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Ten Mistakes to Avoid In Your Big Data Implementation

Ten Mistakes to Avoid in Your Big Data Implementation
TDWI Member Exclusive

February 19, 2013

By Krish Krishnan

Big data is the biggest buzzword in the industry today. Every organization—big or small—is looking into understanding and deploying a big data program. Big data doesn’t just refer to having larger volumes of data. We must consider the source(s) of the data.

One purpose of a big data implementation is to incorporate additional data sets into the current data infrastructure to help the enterprise question anything from the data. Although the possibility of accomplishing this goal seems realistic with the evolution of technology and commoditization of an enterprise’s infrastructure, there are several critical pitfalls to avoid. In this Ten Mistakes to Avoid, we will look at the most common mistakes that occur when implementing a big data program to help you enhance your analytical insights and the decision support processes in your enterprise.

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