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Much of Hadoop adoption thus far has been for use cases such as processing log files, text mining, and storing masses of file data — all very necessary, but largely not exciting. In this presentation, Michael Cutler presents a selection of methodologies, primarily using Mahout, that will enable you to derive real insight into your data (mined in Hadoop) and build a recommendation engine focused on the implicit data collected from your users.