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The unvarnished truth about Big Data

Debarati Roy | May 23, 2013
There are plenty who believe that beneath big data’s shiny exterior, companies will find a hollow ring of tin plating. Will big data reveal itself to be just another IT fad?

And when the likes of IBM decide that enterprises are going to buy a product, they back their decision with sizeable marketing budgets and create demand. It's what's gotten a technology concept as complex and niche as big data on the cover of the Harvard Business Review, Forbes, and Businessworld.

Michael Chui, principal, McKinsey Global Institute and co-author of one of the first comprehensive reports on big data, says that since he co-authored his report in 2011, a lot has changed in the way big data is perceived. "A couple of years ago, there were a number of people in the tech community who were talking about big data, but in the intervening time we have seen interest and awareness increase in business and executive communities," he says.

The Bigger They Are...
One of the challenges of being a legend is living up to your reputation. That's a problem big data is already beginning to face thanks to all the hype surrounding it. According to Gartner's 2012 hype cycle for emerging technology, big data has moved into the Peak of Inflated Expectations. "There are several use cases where big data has helped solve various challenges at various organizations, but the hype being built around those cases is too high at the moment. End users are beginning to expect those benefits automatically, which might not turn out to be true in all cases," says Deshpande at Gartner.

One downside to that, as Arun Gupta, CIO, Cipla, points out are that IT leaders have begun to force fit problems to the technology. But because big data solutions aren't solving organic problems, he says, it's probable that big data won't see mainstream enterprise acceptance.

"Most companies I speak to are curious about big data, what with all the hype being built around it. But they have no clue what it means to them," says Gupta. "Various models created by vendors or analyst firms are not based on empirical data but largely on hypothetical, potential use cases. Anecdotal references, too, are primarily from large Internet companies and a few global FMCG experiments," he says.

Even if big data does get past this hurdle, it's going to have to face a number of legacy issues—challenges that have sunk many a business intelligence initiative in the past.

First among these is the cultural change an analytical project like big data will introduce. According to Chui, big data will turn an organization into one giant laboratory and will force companies—that are used to listening to HIPPOs (Highest Paid Person's Opinion)--to change the way they make decisions. "Imagine having to move from experience and instinct to running an organization like a 24x7 laboratory. There is nothing harder than having an organization that is learning to make decisions in a different way," he says.


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