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Dynamic Warehousing: Data Mining Made Easy

An IBM Redbooks publication

Note: This is publication is now archived. For reference only.


Published on 06 September 2007, updated 12 March 2009

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ISBN-10: 0738488860
ISBN-13: 9780738488868
IBM Form #: SG24-7418-00

Authors: Chuck Ballard, John Rollins, Jo Ramos, Andy Perkins, Richard Hale, Ansgar Doerneich, Edward Cas Milner and Janardhan Chodagam

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    Data mining has evolved from the ethereal domain of the highly-skilled mathematician to the expert data miner's workbench tool and ultimately to widely accessible business applications. For decades, industry and academia have been engaged in far-reaching research and development of data mining. At the same time, businesses have been leveraging this research, exploiting a handful of algorithms most useful in finding information to help resolve business problems.

    Recent trends have made these algorithms and systems, which are rooted in solid research, available to a wide range of business users in easy-to-use forms. Large numbers of business analysts, who may not be data mining experts, can now solve high-value business problems using data mining technology embedded in database-resident business applications.

    In this IBM Redbooks publication, we discuss the methodology and selected techniques of embedded data mining and show how sophisticated technologies can be used in today's business environment to create significant business value. All this is enabled by the IBM DB2 Warehouse (DB2W) data mining capabilities. Using DB2W, we show examples of using data mining capabilities for such analytic functions as data modeling, scoring, and visualization. In addition, there are scenarios and examples that help in understanding where, when, and how to use data mining. For techniques, technical details, and practical examples, this is the book you need.

    Table of Contents

    Chapter 1. The business value of data mining

    Chapter 2. Data mining as a process

    Chapter 3. Case studies

    Chapter 4. Data mining methods

    Chapter 5. DB2 Warehouse tooling for data mining

    Chapter 6. Data preparation for data mining

    Chapter 7. Data Mining in DB2 Warehouse

    Chapter 8. Deploying a data mining solution

    Chapter 9. Solving a business problem with data mining

    Chapter 10. Emerging applications of data mining

    Appendix A. DB2 Warehouse data mining algorithms: a deep dive

    Appendix B. Power options


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