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Data warehousing, data mining, and OLAP / Alex Berson and Stephen J. Smith.

By: Berson, AlexContributor(s): Smith, Stephen J, 1953-Material type: TextTextPublication details: London : McGraw-Hill, 1997. ISBN: 0070062722Subject(s): Decision support systems | Application software -- DevelopmentDDC classification: 658.4038028551
Partial contents:
Ch. 1. Introduction to Data Warehousing -- Ch. 2. Client/Server Computing Model and Data Warehousing -- Ch. 3. Parallel Processors and Cluster Systems -- Ch. 4. Distributed DBMS Implementations -- Ch. 5. Client/Server RDBMS Solutions -- Ch. 6. Data Warehousing Components -- Ch. 7. Building a Data Warehouse -- Ch. 8. Mapping the Data Warehouse to a Multiprocessor Architecture -- Ch. 9. DBMS Schemas for Decision Support -- Ch. 10. Data Extraction, Cleanup, and Transformation Tools -- Ch. 11. Metadata -- Ch. 12. Reporting and Query Tools and Applications -- Ch. 13. On-Line Analytical Processing (OLAP) -- Ch. 14. Patterns and Models -- Ch. 15. Statistics -- Ch. 16. Artificial Intelligence -- Ch. 17. Introduction to Data Mining -- Ch. 18. Decision Trees -- Ch. 19. Neural Networks -- Ch. 20. Nearest Neighbor and Clustering -- Ch. 21. Genetic Algorithms -- Ch. 22. Rule Induction -- Ch. 23. Selecting and Using the Right Technique -- Ch. 24. Data Visualization -- Ch. 25. Putting It All Together -- App. B. Big Data - Better Returns: Leveraging Your Hidden Data Assets to Improve ROI -- App. C. Dr. E.F. Codd's 12 Guidelines for OLAP -- App. D. 10 Mistakes for Data Warehousing Managers to Avoid.
Holdings
Item type Home library Call number Status Date due Barcode Item holds
Two Week Loan Two Week Loan de Havilland Learning Resources Centre
Main Shelves 		658.4038028551 BER (Browse shelf(Opens below)) Available 4404065899
Total holds: 0

Enhanced descriptions from Syndetics:

Ch. 1. Introduction to Data Warehousing -- Ch. 2. Client/Server Computing Model and Data Warehousing -- Ch. 3. Parallel Processors and Cluster Systems -- Ch. 4. Distributed DBMS Implementations -- Ch. 5. Client/Server RDBMS Solutions -- Ch. 6. Data Warehousing Components -- Ch. 7. Building a Data Warehouse -- Ch. 8. Mapping the Data Warehouse to a Multiprocessor Architecture -- Ch. 9. DBMS Schemas for Decision Support -- Ch. 10. Data Extraction, Cleanup, and Transformation Tools -- Ch. 11. Metadata -- Ch. 12. Reporting and Query Tools and Applications -- Ch. 13. On-Line Analytical Processing (OLAP) -- Ch. 14. Patterns and Models -- Ch. 15. Statistics -- Ch. 16. Artificial Intelligence -- Ch. 17. Introduction to Data Mining -- Ch. 18. Decision Trees -- Ch. 19. Neural Networks -- Ch. 20. Nearest Neighbor and Clustering -- Ch. 21. Genetic Algorithms -- Ch. 22. Rule Induction -- Ch. 23. Selecting and Using the Right Technique -- Ch. 24. Data Visualization -- Ch. 25. Putting It All Together -- App. B. Big Data - Better Returns: Leveraging Your Hidden Data Assets to Improve ROI -- App. C. Dr. E.F. Codd's 12 Guidelines for OLAP -- App. D. 10 Mistakes for Data Warehousing Managers to Avoid.

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