Predictive Analytics is one of the hottest careers on the tech scene these days and with good reason: data is being collected in ever greater amounts, and this data, it turns out, is useful for improving decisions and efficiencies of organizations. No surprises here for this audience. My last article for the PA Times argued that we don’t need to know details of the mathematics in order to be good predictive modelers. However, we predictive modelers must become better at understanding how the models are going to be used and what the predictions mean for the business;
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