Much of the discussion in the predictive analytics discipline tends to deal with techniques and approaches that will help resolve a given business challenge or problem. In any approach or technique, though, integration of both technical(i.e. mathematics and software) and domain knowledge is critical to the success of any predictive analytics solution. Yet, there is a third element, which is arguably the most significant in being able to develop predictive analytics solutions: DATA. In previous articles, I have talked at length about the data and the importance of the practitioner becoming “intimate” with the data. The discipline of the “data
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