"The Freakonomics of big data."
—Stein Kretsinger, founding executive ofAdvertising.com; former lead analyst at Capital One
This book is easily understood by all readers. Rather than a"how to" for hands-on techies, the book entices lay-readers andexperts alike by covering new case studies and the lateststate-of-the-art techniques.
You have been predicted — by companies, governments, lawenforcement, hospitals, and universities. Their computers say, "Iknew you were going to do that!" These institutions are seizingupon the power to predict whether you're going to click, buy, lie,or die.
Why? For good reason: predicting human behavior combats financialrisk, fortifies healthcare, conquers spam, toughens crime fighting,and boosts sales.
How? Prediction is powered by the world's most potent, boomingunnatural resource: data. Accumulated in large part as theby-product of routine tasks, data is the unsalted, flavorlessresidue deposited en masse as organizations churn away. Surprise!This heap of refuse is a gold mine. Big data embodies anextraordinary wealth of experience from which to learn.
Predictive analytics unleashes the power of data. With thistechnology, the computer literally learns from data how topredict the future behavior of individuals. Perfect prediction isnot possible, but putting odds on the future — lifting a bitof the fog off our hazy view of tomorrow — means paydirt.
In this rich, entertaining primer, former Columbia Universityprofessor and Predictive Analytics World founder Eric Siegelreveals the power and perils of prediction:
- What type of mortgage risk Chase Bank predicted before therecession.
- Predicting which people will drop out of school, cancel asubscription, or get divorced before they are even aware of itthemselves.
- Why early retirement decreases life expectancy and vegetariansmiss fewer flights.
- Five reasons why organizations predict death, including onehealth insurance company.
- How U.S. Bank, European wireless carrier Telenor, and Obama's2012 campaign calculated the way to most strongly influence eachindividual.
- How IBM's Watson computer used predictive modeling toanswer questions and beat the human champs on TV'sJeopardy!
- How companies ascertain untold, private truths — howTarget figures out you're pregnant and Hewlett-Packard deducesyou're about to quit your job.
- How judges and parole boards rely on crime-predicting computersto decide who stays in prison and who goes free.
- What's predicted by the BBC, Citibank, ConEd, Facebook, Ford,Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal,Pfizer, and Wikipedia.
A truly omnipresent science, predictive analytics affectseveryone, every day. Although largely unseen, it drives millions ofdecisions, determining whom to call, mail, investigate,incarcerate, set up on a date, or medicate.
Predictive analytics transcends human perception. This book's finalchapter answers the riddle: What often happens to you thatcannot be witnessed, and that you can't even be sure has happenedafterward — but that can be predicted inadvance?
Whether you are a consumer of it — or consumed by it —get a handle on the power of Predictive Analytics.
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