Chapter 14 Sharing Enterprise Data David M. Kroenke Database Processing © 2000 Prentice Hall
Chapter 14 © 2000 Prentice Hall Enterprise Database Processing Architectures Teleprocessing Systems Client-Server Systems File-Sharing Systems Distributed Database Systems Page 377
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
Teleprocessing Architecture Page 378 Figure 14-1 © 2000 Prentice Hall
Chapter 14 © 2000 Prentice Hall Client-Server Systems “clients process application programs while servers process the database” Page 377
Client-Server Architecture Page 379 Figure 14-2 © 2000 Prentice Hall
Chapter 14 © 2000 Prentice Hall File-Sharing “Distributes to the users’ computers not only the application programs but also the DBMS” Page 379
File Sharing Architecture Page 380 Figure 14-3 © 2000 Prentice Hall
Chapter 14 © 2000 Prentice Hall Distributed Database Systems “Application processing has been distributed among several computers” –file-sharing –client-server –distributed database Page 380
Distributed Database Architecture Page 381 Figure 14-4 © 2000 Prentice Hall
Chapter 14 © 2000 Prentice Hall Types of Distributed Databases Vertical fragment Horizontal fragment Page 381
Chapter 14 © 2000 Prentice Hall Downloading Data “Can (should) be used for query and reporting purposes only” Page 383
Chapter 14 © 2000 Prentice Hall Download Problems Coordination Consistency Access Control Computer Crime Page 385
Chapter 14 © 2000 Prentice Hall On Line Analytic Processing OLAP; data is viewed in he frame of a table or cube Page 388
OLAP Table Page 389 Figure © 2000 Prentice Hall
OLAP Cube Page 390 Figure © 2000 Prentice Hall
OLAP Terminology Page 390 Figure © 2000 Prentice Hall
Chapter 14 © 2000 Prentice Hall Data Warehouse “a store of enterprise data that is designed to facilitate management decision making” Page 394
Data Warehouse Page 395 Figure © 2000 Prentice Hall
Data Warehouse Components Page 396 Figure © 2000 Prentice Hall
Data Warehouse Requirements Page 397 Figure © 2000 Prentice Hall
Chapter 14 © 2000 Prentice Hall Data Warehouse Challenges Inconsistent Data Tool Integration Missing Warehouse Data Management Tools Ad Hoc Nature of Requirements Page 397
Chapter 14 © 2000 Prentice Hall Data Mart “Facility akin to a data warehouse but for a much smaller domain” Page 401
Chapter 14 © 2000 Prentice Hall Data Administration “in some ways, data administration is to data what the controller is to money” Page 402
Data Administration Challenges Page 403 Figure © 2000 Prentice Hall
Data Administration Functions Page 404 Figure © 2000 Prentice Hall