The Data Warehouse Method

The Data Warehouse Method

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With The Data Warehouse Method, enterprises can transcend yesterday's haphazard approaches to data warehousing - and achieve unprecedented strategic gains. Leading consultant Tom Debevolse synthesizes the entire field's experience into a comprehensive methodology that delivers consistency, value, and above all, quality. Avoiding generalities, Debevoise demonstrates enterprise-class techniques in the context of 64-bit multiprocessing UNIX servers, the Oracle 8 OORDBMS, and the Business Objects Managed Query Environment. Whether you choose identical technologies or not, the resulting methodology is refreshingly specific and practical. The Data Warehouse Method presents the quality data warehouse from every key perspective: the business, the user, the architect, and the administrator. It previews the evolution of data warehouses into business knowledge repositories that integrate the entire enterprise. Best of all, it offers a path you can follow today to achieve maximum results with maximum more

Product details

  • Mixed media product | 420 pages
  • 180.34 x 233.68 x 40.64mm | 1,156.65g
  • Pearson Education (US)
  • Prentice Hall
  • Upper Saddle River, United States
  • English
  • 0130813060
  • 9780130813060

About Nielson Debevboise

Nielson Debevoiseis a data warehousing consultant for Blue Ridge NCA Corporation, residing in Blue Ridge, more

Table of contents

1. The Data Warehouse Method. Quality Data Warehouses Processes. Data Warehouse Methodology. Technical Architectures. Data Warehouse Administration. Performance Management.2. The Managed Query Environment. Interaction with the MQE Environment. Data Mining Tools. Implementing the Discovery into the Strategy.3. Methodology. Data Warehouse Method Introduction. Team Roles in the IDSE. Preparation for Data Warehouse Methods. The Guiding Principals of the Data Warehouse Method.4. Strategy. Strategy and the Data Warehouse. CASE and Strategic Analysis. Quality in a DWM Strategy. MQE Tools. Strategy Quality Risks. Strategy Deliverables.5. Analysis. Analysis Phase Use Case Analysis. Analysis Planning. Business Rules Analysis. Business Rules, Terms and Objectives. Analysis Data Elements. Candidate Semantic Cubes. Acquisition Classes. Quality Risks, Quality Improvements. Analysis Functional Documentation and Deliverable.6. Design. Design Use Case Analysis. Planning for Design. Acquisition Module Design. Data Object Construction. Quality Risks/Quality Improvements in the Design Process. Design Conclusion.7. Construction. Construction Use Case. Planning for Construction. Constructing the Process Monitor. Construction Project Example. Quality Risks, Quality Improvements for the Construction Phase. Construction Conclusion.8. The Quality DW Technical Architecture. Fading Client Server Architectures. Logical Architecture. Physical Architecture. Subsystem Requirements. Summary.9. Administration of the IDSE. The Mission of the Database Administrator. The Roles of the DBA. Managing Memory and I/O Resources. Optimizing "Star" Queries. Parallel Query Tuning. Tablespaces. Partitioning and the Parallel Load. Partitions in Oracle. Fragmentation. Process Management. Oracle's Cost Based Analyzer. Backup and Recovery. Conclusion.10. Managing Dimension and Event Data. Degrees of Freedom and the Aggregate. Aggregate Management Process Overview. Components of the Solution. Aggregate Creation. Conclusion.11. Conclusion. The Need for a New Repository. Business Knowledge Method. Components of the BRR Architecture. Object Transport Components. Business Rules Data Schema. Operational Data Store. Enterprise Architecture. Summary.Appendix A: IDSE Sample Object Naming Convention. Naming Conventions and Guidelines. CASE Abbreviations.Appendix B: Aggregate Wizard Setup. Steps for Installation. Aggregate Forms.Appendix C: Aggregate Wizard Package Listing. Repository Utilities. Repository Integration Utilities. Aggregate Generation Utilities. Task Broker. Aggregate Wizard, Remote Agent. more

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