Understanding the Predictive Analytics Lifecycle

PRAISE FOR UNDERSTANDING THE PREDICTIVE ANALYTICS LIFECYCLE 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 todays 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. Als 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. Als 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 usthere 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

Foreword Preface Acknowledgments Chapter 1 Problem Identification and Definition Importance of Clear Business Objectives Office Politics Note Chapter 2 Design and Build The Managing Phase The Planning Phase The Delivery Phase Notes Chapter 3 Data Acquisition Data: the Fuel for Analytics A Data Scientist′s Job Notes Chapter 4 Exploration and Reporting Visualization Cloud Reporting Chapter 5 Modeling Churn Model Risk Scoring Model Notes Chapter 6 Actionable Analytics Digital Asset Management Social Media Chapter 7 Feedback What the Different Software Components Should Do Note Conclusion Appendix: Useful Questions Bibliography About the Author Index

ALBERTO CORDOBA is Director of the SAS Center of Excellence at Truven Health Analytics (formerly the Healthcare Business of Thomson Reuters) where he leads a team of highly–skilled SAS experts. In addition, he provides a leadership role and direct project support for client–sponsored research studies. He is a former Vice President of Business Intelligence and Predictive Analytics at Qualex Consulting Services.