“Data Lake” is one of the current hot topics in Big Data with lots of press and little practical content. A big part of the confusion and controversy arises from the tension between hype and common sense. Proponents promise phenomenal insights and actionable predictions about customer behavior, employee behavior, doctors’ handwritten diagnostic notes and so on. Basically, they claim you dump documents and data into the lake and let the algorithms make sense of it all. Of course, that’s patent nonsense. Unfortunately, the hype obscures some real value in the data lake concept. In this and following posts we’ll see … Read More