A set of quality indicators and their corresponding metrics for conceptual models of data warehouses

  • Authors:

  • Gema Berenguer;Rafael Romero;Juan Trujillo;Manuel Serrano;Mario Piattini

  • Affiliations:

  • Dept. de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante;Dept. de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante;Dept. de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante;Escuela Superior de Informática, University of Castilla – La Mancha, Ciudad Real;Escuela Superior de Informática, University of Castilla – La Mancha, Ciudad Real

  • Venue:
  • DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
  • Year:
  • 2005

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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.