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Early adopters offer insight on data management, visualization, and co-locating data and apps in the cloud.

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It’s time for a Big Data reality check. All of the hype about the profound value and benefits of the ability of new databases, servers, networks and other ingredients to rapidly process and present massive amounts of data in the Big Data stew has risen to the peak of expectations made famous by the Gartner hype cycle. After conducting a variety of surveys about the reality of Big Data implementations this year, and asking leading consultants and vendors about what they and their clients have learned, it’s time to just slightly deflate the balloon.

While it is too early to declare the arrival of the next phase of the hype cycle—the inevitable trough of disillusionment—early adopters have learned lessons that should be shared with the rest of us. Here are nine Big Data lessons learned that I’ve collected:

1. Focus on data management. The IT department, specifically data architects, need to determine where the data and apps will reside. In one on-premise system or together in a cloud implementation? The traditional Business Intelligence era approach of 10 years ago—trying to have everything in one data warehouse—frequently failed in the wake of numerous data marts developed by maverick departments like finance. Thomas Davenport, co-author of the best-selling book Competing on Analytics and the upcoming Big Data at Work, warns that “while it is good to have options, multiple Big Data implementations leads to a more complex set of IT management decisions.”

Michael Driscoll, CEO of Metamarkets and a longtime observer of the analytics scene, says he’s seen too many large companies attempt to put all of the data—and the processors—in one place. He warns against pursuing a “one- platform” solution, foisted on the organization by the CIO. “Unified data platforms are a false promise of hope,” he contends. They are too big, too complex and will inevitably frustrate one or more departments or units. “A federation of services approach is best,” he explains. In these arrangements, marketing and finance and other departments can each have their own Big Data implementation.

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Blog Publisher / Head of Data Science Search

Founder & Head of Data Science Search at Starbridge Partners, LLC.