A Comparison of Data Warehouse Development Methodologies Case Study of the Process Warehouse

• Published in: Database and Expert Systems Applications pp. 203 - 215
• Main Authors: List, Beate, Bruckner, Robert M., Machaczek, Karl, Schiefer, Josef
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2002; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Audit Trail; Business Process; Computer science; control theory; systems; Development Methodology; Exact sciences and technology; Information systems. Data bases; Memory organisation. Data processing; Performance Measurement System; Process Instance; Software; Business process; Decision support system; Data storage; Firm management; Integrated management; Data warehouse; Software engineering
• ISBN: 9783540441267; 3540441263
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/3-540-46146-9_21

Building a data warehouse is a very challenging issue because compared to software engineering it is quite a young discipline and does not yet offer well-established strategies and techniques for the development process. Current data warehouse development methods can fall within three basic groups: data-driven, goal-driven and user-driven. All three development approaches have been applied to the Process Warehouse that is used as the foundation of a process-oriented decision support system, which aims to analyse and improve business processes continuously. In this paper we evaluate all three development methodologies by various assessment criteria. The aim is to establish a link between the methodology and the requirement domain.