1. Copyright © 2004 Pearson Education, Inc.

2. Chapter 28 Overview of Data Warehousing and OLAP

3. Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition Copyright © 2004 Pearson Education, Inc. Slide 28-3 Introduction, Definitions, and Terminology Data warehouse –Long-term data storage OLAP –Online analytical processing DSS –Decision support systems

4. Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition Copyright © 2004 Pearson Education, Inc. Slide 28-4 Characteristics of Data Warehouses Modeled differently – multidimensional rather than strictly relational Data is “cleaned” prior to transfer Data is updated on scheduled basis, rather than as transactions happen Used for making long-term business decisions, not for daily transactions

5. Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition Copyright © 2004 Pearson Education, Inc. Slide 28-5 Data Modeling for Data Warehouses Multidimensional models use matrices called data cubes The relational data model can be cumbersome for the types of querying that is needed in a data warehouse. Can query in each direction to answer questions.

6. Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition Copyright © 2004 Pearson Education, Inc. Slide 28-6 Building a Data Warehouse Needs careful design Terms need to be standardized –For instance, F/M instead of Female/Male Often subdivided into dependent data marts, keeping related data physically close

7. Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition Copyright © 2004 Pearson Education, Inc. Slide 28-7 Problems and Open Issues in Data Warehouses Difficulties of Implementing Data Warehouses Open Issues in Data Warehousing

8. Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition Copyright © 2004 Pearson Education, Inc. Slide 28-8 Summary http://en.wikipedia.org/wiki/Data_warehous e http://en.wikipedia.org/wiki/Data_warehous e