Designing A Data Warehouse: Supporting Customer Relationship Management

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.

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