Profit drive business analytics : a practitioner's guide to transforming big data into added value

Cover -- Title Page -- Copyright -- Contents -- Foreword -- Acknowledgments -- Chapter 1: A Value-Centric Perspective Towards Analytics -- Introduction -- Business Analytics -- Profit-Driven Business Analytics -- Analytics Process Model -- Analytical Model Evaluation -- Analytics Team -- Profiles -- Data Scientists -- Conclusion -- Review Questions -- Multiple Choice Questions -- Open Questions -- References -- Chapter 2: Analytical Techniques -- Introduction -- Data Preprocessing -- Denormalizing Data for Analysis -- Sampling -- Exploratory Analysis -- Missing Values -- Outlier Detection and Handling -- Principal Component Analysis -- Types of Analytics -- Predictive Analytics -- Introduction -- Linear Regression -- Logistic Regression -- Decision Trees -- Neural Networks -- Ensemble Methods -- Bagging -- Boosting -- Random Forests -- Evaluating Ensemble Methods -- Evaluating Predictive Models -- Splitting Up the Dataset -- Performance Measures for Classification Models -- Performance Measures for Regression Models -- Other Performance Measures for Predictive Analytical Models -- Descriptive Analytics -- Introduction -- Association Rules -- Sequence Rules -- Clustering -- Survival Analysis -- Introduction -- Survival Analysis Measurements -- Kaplan Meier Analysis -- Parametric Survival Analysis -- Proportional Hazards Regression -- Extensions of Survival Analysis Models -- Evaluating Survival Analysis Models -- Social Network Analytics -- Introduction -- Social Network Definitions -- Social Network Metrics -- Social Network Learning -- Relational Neighbor Classifier -- Probabilistic Relational Neighbor Classifier -- Relational Logistic Regression -- Collective Inferencing -- Conclusion -- Review Questions -- Multiple Choice Questions -- Open Questions -- Notes -- References -- Chapter 3: Business Applications -- Introduction.