Predictive analytics is the trend of the day for businesses looking to get more value from their data. Unleash predictive models on that data, and who knows what interesting -- and telling -- patterns will emerge? These could even be the differentiation between also-ran and competitive juggernaut.
But, as Dean Abbott, internationally recognized data-mining and predictive analytics expert, points out in his new book, Applied Predictive Analytics, "predictive analytics doesn't do anything that any analyst couldn't accomplish with pencil and paper or a spreadsheet if given enough time." That's because the algorithms, he says, "while powerful, have no common sense." Abbott, who is president of Abbot Analytics, wants to make sure the same can't be said of professional data analysts.
In his book, Abbott lays out principles and techniques for applying predictive analytics, some of which he'll share during this A2 Radio episode. Tune in to hear for his advice on how to:
- Prep for predictive modeling
- Match the model to the business objective
- Avoid common mistakes
- Know whether your model is working or not
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