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Profit Driven Business Analytics

Book Description

Maximize profit and optimize decisions with advanced business analytics

Profit-Driven Business Analytics provides actionable guidance on optimizing the use of data to add value and drive better business. Combining theoretical and technical insights into daily operations and long-term strategy, this book acts as a development manual for practitioners seeking to conceive, develop, and manage advanced analytical models. Detailed discussion delves into the wide range of analytical approaches and modeling techniques that can help maximize business payoff, and the author team draws upon their recent research to share deep insight about optimal strategy. Real-life case studies and examples illustrate these techniques at work, and provide clear guidance for implementation in your own organization. From step-by-step instruction on data handling, to analytical fine-tuning, to evaluating results, this guide provides invaluable guidance for practitioners seeking to reap the advantages of true business analytics.

Despite widespread discussion surrounding the value of data in decision making, few businesses have adopted advanced analytic techniques in any meaningful way. This book shows you how to delve deeper into the data and discover what it can do for your business.

  • Reinforce basic analytics to maximize profits
  • Adopt the tools and techniques of successful integration
  • Implement more advanced analytics with a value-centric approach
  • Fine-tune analytical information to optimize business decisions

Both data stored and streamed has been increasing at an exponential rate, and failing to use it to the fullest advantage equates to leaving money on the table. From bolstering current efforts to implementing a full-scale analytics initiative, the vast majority of businesses will see greater profit by applying advanced methods. Profit-Driven Business Analytics provides a practical guidebook and reference for adopting real business analytics techniques.

Table of Contents

  1. Cover
  2. Wiley & SAS Business Series
  3. Title Page
  4. Foreword
  5. Acknowledgments
  6. CHAPTER 1: A Value-Centric Perspective Towards Analytics
    1. INTRODUCTION
    2. PROFIT-DRIVEN BUSINESS ANALYTICS
    3. ANALYTICS PROCESS MODEL
    4. ANALYTICAL MODEL EVALUATION
    5. ANALYTICS TEAM
    6. CONCLUSION
    7. REVIEW QUESTIONS
    8. REFERENCES
  7. CHAPTER 2: Analytical Techniques
    1. INTRODUCTION
    2. DATA PREPROCESSING
    3. TYPES OF ANALYTICS
    4. PREDICTIVE ANALYTICS
    5. ENSEMBLE METHODS
    6. EVALUATING PREDICTIVE MODELS
    7. DESCRIPTIVE ANALYTICS
    8. SURVIVAL ANALYSIS
    9. SOCIAL NETWORK ANALYTICS
    10. CONCLUSION
    11. REVIEW QUESTIONS
    12. NOTES
    13. REFERENCES
  8. CHAPTER 3: Business Applications
    1. INTRODUCTION
    2. MARKETING ANALYTICS
    3. FRAUD ANALYTICS
    4. CREDIT RISK ANALYTICS
    5. HR ANALYTICS
    6. CONCLUSION
    7. REVIEW QUESTIONS
    8. NOTE
    9. REFERENCES
  9. CHAPTER 4: Uplift Modeling
    1. INTRODUCTION
    2. EXPERIMENTAL DESIGN, DATA COLLECTION, AND DATA PREPROCESSING
    3. UPLIFT MODELING METHODS
    4. EVALUATION OF UPLIFT MODELS
    5. PRACTICAL GUIDELINES
    6. CONCLUSION
    7. REVIEW QUESTIONS
    8. NOTE
    9. REFERENCES
  10. CHAPTER 5: Profit-Driven Analytical Techniques
    1. INTRODUCTION
    2. PROFIT-DRIVEN PREDICTIVE ANALYTICS
    3. COST-SENSITIVE CLASSIFICATION
    4. COST-SENSITIVE REGRESSION
    5. COST-SENSITIVE LEARNING FOR REGRESSION
    6. PROFIT-DRIVEN DESCRIPTIVE ANALYTICS
    7. CONCLUSION
    8. REVIEW QUESTIONS
    9. NOTES
    10. REFERENCES
  11. CHAPTER 6: Profit-Driven Model Evaluation and Implementation
    1. INTRODUCTION
    2. PROFIT-DRIVEN EVALUATION OF CLASSIFICATION MODELS
    3. PROFIT-DRIVEN EVALUATION OF REGRESSION MODELS
    4. CONCLUSION
    5. REVIEW QUESTIONS
    6. NOTES
    7. REFERENCES
  12. CHAPTER 7: Economic Impact
    1. INTRODUCTION
    2. ECONOMIC VALUE OF BIG DATA AND ANALYTICS
    3. KEY ECONOMIC CONSIDERATIONS
    4. IMPROVING THE ROI OF BIG DATA AND ANALYTICS
    5. CONCLUSION
    6. REVIEW QUESTIONS
    7. NOTES
    8. REFERENCES
  13. About the Authors
  14. Index
  15. End User License Agreement