Understanding the predictive analytics lifecycle - Cordoba, Alberto, 1958- (Hoboken, New Jersey : Wiley, 2014)
"A high-level, informal look at the different stages of the predictive analytics cycleUnderstanding the Predictive Analytics Lifecycle covers each phase of the development of a predictive analytics initiative. Through the use of illuminating case studies across a range of industries that include banking, megaresorts, mobile operators, healthcare, manufacturing, and retail, the book successfully illustrates each phase of the predictive analytics cycle to create a playbook for future projects. Predictive business analytics involves a wide variety of inputs that include individuals' skills, technologies, tools, and processes. To create a successful analytics program or project to gain forward-looking insight into making business decisions and actions, all of these factors must properly align. The book focuses on developing new insights and understanding business performance based on extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based management 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 across different industries and countries A chapter dedicated to each of the phases of the development of a predictive initiative A comprehensive overview of the entire analytic process lifecycle If you're an executive looking to understand the predictive analytics lifecycle, this is a must-read resource and reference guide"--
"Covers each phase of the development of a predictive analytics initiative. Through the use of case studies across a range of industries that include banking, megaresorts, mobile operators, healthcare, manufacturing, and retail, the book illustrates each phase of the predictive analytics cycle to create a playbook for future projects"--
Problem identification and definition -- Design and build -- Data acquisition -- Exploration and reporting -- Modeling -- Actionable analytics -- Feedback.
Includes bibliographical references and index.
Machine generated contents note: 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.
Print version record and CIP data provided by publisher.
John Wiley and Sons
Keywords: Decision making -- Statistical methods; Forecasting -- Mathematical models; Business planning; x; BUSINESS & ECONOMICS -- Decision-Making & Problem Solving; Business planning; Decision making -- Statistical methods; Forecasting -- Mathematical models