Business Scenario and SAP BW

The objective of data warehousing is to analyze data from diverse sources to support decision making. To achieve this goal, we face two challenges:

• Poor system performance. A data warehouse usually contains a large volume of data. It is not an easy job to retrieve data quickly from the data warehouse for analysis purposes. For this reason, the data warehouse design uses a special technique called a star schema.
• Difficulties in extracting, transferring, transforming, and loading (ETTL) data from diverse sources into a data warehouse. Data must be cleansed before being used. ETTL has been frequently cited as being responsible for the failures of many data warehousing projects. You would feel the pain if you had ever tried to analyze SAP R/3 data without using SAP BW.

SAP R/3 is an ERP (Enterprise Resources Planning) system that most large companies in the world use to manage their business transactions. Before the introduction of SAP BW in 1997, ETTL of SAP R/3 data into a data warehouse seemed an unthinkable task. This macro-environment explained the urgency with which SAP R/3 customers sought a data warehousing solution. The result is SAP BW from SAP, the developer of SAP R/3.

In this chapter we will introduce the basic concept of data warehousing. We will also discuss what SAP BW (Business Information Warehouse) is, explain why we need it, examine its architecture, and define Business Content.

First, we use sales analysis as an example to introduce the basic concept of data warehousing.