Commercial Data Mining: Processing, Analysis and Modeling for Predictive Analytics Projects

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Overview

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 ...

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Commercial Data Mining: Processing, Analysis and Modeling for Predictive Analytics Projects

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More About This Book

Overview

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
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Editorial Reviews

From the Publisher
"The book is laid out nicely to use as a reference and will be helpful to both pros and newbies alike…If you are look for a book that not only can serve as a valuable reference guide for your data mining project, but also offers up practical examples, case studies, and actionable business insights based on the author’s experience, then look no further…"—DataTechnologyToday.com, March 27, 2014
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Product Details

  • ISBN-13: 9780124166028
  • Publisher: Elsevier Science
  • Publication date: 3/1/2014
  • Series: Savvy Manager's Guides Series
  • Pages: 304
  • Sales rank: 1392419
  • Product dimensions: 6.00 (w) x 8.90 (h) x 0.70 (d)

Meet the Author

David F. Nettleton has more than 25 years of experience in IT system development, specializing in databases and data analysis. He has a Bachelor of Science degree in Computer Science, Master of Science degree in Computer Software and Systems Design and a Ph.D. in Artificial Intelligence. He has worked for IBM as a Business Intelligence Consultant, among other companies. In 1995 he founded his own consultancy dedicated to commercial data analysis projects, working in the Banking, Insurance, Media, Industry and Health Sectors. He has published over 40 articles and papers in journals, national and international congresses and magazines, and has given many presentations in conferences and workshops. He is currently a contract researcher at the Universitat Pompeu Fabra, Barcelona, Spain and at the IIIA-CSIC, Spain, specializing in data mining applied to online social networks and data privacy. Dr. Nettleton was born in England and lives in Barcelona, Spain since 1988.

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Table of Contents

1. Introduction 2. Business Objectives 3. Data Quality 4. Data Representation 5. Possible Sources of Data and Information 6. Selection of Variables and Factors 7. Data Sampling 8. Data Analysis 9. Modeling 10. The Data Mart - Structured Data Warehouse 11. Querying, Report Generation and Executive Information Systems 12. Analytical CRM - Customer Relationship Analysis 13. Website Analysis and Internet Search 14. Online Social Network Analysis 15. Web Search Trend Analysis 16. Creating your own Environment for Commercial Data Analysis 17. Summary Appendices, Case Studies

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