Abstract
The quality of Data Warehouses is absolutely relevant for organizations in the decision making process. The sooner we can deal with quality metrics (i.e. conceptual modelling), the more willing we are in achieving a data warehouse (DW) of a high quality. 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 data warehouses. However, in some cases, the goals and purposes of the proposed metrics are not very clear on their own. Lately, quality indicators have been proposed to properly define the goals of a measurement process and group quality measures in a coherent way. In this paper, we present a framework to design metrics in which each metric is part of a quality indicator we wish to measure. In this way, our method allows us to define metrics (theoretically validated) that are valid and perfectly measure our goals as they are defined together a set of well defined quality indicators.
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Berenguer, G., Romero, R., Trujillo, J., Serrano, M., Piattini, M. (2005). A Set of Quality Indicators and Their Corresponding Metrics for Conceptual Models of Data Warehouses. In: Tjoa, A.M., Trujillo, J. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2005. Lecture Notes in Computer Science, vol 3589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546849_10
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DOI: https://doi.org/10.1007/11546849_10
Publisher Name: Springer, Berlin, Heidelberg
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