Data analytics isn’t a magic wand that makes accurate predictions

Predictive modelling is all the rage these days. However, end users and data scientists have very different ideas about what predictive models truly are. With analytics becoming the buzz word and machine learning gaining widespread recognition, there is a tendency to view it as a magic wand, a panacea for all the analytics problems that a spiteful life throws at us. Data scientists are often asked about how to make their predictive models more accurate and whether newer algorithms can help improve the quality of their models. The answer to that question, as to most complex questions is – it depends. There really is no one size fits all where the accuracy of predictive models is concerned. Engineering problems, which are fairly well defined, require accuracies as high as 99%…


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