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10 big myths about Big Data

By Maria Korolov, Network World
January 27, 2014 06:45 AM ET

Page 4 of 4

“I can't look and see what it was 10 minutes ago, or draw a tend line for what it's going to be an hour from now,” says Anthony Jones, chief marketing officer of Philips Healthcare’s Patient Care & Clinical Informatics.

But being able to see the historical data for a patient can be very valuable for a medical practitioner making a decision. “The guys sticking with a core data science team, they're missing a big opportunity,” says Jones.

The problem today is getting all the different devices that generate data to talk to each other even though they weren't designed to do that, and use different platforms, operating systems and programming languages. And then once you do, to get the data in a useful form to doctors and nurses right when they need it.

MYTH 9: Big Data is for big problems

The CIO of a major bank recently gave a talk about Big Data, and was asked about end user self-service.

“And the CIO says, 'I don't believe in that,'” recalls Peters, CEO of Birst.

That's a common attitude, he says, with some executives thinking that Big Data only answers certain types of questions. The attitude can be summed up this way: “The goal of Big Data for us is to solve very few, very high-value problems with a core set of data scientists. We don't want data chaos where normal people have access to this information, because I don't think they need it.”

Peters disagrees with this approach, but says it's common in many industries. “It's a rampant myth inside large insurance companies that business users aren't smart enough to handle it.”

MYTH 10: The Big Data bubble will eventually burst

Hype cycles may come and go, but transformative technological changes stick around. The dot-com crash did not signal the end of the Internet.

Even when the hype dies down, companies will still have Big Data to deal with. In fact, they will have more Big Data to deal with than they ever expected, due to exponential growth – IDC projects that total amount of data collected will double every two years through 2020.

And it's not just that companies are simply collecting more of the stuff that they currently collect. Instead, new types of data are likely to appear, requiring massive amounts of storage.

“We will get to the point where everyone who gets admitted to a hospital, the hospital maps their genome,” says Anthony Jones, chief marketing officer of Philips Healthcare’s Patient Care & Clinical Informatics. “This allows treatment to be customized to the patient. And when you talk about Big Data, that's a massive amount of data. I don't think a lot of CIOs really appreciate how much harder things are going to get.”

By thinking of “Big Data” as just a phase, companies can miss opportunities to capture data elements that could have an impact on their business down the line, says Bryan Hill, CTO of Cadient Group, an interactive marketing agency in King of Prussia, Pa.

“The term 'Big Data' is likely to change, just like cloud computing came up, which is no different than the Web was, or the Internet,” he says. “The term may change, but the spirit of Big Data is here to stay.”

Korolov is a freelance writer. She can be reached at

Read more about software in Network World's Software section.

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