'Big data' prep: 5 things IT should do now

Computerworld - Got your "big data" plan in place? If not, you may want to start thinking about implementing one.

Big data is being hailed -- or hyped, depending on your point of view -- as a key strategic business asset of the future. That means it's only a matter of time before the suits in the corner office want to know IT's thoughts on the matter.

What to tell them? To be sure, handling large amounts of data isn't virgin territory for most IT departments, but beyond the hype, analysts say, big data really is different from the data warehousing, data mining and business intelligence (BI) analysis that have come before it.

Data is being generated with greater velocity and variability than ever before, and, unlike data in the past, most of it is unstructured and raw (sometimes called "gray data").

Blogs, social media networks, machine sensors and location-based data are generating a whole new universe of unstructured data that -- when quickly captured, managed and analyzed -- can help companies uncover facts and patterns they weren't able to recognize in the past.

"We've collected data for a long time, but it was very limited -- we produced a lot of it, but no one was doing much with it," says Paul Gustafson, director of Computer Sciences Corp.'s Leading Edge Forum, Technology Programs. "The data was archived and it was modeled around business processes, not modeled as a broader set of core knowledge for the enterprise. The mantra is this shift from collecting to connecting."

For example, the U.S. healthcare industry could drive efficiencies and increase productivity by effectively harnessing data related to quality of care, success rates and patient history, according to a May report on big data issued by McKinsey Global Institute, which estimated that the industry could generate more than $300 billion in value every year with such bigdata initiatives. The report likewise suggests that big data has the potential to increase an average retailer's operating margin by more than 60%.

IT is standing at the forefront of this data revolution, industry observers say.

"This is an opportunity to walk into the CEO's office and say, 'I can change this business and provide knowledge at your fingertips in a matter of seconds for a price point I couldn't touch five years ago,'" says Eric Williams, CIO at Catalina Marketing.

Williams should know -- Catalina maintains a 2.5-petabyte customer-loyalty database, including data on more than 190 million U.S. grocery shoppers collected by the largest retail chains. This information is, in turn, used to generate coupons at checkout based on purchase history.

To steer organizations into the era of real-time predictive intelligence, Williams and other industry watchers say, tech managers must evolve their enterprise information management architecture and culture to support advanced analytics on data stores that measure in terabytes and petabytes (potentially scaling to exabytes and zettabytes).