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Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management technologies. The author explains the new data mining capabilities in Microsoft's SQL Server 2000 database, Commerce Server, and other products, details the Microsoft OLE DB for Data Mining standard, and gives readers best practices for using all of them. The book bridges the previously specialized field of data mining with the new technologies and methods that are quickly making it an important mainstream tool for companies of all sizes.
Data mining refers to a set of technologies and techniques by which IT professionals search large databases of information (such as those contained by SQL Server) for patterns and trends. Traditionally important in finance, telecommunication, and other information-intensive fields, data mining increasingly helps companies better understand and serve their customers by revealing buying patterns and related interests. It is becoming a foundation for e-commerce and knowledge management.
- Unique book on a hot data management topic
- Part of Digital Press's SQL Server and data mining clusters
- Author is an expert on both traditional and Microsoft data mining technologies
Professional data analysts; DBAs, senior marketing managers, electronic direct marketing specialists; SQL Server programmers, administrators, and system designers
Introduction to Data Mining; The Data Mining Process; Data Mining Tools and Techniques; Managing the Data Mining Project; Modeling Data; Deploying the Results; The Discovery and Delivery of Knowledge for Effective Enterprise Outcomes: Knowledge Management; Appendices: Glossary; References; Web Sites; Data Mining and Knowledge Discovery Data Sets in the Public Domain; Microsoft Solution Providers; Summary of Knowledge Management Case Studies and Web Locations
- No. of pages:
- © Digital Press 2001
- 17th April 2001
- Digital Press
- eBook ISBN:
- Paperback ISBN:
Data mining pioneer and consultant with the SAS Institute. Author of many articles on data analysis, editorial board member for the journal Marketing Research
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