With all the excitement about the transformative potential of big data, one might expect that IT departments would be in the vanguard celebrating what it can deliver. But several recent articles indicate otherwise. For instance, in a post on InfoWorld’s Modernizing IT blog, Eric Knorr notes that the big data trend has been met by serious pushback in many IT departments:
“The testy version goes something like this: ‘Enough already. I have plenty of SQL data stores with lots of data, and I have all the business intelligence tools my business needs. So exactly what are you taking about?’"
While it may seem everyone is now familiar with the insight mining big data can provide, Knorr fears that, in many cases, the “value proposition is lost on conventional IT folks.” Because of this, he believes, an increasing portion of IT spend is slipping from the hands of CIOs to CMOs and lines-of-business managers.
In an interview with Knorr, Rod Smith, vice president of emerging Internet technologies at IBM, gives an example of IT’s resistance to big data. A large financial customer with 150,000 partners wanted to monitor Twitter for information about potential new partners. For example, if a new restaurant tweeted that it received an award, it might be sent a congratulatory message as a means of beginning a dialogue—and potentially a new customer relationship—about a loan or credit card. The reaction from IT was less than enthusiastic, due to their resistance of seeing Twitter as an application with real value.
“It's hard to convince the IT guys they're going to do something where, outside, you can get to the Twitter data or the Facebook data,” says Smith. “And it's fleeting. It might be useful for a particular campaign you're going to do or the launch of a product, but then it might be disposable at that point. So that makes it really tough for the IT guys to say, yeah, we're going to spend with you here, because we know that we'll build it and you'll use it [and it] will have that value over and over again. They can't touch it or feel it the same way anymore.”
Data scientist Olly Downs makes a similar point in a
column on ZDNet. Among the issues he cites as potentially tripping up businesses looking to leverage big data: What data to collect? “The challenge you often see is the data is collected and persistently stored, frequently for the purpose of disaster recovery,” he says. “But that kind of long term or expanded storage perpetuates the same schema that exists live, rather than perpetuating data in a more native form that you could go back to and then change how you subsequently process it and bring it live. It burns in whatever the first thinking was about how that data should be used.”
If IT is to get on board with the big data revolution, it is not first thinking, but new, flexible thinking that must come to the fore, in terms of how data is gathered, maintained, and thought about.
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