3 dw architectures
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The document discusses the components and architectures of data warehousing systems. It describes the major components as including data sources, extraction, loading, a comprehensive database, and metadata. It outlines three common architectures: three-tier, two-tier, and web-based. It also discusses alternative architectures and factors to consider when deciding which architecture to use, such as the database system, parallel processing, data migration tools, and data retrieval/analysis tools.
3 dw architectures
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- 3. The major components of a data warehousing process Data sources Data extraction Data loading Comprehensive database Metadata Middleware tools 3
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- 5. Three parts of the data warehouse The data warehouse that contains the data and associated software Data acquisition (back-end) software that extracts data from legacy systems and external sources, consolidates and summarizes them, and loads them into the data warehouse Client (front-end) software that allows users to access and analyze data from the warehouse 5
- 6. Architecture of a three-tier data warehouse 6
- 7. Architecture of a two tier data warehouse 7
- 8. Architecture of web based data warehousing. 8
- 9. Issues to consider when deciding which architecture to use: Which database management system (DBMS) should be used? Will parallel processing and/or partitioning be used? Will data migration tools be used to load the data warehouse? What tools will be used to support data retrieval and analysis?
- 10. Alternative Data Warehouse Architectures: • EDW Architecture 10
- 11. Alternative Data Warehouse Architectures: • Data Mart Architecture 11
- 12. Alternative Data Warehouse Architectures: • Hub-and-Spoke Data Mart Architecture 12
- 13. Alternative Data Warehouse Architectures: • EDW and ODS (real time access support) 13
- 14. Alternative Data Warehouse Architectures: •Distributed Data Warehouse Architecture 14
- 15. Alternative Architectures for Data Warehouse Efforts 15
- 16. Teradata Corp.’s EDW 16
- 17. Ten factors that potentially affect the architecture selection decision: 1. Information 5. Constraints on resources interdependence between 6. Strategic view of the data organizational units warehouse prior to 2. Upper management’s implementation information needs 7. Compatibility with existing 3. Urgency of need for a data systems warehouse 8. Perceived ability of the in- 4. Nature of end-user tasks house IT staff 9. Technical issues 10. Social/political factors
- 18. DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE. Turban Modern Data Warehousing, Mining, and Visualization: Core Concepts. George M. Marakas Modern Database Management.9th Edition.Jeffrey A. Hoffer, Mary B. Prescott, Heikki Topi