+353-1-416-8900REST OF WORLD
+44-20-3973-8888REST OF WORLD
1-917-300-0470EAST COAST U.S
1-800-526-8630U.S. (TOLL FREE)


Understanding the Predictive Analytics Lifecycle. Wiley and SAS Business Series

  • ID: 2827001
  • Book
  • October 2014
  • Region: Global
  • 240 Pages
  • John Wiley and Sons Ltd
1 of 3


This is a must–read book for businesses that are planning to take advantage of their massive data collections and build predictive models. It shows examples and gives guidance on how to avoid the most common pitfalls to reach a successful outcome.
Carmelina Collado, Directeur des Programmes & Transformation, inwi

I am glad to see that there is a book that shows the entire cycle, the entire evolution, for big data to turn into valuable and actionable information using advanced software analytical tools in today s world!
Clive Pearson, CEO, Qualex Consulting Services

In this book, Al Cordoba has provided a complete picture of the advanced analytics process and how it contributes to business value. Al s years of experience in helping organizations worldwide give this book valuable insight and recommendations that business and IT professionals can heed.
Jeff Babcock, Senior Vice President and General Manager, Kronos

We live in a world where data are more prevalent than ever. Al s book uses plain language and stories as a way to present sophisticated technology subjects like data integration and advanced analytics.
Rob Berman, Vice President of Global Alliances, Teradata

With rapid datafication of everything around us there is tremendous opportunity for enterprises to get new differentiated actionable business value. Advanced analytics is key to delivering such business value. In this book, Al Cordoba has provided a complete 360–degree view of the advanced analytics process and has made it easy to understand through many examples. I would recommend this book to all the executives.
Gokula Mishra, Vice President of Advanced Analytics & Big Data, Oracle; Co–Author of The Oracle Big Data Handbook

Note: Product cover images may vary from those shown
2 of 3

Foreword xi

Preface xiii

Acknowledgments xv

Chapter 1 Problem Identification and Definition 1

Importance of Clear Business Objectives 4

Office Politics 8

Note 13

Chapter 2 Design and Build 15

Managing Phase 16

Planning Phase 18

Delivery Phase 19

Notes 32

Chapter 3 Data Acquisition 33

Data: The Fuel for Analytics 36

A Data Scientist s Job 41

Notes 53

Chapter 4 Exploration and Reporting 55

Visualization 57

Cloud Reporting 61

Chapter 5 Modeling 69

Churn Model 71

Risk Scoring Model 77

Notes 99

Chapter 6 Actionable Analytics 101

Digital Asset Management 104

Social Media 104

Chapter 7 Feedback 129

What the Different Software Components Should Do 132

Note 148

Conclusion 149

Appendix: Useful Questions 155

Bibliography 209

About the Author 211

Index 213

Note: Product cover images may vary from those shown
3 of 3


4 of 3
Alberto Cordoba
Note: Product cover images may vary from those shown