Commercial data mining : processing, analysis and modeling for predictive analytics projects /
Nettleton, David, author.
Commercial data mining : processing, analysis and modeling for predictive analytics projects / by David Nettleton 1963-. - Amsterdam : Elsevier, c2014. - xi, 288 pages ; 23 cm
Includes bibliographical references and index.
1. Introduction 2. Business objectives 3. Incorporating various sources of data and information 4. Data representation 5. Data quality 6. Selection of variables and factor derivation 7. Data sampling and partitioning 8. Data Analysis 9. Data modeling 10. Deployment systems : from query reporting to EIS and expert systems 11. Text analysis 12. Data mining from relationally structured data, marts and warehouses 13. CRM -- Customer Relationship Management and analysis 14. Analysis of data on the Internet I -- website analysis and internet search (online chapter) 15. Analysis of data on the Internet II -- search experience analysis (online chapter) 16. Analysis of data on the Internet III -- online social network analysis (online chapter) 17. Analysis of data on the Internet IV -- search trend analysis over time (online chapter) 18. Data privacy and privacy-preserving data publishing 19. Creating an environment for commercial data analysis 20. Summary. Appendix : Case Studies.
Helps you learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. This book 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.
In English text.
9780124166028
Management.
Data Mining.
Management--Data processing.
Management --Mathematical models.
CIR HD 30.25 / N48 2014
Commercial data mining : processing, analysis and modeling for predictive analytics projects / by David Nettleton 1963-. - Amsterdam : Elsevier, c2014. - xi, 288 pages ; 23 cm
Includes bibliographical references and index.
1. Introduction 2. Business objectives 3. Incorporating various sources of data and information 4. Data representation 5. Data quality 6. Selection of variables and factor derivation 7. Data sampling and partitioning 8. Data Analysis 9. Data modeling 10. Deployment systems : from query reporting to EIS and expert systems 11. Text analysis 12. Data mining from relationally structured data, marts and warehouses 13. CRM -- Customer Relationship Management and analysis 14. Analysis of data on the Internet I -- website analysis and internet search (online chapter) 15. Analysis of data on the Internet II -- search experience analysis (online chapter) 16. Analysis of data on the Internet III -- online social network analysis (online chapter) 17. Analysis of data on the Internet IV -- search trend analysis over time (online chapter) 18. Data privacy and privacy-preserving data publishing 19. Creating an environment for commercial data analysis 20. Summary. Appendix : Case Studies.
Helps you learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. This book 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.
In English text.
9780124166028
Management.
Data Mining.
Management--Data processing.
Management --Mathematical models.
CIR HD 30.25 / N48 2014