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Autore: | Nettleton David <1963-> |
Titolo: | Commercial data mining : processing, analysis and modeling for predictive analytics projects / / David Nettleton |
Pubblicazione: | Waltham, MA : , : Morgan Kaufmann, an imprint of Elsevier, , 2014 |
Edizione: | 1st edition |
Descrizione fisica: | 1 online resource (ix, 288 pages) : illustrations (some color) |
Disciplina: | 658/.056312 |
Soggetto topico: | Data mining |
Management - Mathematical models | |
Management - Data processing | |
Note generali: | Description based upon print version of record. |
Nota di bibliografia: | Includes bibliographical references and index. |
Nota di contenuto: | 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. |
Sommario/riassunto: | 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. < |
Titolo autorizzato: | Commercial data mining |
ISBN: | 0-12-416658-X |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910789040803321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |