De­scrip­ti­on

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.