Book Description

Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you’ll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling.

Commercial Data Mining includes case studies and practical examples from Nettleton’s more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book.

• Illustrates cost-benefit evaluation of potential projects
• Includes vendor-agnostic advice on what to look for in off-the-shelf solutions as well as tips on building your own data mining tools
• Approachable reference can be read from cover to cover by readers of all experience levels
• Includes practical examples and case studies as well as actionable business insights from author’s own experience

Table of Contents
Chapter 1. Introduction
Chapter 2. Business Objectives
Chapter 3. Data Quality
Chapter 4. Data Representation
Chapter 5. Possible Sources of Data and Information
Chapter 6. Selection of variables and factors
Chapter 7. Data Sampling
Chapter 8. Data Analysis
Chapter 9. Modeling
Chapter 10. The Data Mart – structured data warehouse
Chapter 11. Querying, Report Generation and Executive Information Systems
Chapter 12. Analytical CRM – Customer Relationship Analysis
Chapter 13. Website analysis and Internet search
Chapter 14. Online social network analysis
Chapter 15. Web search trend analysis
Chapter 16. Creating your own environment for commercial data analysis
Chapter 17. Summary

Book Details

• Paperback: 304 pages
• Publisher: Morgan Kaufmann (February 2014)
• Language: English
• ISBN-10: 0124166024
• ISBN-13: 978-0124166028

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