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Does Big Data Need A 'LinkedIn For Analytics'?

A social media approach to analytics could help enterprises get more value from their big data systems, says Teradata exec.

For many enterprises, big data analytics may seem more like a collection of science experiments rather than a refined discipline that delivers tangible insights. And organizations experimenting with Hadoop and other big data tools may also find their tried-and-true data-management methods aren't producing the results they had hoped for.

The solution? Adding social media collaboration and crowdsourcing to analytics, or so says Oliver Ratzesberger, senior VP of software at Teradata and formerly analytics head at eBay and Sears. Ratzesberger is writing a nonfiction book, tentatively titled The Sentient Enterprise, in collaboration with Northwestern's Kellogg School of Management professor Mohan Sawhney. The book, slated for publication next year, will examine the role that crowdsourcing might play in the future of analytics.

[It's Time to Put Data Mastery in the Driver's Seat]

It's a social approach to big data analysis, or "LinkedIn for Analytics," the authors say.

Ratzesberger came up with the concept in 2008.

"We started realizing that when you bring more and more people together to work on analytics in a company, the traditional concepts of metadata and documentation -- and 'go ask that person for insights' -- start to break," Ratzesberger told InformationWeek in a phone interview.

For instance, when a company grows ever larger, manages faster and faster data streams, and has 100 or even 1,000 or more analysts, the old ways don't always work.

Read the full story on InformationWeek.

Jeff Bertolucci is a technology journalist in Los Angeles who writes mostly for Kiplinger's Personal Finance, The Saturday Evening Post, and InformationWeek. View Full Bio

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