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Other titles in the Hewlett-Packard Professional Books series:
Designing a Data Warehouse: Supporting Customer Relationship Management (Hewlett-Packard Professional Books)by Chris Todman
Synopses & Reviews
The complete guide to building tomorrow's CRM-focused data warehouses.
Today's next-generation data warehouses are being built with a clear goal: to maximize the power of Customer Relationship Management. To make CRM-focused data warehousing work, you need new techniques, and new methodologies. In this book, Dr. Chris Todman—one of the world's leading data warehouse consultants—delivers the first start-to-finish methodology for defining, designing, and implementing CRM-focused data warehouses. Todman covers all this, and more:
If you want to leverage the full power of your CRM system, you need a data warehouse designed for the purpose. One book shows you exactly how to build one: Designing Data Warehouses by Dr. Chris Todman.
Includes bibliographical references (p. 313) and index.
About the Author
DR. CHRIS TODMAN has, for the last decade, specialized in data warehousing projects throughout the telecommunications, financial services, automotive and utilities industries. During the past five years he has served as Hewlett-Packard's UK Data Warehouse Practice Manager. An IT professional for more than 20 years, Todman earned a Ph.D. based in part on his advanced research into data warehousing.
Table of Contents
1. Customer Relationship Management.
The Business Dimension. Business Goals. Business Strategy. The Value Proposition. Customer Relationship Management. Summary.
2. An Introduction to Data Warehousing.
Introduction. What Is a Data Warehouse? Dimensional Analysis. Building a Data Warehouse. Problems When Using Relational Databases. Summary.
3. Design Problems We Have to Face Up To.
Dimensional Data Models. What Works for CRM. Summary.
4. The Implications of Time in Data Warehousing.
The Role of Time. Problems Involving Time. Capturing Changes. First-Generation Solutions for Time. Variations on a Theme. Conclusions to the Review of First-Generation Methods.
5. The Conceptual Model.
Requirements of the Conceptual Model. The Identification of Changes to Data. Dot Modeling. Dot Modeling Workshops. Summary.
6. The Logical Model.
Logical Modeling. The Implementation of Retrospection. The Use of the Time Dimension. Logical Schema. Performance Considerations. Choosing a Solution. Frequency of Changed Data Capture. Constraints. Evaluation and Summary of the Logical Model.
7. The Physical Implementation.
The Data Warehouse Architecture. CRM Applications. Backup of the Data. Archival. Extraction and Load. Summary.
8. Business Justification.
The Incremental Approach. The Submission. Summary.
9. Managing the Project.
Introduction. What Are the Deliverables? What Assumptions and Risks Should I Include? What Sort of Team Do I Need? Summary.
10. Software Products.
Extraction, Transformation, and Loading. OLAP. Query Tools. Data Mining. Campaign Management. Personalization. Metadata Tools. Sorts.
11. The Future.
Temporal Databases (Temporal Extensions). OLAP Extensions to SQL. Active Decision Support. External Data. Unstructured Data. Search Agents. DSS Aware Applications.
Appendix A. Wine Club Temporal Classifications.
Appendix B. Dot Model for the Wine Club.
Appendix C. Logical Model for the Wine Club.
Appendix D. Customer Attributes.
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