Cordoba Understanding the Predictive Analytics Lifecycle

1. Auflage 2014
ISBN: 978-1-118-93893-5
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 240 Seiten, E-Book

Reihe: SAS Institute

A high-level, informal look at the different stages of thepredictive analytics cycle
Understanding the Predictive Analytics Lifecycle coverseach phase of the development of a predictive analytics initiative.Through the use of illuminating case studies across a range ofindustries that include banking, megaresorts, mobile operators,healthcare, manufacturing, and retail, the book successfullyillustrates each phase of the predictive analytics cycle to createa playbook for future projects.
Predictive business analytics involves a wide variety of inputsthat include individuals' skills, technologies, tools, andprocesses. To create a successful analytics program or project togain forward-looking insight into making business decisions andactions, all of these factors must properly align. The book focuseson developing new insights and understanding business performancebased on extensive use of data, statistical and quantitativeanalysis, explanatory and predictive modeling, and fact-basedmanagement as input for human decisions. The book includes:
* An overview of all relevant phases: design, prepare, explore,model, communicate, and measure
* Coverage of the stages of the predictive analytics cycle acrossdifferent industries and countries
* A chapter dedicated to each of the phases of the development ofa predictive initiative
* A comprehensive overview of the entire analytic processlifecycle
If you're an executive looking to understand the predictiveanalytics lifecycle, this is a must-read resource and referenceguide.

Autoren/Hrsg.

Cordoba, Alberto

Inhaltsverzeichnis

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

Über Autor(innen)

ALBERTO CORDOBA is Director of the SAS Center ofExcellence at Truven Health Analytics (formerly the HealthcareBusiness of Thomson Reuters) where he leads a team ofhighly-skilled SAS experts. In addition, he provides a leadershiprole and direct project support for client-sponsored researchstudies. He is a former Vice President of Business Intelligence andPredictive Analytics at Qualex Consulting Services.