Empirical Validation of Metrics for Datawarehouses
Manuel Serrano, Coral Calero, Juan Trujillo, Sergio Luján-Mora, Mario Piattini
Proceedings of the 4th ASERC Workshop on Quantitative and Soft Computing Based Software Engineering (QSSE 2004), p. 44-49, Banff (Canada), February 16-17 2004.
(QSSE'04) Congreso internacional / International conference
Datawarehouses (DW), based on the multidimensional modeling, provide companies with huge historical information for the decision making process. As these DW's are crucial for companies in making decisions, their quality lays on the models (conceptual, logical and physical) we use to design them. In the last years, there have been several approaches to design DW's from the conceptual, logical and physical perspectives. However, from our point of view, there is a lack of more objective indicators (metrics) to guide the designer in accomplishing an outstanding model that allows us to guarantee the quality of these DW's. In this paper, we present a set of metrics to measure the quality of conceptual models for DW's. We have validated them through an empirical experiment performed by last course students in computer science. Our experiment showed us that several of the proposed metrics seems to be practical indicators of the quality of conceptual models for DW's.