explode in a huge fireball.

“Big data analytics” is already a cult (like so many cults we’ve seen before).  The data Gods are angry, my friends, and they’re pouring data onto us so fast that it’s impossible to avoid being buried alive – or so the pundits and consultants would have us believe.   So we need more servers, data bases, tools and most of all, “data scientists.”

Universities are scrambling to create this expertise, churning out data scientists as quickly as they can.  Students are flocking to these programs because companies pay data scientists really well, and everyone knows it: try finding data scientists at the mall – or anywhere, for that matter. (At Villanova, we offer a new masters program in analytics and it’s already very popular.

“Predictive analytics” is the goal:  of course (!), who wouldn’t want to predict the future? Yes, “analytics” is important, just as digital commerce, location awareness, cloud computing, mobility and digital security are important.  Hopefully, we’ve learned how to ride these technology waves – because there will be others. There are always others.

But there’s another side to the analytics obsession that needs attention because most analytics applications and technologies are focused more on structured than unstructured data.  (Oh, the joys of relational data base management, now largely gone, as old data base managers endlessly pine for the good old days of rows and columns.)

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