Gigabits of I/O and the ability to work with data in business analytics sandboxes outside of production environments, power these thought-exercises in what Barth calls a kind of "agile analytics" approach to asking questions and solving problems.
Big data analytics not ready for prime time
While all of this is promising and exciting for business users-if they even know about it, which they don't- hooking big data analytics into a natural language processing engine and a Siri-like Q&A interface is some ways off. Hadoop, while powerful, is still by all accounts a "primitive" tool for tackling massive data sets.
Think very carefully about the usefulness of these insights, too. Are 100 million opinions really worth more than 100,000, Barth asks-or even a highly qualified and influential 1,000?
"There's a lot of repetition out there," Barth says, and "you still need really smart analysts" if you want your analyses done right. Fortunately, he adds, big data gives them "very powerful tools" to do so.
Allen Bernard is a Columbus, Ohio-based writer. He has covered IT management and the integration of technology into the enterprise since 2000. You can reach Bernard via email or follow him on Twitter @allen_bernard1. Follow everything from CIO.com on Twitter @CIOonline, on Facebook, and on Google +.
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