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Big Data ROI will take time, clear goals and talent

Brian Eastwood | July 23, 2013
The big data market is expected, by one estimate, to grow more than 30 percent annually until the end of the decade. But more than half of big data projects fail--and even those that do succeed can fall apart if the findings aren't applied to operational efficiencies. Ron Bodkin, CEO of Think Big Analytics, offers advice to help you prevent your business from becoming just another statistic.

The second is healthcare, where "pockets of innovation" in wellness, genomic research and wearable tech are poised to make data processing a core part of the way that teams of physicians treat patients. The "engine of sequencing," Bodkin says, "is going to require a radical shift."

There's lots of great wearable tech, but the challenge is integrating data from disparate devices and "trying to create a more blended picture" of a person's health, Bodkin says. As if that isn't tough enough, the next step is taking this (often unstructured) heart rate, diet, exercise, sleep pattern or geolocation data and painting a larger picture about a person's overall health.

Healthcare IT's struggles with interoperability and integration will make this a tall task, but the capability to provide individualized wellness recommendations-and to do it far more often than a patient's annual physical-will clearly demonstrate the value of healthcare big data, Bodkin says. That, in turn, will encourage others to opt in to data collection initiatives.

Whats Next for Big Data?
The next steps for big data projects will involve a move from simply storing data to connecting it with the business, Bodkin says. This means predictive analytics, automated business decisions and, as the Tata survey respondents also say, using data as an asset to create newer, better product offerings.

This, in turn, will drive customer engagement, thanks to a more consistent experience across channels; customers will appreciate a company's 360-degree view of their online, mobile and brick-and-mortar activity as much as the company does, Bodkin suggests. Making this work will require an agile approach that makes data available to the right power users and data scientists, he adds.

As big data technology matures over the next five years, the need to integrate largely single-service big data "point applications" in order to boost business value will raise the bar for business analysts. They'll need a greater level of mathematical sophistication than is currently expected, Bodkin says. Fortunately, he adds, this sort of knowledge should become increasingly common-just as basic computers skills, once a major differentiator among employees, are now expected.

 

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