Data warehouse testing: A prototype-based methodology

Context g is an essential part of the development life-cycle of any software product. While most phases of data warehouse design have received considerable attention in the literature, not much has been written about data warehouse testing. ive s paper we propose a comprehensive approach to testing data warehouse systems. Its main features are earliness with respect to the life-cycle, modularity, tight coupling with design, scalability, and measurability through proper metrics. roduce a number of specific testing activities, we classify them in terms of what is tested and how it is tested, and we show how they can be framed within a prototype-based methodology. We apply our approach to a real case study for a large retail company. s se study we faced, based on an iterative prototype-based medium-size project, confirmed the validity of our approach. In particular, the main benefits were obtained in terms of project transparency, coordination of the development team, and organization of design activities. sion some general-purpose testing techniques can be applied to data warehouse projects, the effectiveness of testing can be largely improved by applying specifically-devised techniques and metrics.