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For some time now, predictive analytics has been hailed as the “next big thing.” A quick Google search for “predictive analytics” shows that everyone from Forbes to The Wall Street Journal and beyond have written about how predictive analytics is going to “transform business” and “turn analytics on its head” and even “make BI obsolete”.
However, despite years of optimism, the analytics market is still dominated by visualization and business intelligence software such as Tableau, Qlik, and Birst. If predictive analytics is the next best thing, why isn’t everyone using it?
Predictive analytics examines data and tells you what it is likely to happen in the future. It promises to give you the power to “predict the future of your business” and to “know what will happen next.” And current technology is capable of making thousands, even millions, of predictions each second. Sounds pretty darn impressive.
But the dirty secret is that much of the automated predictive analytics technology on offer simply isn’t very useful. Why? Knowing what’s going to happen next is nice, but if you don’t know why, you won’t know what to do about it, and it will be of little value.
Consider the simple case of customer churn. With predictive analytics, you will know …
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