1. Chapter 14 Sharing Enterprise Data David M. Kroenke Database Processing © 2000 Prentice Hall

2. Chapter 14 © 2000 Prentice Hall Enterprise Database Processing Architectures Teleprocessing Systems Client-Server Systems File-Sharing Systems Distributed Database Systems Page 377

3. Chapter 14 © 2000 Prentice Hall Teleprocessing “All processing is done by one computer and one CPU while users operate dumb terminals that transmit transactions to the centralized computer” Page 377

4. Teleprocessing Architecture Page 378 Figure 14-1 © 2000 Prentice Hall

5. Chapter 14 © 2000 Prentice Hall Client-Server Systems “clients process application programs while servers process the database” Page 377

6. Client-Server Architecture Page 379 Figure 14-2 © 2000 Prentice Hall

7. Chapter 14 © 2000 Prentice Hall File-Sharing “Distributes to the users’ computers not only the application programs but also the DBMS” Page 379

8. File Sharing Architecture Page 380 Figure 14-3 © 2000 Prentice Hall

9. Chapter 14 © 2000 Prentice Hall Distributed Database Systems “Application processing has been distributed among several computers” –file-sharing –client-server –distributed database Page 380

10. Distributed Database Architecture Page 381 Figure 14-4 © 2000 Prentice Hall

11. Chapter 14 © 2000 Prentice Hall Types of Distributed Databases Vertical fragment Horizontal fragment Page 381

12. Chapter 14 © 2000 Prentice Hall Downloading Data “Can (should) be used for query and reporting purposes only” Page 383

13. Chapter 14 © 2000 Prentice Hall Download Problems Coordination Consistency Access Control Computer Crime Page 385

14. Chapter 14 © 2000 Prentice Hall On Line Analytic Processing OLAP; data is viewed in he frame of a table or cube Page 388

15. OLAP Table Page 389 Figure 14-11 © 2000 Prentice Hall

16. OLAP Cube Page 390 Figure 14-12 © 2000 Prentice Hall

17. OLAP Terminology Page 390 Figure 14-14 © 2000 Prentice Hall

18. Chapter 14 © 2000 Prentice Hall Data Warehouse “a store of enterprise data that is designed to facilitate management decision making” Page 394

19. Data Warehouse Page 395 Figure 14-18 © 2000 Prentice Hall

20. Data Warehouse Components Page 396 Figure 14-19 © 2000 Prentice Hall

21. Data Warehouse Requirements Page 397 Figure 14-20 © 2000 Prentice Hall

22. Chapter 14 © 2000 Prentice Hall Data Warehouse Challenges Inconsistent Data Tool Integration Missing Warehouse Data Management Tools Ad Hoc Nature of Requirements Page 397

23. Chapter 14 © 2000 Prentice Hall Data Mart “Facility akin to a data warehouse but for a much smaller domain” Page 401

24. Chapter 14 © 2000 Prentice Hall Data Administration “in some ways, data administration is to data what the controller is to money” Page 402

25. Data Administration Challenges Page 403 Figure 14-25 © 2000 Prentice Hall

26. Data Administration Functions Page 404 Figure 14-26 © 2000 Prentice Hall