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Book Review: ‘Data Smart’ by John W. Foreman

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New book looks at data science applications

New book looks at data science applications

One of the hot topics for business books these days appears to be about data mining. John W. Foreman has written the latest of many such books. His book, Data Smart Using Data Science to Transform Information into Insight, is a hands-on training exercise.

The introduction goes over why businesses and others are “going about data science all wrong.” He goes on to write that his book will give the reader an “introduction to the practice of data science in a comfortable and conversational way.”

He starts out by giving the reader a workable definition of what data science is, “Data science is the transformation of data using mathematics and statistics into valuable insights, decisions, and products.”

This book is set apart from many of the data mining books because of its hands-on exercises and the way the author uses those exercises to describe certain techniques and practices used in data science. The first chapter provides a primer on using Microsoft Excel because the exercises in the book use the spreadsheet.

There is no doubt that this book is not a book about the theory of data science. It is a technical how-to manual. If the reader is looking for the theories and case studies that so many other books provide, they will be a bit disappointed with this book.

On the other hand, for those that really want to get into the weeds of using data science, this book will be perfect.  The book is filled with technical terms. The author does provide plenty of definitions and examples of how the terms are applied to the field of data science. A short list of topics include:

  • Cluster analysis
  • Nut graphs
  • K-Means
  • Artificial Intelligence
  • Regression
  • Ensemble models
  • Forecasting
  • Outlier Detection

While the book does start out using Excel, the last chapter looks at using a programming language called R. Foreman writes, “After spending the previous nine chapters injecting Excel directly into your veins, I’m now going to tell you to drop it. Well, not for everything, but let’s be honest, Excel is not ideal for all analytics tasks.”

The author uses plenty of graphics and screen shots to help the reader stay connected to the concept and exercise being presented. Foreman does include some case studies. Foreman details the well published story of how the Target retail chain uses an artificial intelligence model to predict when its customers were pregnant and then sending them marketing materials for pregnancy items sold at Target.

If a reader is looking for an applications book on data mining, this is it. And, the step-by-step exercises will please the reader looking for a way to get started using the techniques and the practices associated with data science.

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