Nonfiction Book Award Status: Gold Award
“The Freakonomics of big data.” —Stein Kretsinger, founding executive of Advertising.com; former lead analyst at Capital One
An introduction for everyone. This book is easily understood by all readers. Rather than a “how to” for hands-on techies, the book entices lay-readers and experts alike by covering new case studies and the latest state-of-the-art techniques.
You have been predicted – by companies, governments, law enforcement, hospitals and universities. Their computers say, “I knew you were going to do that!” These institutions are seizing upon the power to predict whether you’re going to click, buy, lie, or die.
Why? For good reason: Predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime fighting, and boosts sales.
How? Prediction is powered by the world’s most potent, booming unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn.
Predictive analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future — lifting a bit of the fog off our hazy view of tomorrow — means pay dirt.
In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction:
- What type of mortgage risk Chase Bank predicted before the recession.
- Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves.
- Why early retirement decreases life expectancy and vegetarians miss fewer flights.
- Five reasons why organizations predict death, including one health insurance company.
- How U.S. Bank, European wireless carrier Telenor, and Obama’s 2012 campaign calculated the way to most strongly influence each individual.
- How IBM’s Watson computer used predictive modeling to answer questions and beat the human champs on TV’s Jeopardy!.
- How companies ascertain untold, private truths — how Target figures out you’re pregnant and Hewlett-Packard deduces you’re about to quit your job.
- How judges and parole boards rely on crime-predicting computers to 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 cross-industry compendium of 147 mini-case studies in predictive analytics.
A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate.
Predictive analytics transcends human perception. This book’s final chapter answers the riddle:What often happens to you that cannot be witnessed, and that you can’t even be sure has happened afterward — but that can be predicted in advance?
Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics. Buy the book on Amazon.
Eric Siegel, Ph.D., founder of Predictive Analytics World and Text Analytics World, and Executive Editor of the Predictive Analytics Times, makes the how and why of predictive analytics understandable and captivating. In addition to being the author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, Eric is a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field. He has appeared on Bloomberg TV and Radio, Fox News, BNN (Canada), Israel National Radio, Radio National (Australia), The Street, Newsmax TV, and NPR affiliates. Eric and his book have been featured in Businessweek, CBS MoneyWatch, The Financial Times, Forbes, Forrester, Fortune, The Huffington Post, The New York Times, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.
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