Studierende stehen vor dem LC und blicken lächelnd einer Kollegin mit einer Mappe in der Hand nach.

Data Warehouse Management with SAP BW


The methodological part introduces terms and concepts in data warehousing, explaining the fundamental difference between a warehouse containing multi-dimensional and aggregate data as opposed to operational information systems. The design methods concentrate on conceptual data modeling, which is the fundamental basis for the design and implementation of any data warehouse. The methods presented are Dimensional Fact Modeling (DFM), which is used to transfer an Entity-Relationship model of an operational system into a basic warehouse model and an Aggregation Path Array (APA), which is used to decide the aggregates that will be needed in warehouse usage.

As regards to the implementation of the conceptual model, the relational Star Schema and its derivatives are considered in detail. Thus, the methodological part of the book ranges from the modeling of user requirements to the relational table definition.

The implementation part of the book deals with a case study (a warehouse used for sales analysis), which is implemented in SAP® BW. After an introduction to the architecture of the product, the entire warehouse definition and implementation phase is demonstrated including the definition of multi-dimensional data structures ("info cubes"), import and filtering of operational data, building aggregation hierarchies, and the definition of a reporting scheme. Each step is documented by screen shots and a detailed explanation of the data entries made.

A host of free, Web-based materials is available in the Courses section, which can be used in conjunction with the text including transparencies for classroom use, Web trainers for all methods presented in the book, and a Java® applet implementing the Aggregation Path Array for warehouse design.

The indended audience are students and lecturers in the fields of applied computing science or business administration with a focus on Controlling and analytical information processing as well as practitioners, who would like to learn about data warehouse design methodology applied to an industry-relevant case study.

The Authors

Alexander Prosser is Associate Professor at the Department of Production Management at the University of Economics and Business Administration, Vienna and Permanent Visiting Professor at the School of Accounting at the University of Technology, Sydney.
Maria-Luise Ossimitz has taught Data Warehouse Management at the University of Economics and Business Administration, Vienna and the University of Technology, Sydney.