Nettleton, David, 1963-
Commercial data mining : processing, analysis and modeling for predictive analytics projects / David Nettleton. - Amsterdam : Elsevier, 2014. - xi, 288 p. : ill. ; 23 cm.
Machine generated contents note: 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 .
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.
9780124166028
2013045341
Data mining.
Management--Mathematical models.
Management--Data processing.
658/.056312
Commercial data mining : processing, analysis and modeling for predictive analytics projects / David Nettleton. - Amsterdam : Elsevier, 2014. - xi, 288 p. : ill. ; 23 cm.
Machine generated contents note: 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 .
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.
9780124166028
2013045341
Data mining.
Management--Mathematical models.
Management--Data processing.
658/.056312