Month: April 2013

Big Data, big hype, big danger

A remarkable thing happened in Big Data last week. One of Big Data’s best friends poked fun at one of its icons: the Three V’s.

The well-networked and alert observer Shawn Rogers, vice president of research at Enterprise Management Associates, tweeted his eight V’s: “…Vast, Volumes of Vigorously, Verified, Vexingly Variable Verbose yet Valuable Visualized high Velocity Data.”

He was quick to explain to me that this is no comment on Gartner analyst Doug Laney’s three-V definition. Shawn’s just tired of people getting stuck on V’s.

How strange to be stuck on a definition, but we get stuck all the time trying to define Big Data. Other terms are easier. We’ve always known what visualization is. We seem to agree on “self service BI.” We also know what relational databases are, what ETL is, and all kinds of other established technology. We don’t agree on “business intelligence” or “decision support,” but somehow we don’t dwell on it. We don’t even quibble too heartily with “easy to use,” even though I could argue that we should.

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