Оглавление
Baesens Bart. Profit Driven Business Analytics
Wiley & SAS Business Series
Foreword
Acknowledgments
CHAPTER 1. A Value-Centric Perspective Towards Analytics
INTRODUCTION
PROFIT-DRIVEN BUSINESS ANALYTICS
ANALYTICS PROCESS MODEL
ANALYTICAL MODEL EVALUATION
ANALYTICS TEAM
CONCLUSION
REVIEW QUESTIONS
REFERENCES
CHAPTER 2. Analytical Techniques
INTRODUCTION
DATA PREPROCESSING
TYPES OF ANALYTICS
PREDICTIVE ANALYTICS
ENSEMBLE METHODS
EVALUATING PREDICTIVE MODELS
DESCRIPTIVE ANALYTICS
SURVIVAL ANALYSIS
SOCIAL NETWORK ANALYTICS
CONCLUSION
REVIEW QUESTIONS
REFERENCES
CHAPTER 3. Business Applications
INTRODUCTION
MARKETING ANALYTICS
FRAUD ANALYTICS
CREDIT RISK ANALYTICS
HR ANALYTICS
CONCLUSION
REVIEW QUESTIONS
REFERENCES
CHAPTER 4. Uplift Modeling
INTRODUCTION
EXPERIMENTAL DESIGN, DATA COLLECTION, AND DATA PREPROCESSING
UPLIFT MODELING METHODS
EVALUATION OF UPLIFT MODELS
PRACTICAL GUIDELINES
CONCLUSION
REVIEW QUESTIONS
REFERENCES
CHAPTER 5. Profit-Driven Analytical Techniques
INTRODUCTION
PROFIT-DRIVEN PREDICTIVE ANALYTICS
COST-SENSITIVE CLASSIFICATION
COST-SENSITIVE REGRESSION
COST-SENSITIVE LEARNING FOR REGRESSION
PROFIT-DRIVEN DESCRIPTIVE ANALYTICS
CONCLUSION
REVIEW QUESTIONS
REFERENCES
CHAPTER 6. Profit-Driven Model Evaluation and Implementation
INTRODUCTION
PROFIT-DRIVEN EVALUATION OF CLASSIFICATION MODELS
PROFIT-DRIVEN EVALUATION OF REGRESSION MODELS
CONCLUSION
REVIEW QUESTIONS
REFERENCES
CHAPTER 7. Economic Impact
INTRODUCTION
ECONOMIC VALUE OF BIG DATA AND ANALYTICS
KEY ECONOMIC CONSIDERATIONS
IMPROVING THE ROI OF BIG DATA AND ANALYTICS
CONCLUSION
REVIEW QUESTIONS
REFERENCES
About the Authors
WILEY END USER LICENSE AGREEMENT
Отрывок из книги
In today's corporate world, strategic priorities tend to center on customer and shareholder value. One of the consequences is that analytics often focuses too much on complex technologies and statistics rather than long-term value creation. With their book Profit-Driven Business Analytics, Verbeke, Bravo, and Baesens pertinently bring forward a much-needed shift of focus that consists of turning analytics into a mature, value-adding technology. It further builds on the extensive research and industry experience of the author team, making it a must-read for anyone using analytics to create value and gain sustainable strategic leverage. This is even more true as we enter a new era of sustainable value creation in which the pursuit of long-term value has to be driven by sustainably strong organizations. The role of corporate employers is evolving as civic involvement and social contribution grow to be key strategic pillars.
We are grateful to the active and lively business analytics community for providing various user fora, blogs, online lectures, and tutorials, which proved very helpful.
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A number of key characteristics of successful analytical models are defined and explained in Table 1.7. These broadly defined evaluation criteria may or may not apply, depending on the exact application setting, and will have to be further specified in practice.
Table 1.7 Key Characteristics of Successful Business Analytics Models
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