Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

by Eric Siegel

But the point of predictive analytics is not the relative size or unruliness of your data, but what you do with it. I have found that “big data often equals small math,” and many big data practitioners are content just to use their data to create some appealing visual analytics. That’s not nearly as valuable as creating a predictive model.

Yesterday is history, tomorrow is a mystery, but today is a gift. That’s why we call it the present

In God we trust. All others must bring data. —William Edwards Deming

As data piles up, we have ourselves a genuine gold rush. But data isn’t the gold. I repeat, data in its raw form is boring crud. The gold is

what’s discovered therein.

An economist is an expert who will know tomorrow why the things he predicted yesterday didn’t happen. —Earl Wilson

Predictive analytics (PA)—Technology that learns from experience (data) to predict the future behavior of individuals in order to drive better decisions

In this way, PA is a completely different animal from forecasting. Forecasting makes aggregate predictions on a macroscopic level. How will the economy fare? Which presidential candidate will win more votes in Ohio? Whereas forecasting estimates the total number of ice cream cones to be purchased next month in Nebraska, predictive technology tells you which individual Nebraskans are most likely to be seen with cone in hand.

The powerhouse organizations of the Internet era, which include Google and Amazon . . . have business models that hinge on predictive models based on machine learning

Why does your nose run, and your feet smell? —George Carlin