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049 _aMAIN
100 1 _aCordoba, Alberto,
_d1958-
245 1 0 _aUnderstanding the predictive analytics lifecycle /
_cAlberto Cordoba.
264 1 _aHoboken, New Jersey :
_bWiley,
_c2014.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
520 _a"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"--
_cProvided by publisher
520 _a"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"--
_cProvided by publisher
504 _aIncludes bibliographical references and index.
500 _aMachine 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.
588 0 _aPrint version record and CIP data provided by publisher.
505 0 _aProblem identification and definition -- Design and build -- Data acquisition -- Exploration and reporting -- Modeling -- Actionable analytics -- Feedback.
590 _aJohn Wiley and Sons
_bWiley Online Library: Complete oBooks
650 0 _aDecision making
_xStatistical methods.
650 0 _aForecasting
_xMathematical models.
650 0 _aBusiness planning.
650 6 _aPrise de d�ecision
_xM�ethodes statistiques.
650 7 _aBUSINESS & ECONOMICS
_xDecision-Making & Problem Solving.
_2bisacsh
650 7 _aBusiness planning
_2fast
650 7 _aDecision making
_xStatistical methods
_2fast
650 7 _aForecasting
_xMathematical models
_2fast
758 _ihas work:
_aUnderstanding the predictive analytics life cycle (Text)
_1https://id.oclc.org/worldcat/entity/E39PCGX3CW4fhCjVFMrV4drJfy
_4https://id.oclc.org/worldcat/ontology/hasWork
776 0 8 _iPrint version:
_aCordoba, Alberto, 1958-
_tUnderstanding the predictive analytics lifecycle.
_dHoboken, New Jersey : Wiley, 2014
_z9781118867105
_w(DLC) 2014013347
856 4 0 _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781118936740
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