Data Smart: Using Data Science to Transform Information into Insight - Softcover

Foreman, John W.

Softcover

ISBN 10: 111866146X ISBN 13: 9781118661468

Publisher: Wiley, 2013

Synopsis

Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.

But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.

Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet.

About this title

About the Author

John W. Foreman is Chief Data Scientist for MailChimp.com, where he leads a data science product development effort called the Email Genome Project. As an analytics consultant, John has created data science solutions for The Coca-Cola Company, Royal Caribbean International, Intercontinental Hotels Group, Dell, the Department of Defense, the IRS, and the FBI.

From the Back Cover

"Data Smart makes modern statistic methods and algorithms understandable and easy to implement. Slogging through textbooks and academic papers is no longer required!"
―Patrick Crosby, Founder of StatHat & first CTO at OkCupid

"When Mr. Foreman interviewed for a job at my company, he arrived dressed in a 'Kentucky Colonel' kind of suit and spoke about nonsensical things like barbecue, lasers, and orange juice pulp. Then, he explained how to de-mystify and solve just about any complex 'big data' problem in our company with simple spreadsheets. No server clusters, mainframes, or Hadoop-a-ma-jigs. Just Excel. I hired him on the spot. After reading this book, you too will learn how to use math and basic spreadsheet formulas to improve your business or, at the very least, how to trick senior executives into hiring you as their data scientist."
―Ben Chestnut, Founder & CEO of MailChimp

"You need a John Foreman on your analytics team. But if you can't have John, then reading this book is the next best thing."
―Patrick Lennon, Director of Analytics, The Coca-Cola Company

Most people are approaching data science all wrong. Here's how to do it right.

Not to disillusion you, but data scientists are not mystical practitioners of magical arts. Data science is something you can do. Really. This book shows you the significant data science techniques, how they work, how to use them, and how they benefit your business, large or small. It's not about coding or database technologies. It's about turning raw data into insight you can act upon, and doing it as quickly and painlessly as possible.

Roll up your sleeves and let's get going.

Relax ― it's just a spreadsheet

Visit the companion website at www.wiley.com/go/datasmart to download spreadsheets for each chapter, and follow them as you learn about:

• Artificial intelligence using the general linear model, ensemble methods, and naive Bayes
• Clustering via k-means, spherical k-means, and graph modularity
• Mathematical optimization, including non-linear programming and genetic algorithms
• Working with time series data and forecasting with exponential smoothing
• Using Monte Carlo simulation to quantify and address risk
• Detecting outliers in single or multiple dimensions
• Exploring the data-science-focused R language

From the Inside Flap

"Data Smart makes modern statistic methods and algorithms understandable and easy to implement. Slogging through textbooks and academic papers is no longer required!"
—Patrick Crosby, Founder of StatHat & first CTO at OkCupid

"When Mr. Foreman interviewed for a job at my company, he arrived dressed in a 'Kentucky Colonel' kind of suit and spoke about nonsensical things like barbecue, lasers, and orange juice pulp. Then, he explained how to de-mystify and solve just about any complex 'big data' problem in our company with simple spreadsheets. No server clusters, mainframes, or Hadoop-a-ma-jigs. Just Excel. I hired him on the spot. After reading this book, you too will learn how to use math and basic spreadsheet formulas to improve your business or, at the very least, how to trick senior executives into hiring you as their data scientist."
—Ben Chestnut, Founder & CEO of MailChimp

"You need a John Foreman on your analytics team. But if you can't have John, then reading this book is the next best thing."
—Patrick Lennon, Director of Analytics, The Coca-Cola Company

Most people are approaching data science all wrong. Here's how to do it right.

Not to disillusion you, but data scientists are not mystical practitioners of magical arts. Data science is something you can do. Really. This book shows you the significant data science techniques, how they work, how to use them, and how they benefit your business, large or small. It's not about coding or database technologies. It's about turning raw data into insight you can act upon, and doing it as quickly and painlessly as possible.

Roll up your sleeves and let's get going.

Relax — it's just a spreadsheet

Visit the companion website at www.wiley.com/go/datasmart to download spreadsheets for each chapter, and follow them as you learn about:

• Artificial intelligence using the general linear model, ensemble methods, and naive Bayes
• Clustering via k-means, spherical k-means, and graph modularity
• Mathematical optimization, including non-linear programming and genetic algorithms
• Working with time series data and forecasting with exponential smoothing
• Using Monte Carlo simulation to quantify and address risk
• Detecting outliers in single or multiple dimensions
• Exploring the data-science-focused R language

Edition details

• Publisher: Wiley
• Publication date: 2013
• Language: English
• ISBN 10: 111866146X
• ISBN 13: 9781118661468
• Binding: Paperback
• Edition number: 1
• Number of pages: 432