Predictive Analytics Times
Predictive Analytics Times
AI, Machine Learning, and the Basics of Predictive Analytics for Process Management
APQC Chair Carla O’Dell interviews Predictive Analytics Times Executive...
Data Reliability and Analytic Validity for Non-Dummies
There is not much attention paid these days to...
Overview of Mega-PAW Vegas 2018: Summary of Keynotes and More
As both a speaker and a representative of the...
Analytics Assessment: A Blueprint for Effective Analytics Programs
If you are like me, when you first heard...

Industry Books

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
By Siegel, Eric Revised and Updated

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.


Predictive Analytics: Microsoft Excel [Paperback]
By Conrad Carlberg

Predictive Analytics: Microsoft® Excel
Excel predictive analytics for serious data crunchers!

The movie Moneyball made predictive analytics famous: Now you can apply the same techniques to help your business win. You don’t need multimillion-dollar software: All the tools you need are available in Microsoft Excel, and all the knowledge and skills are right here, in this book!


Competing on Analytics: The New Science of Winning
By Thomas H. Davenport, Jeanne G. Harris

You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool.

In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling.

Applied Predictive Modeling
By Max Kuhn, Kjell Johnson

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.