Abstract
A data warehouse is a database focused on decision making. Decision makers typically access data warehouses through OLAP tools, based on a multidimensional representation of data. In the past, the key issue of data warehouse quality has often been centered on data quality. However, since OLAP tool users directly access multidimensional schemas, multidimensional schema quality evaluation is also crucial. This paper focuses on the quality of multidimensional schemas, more specifically on the analyzability and simplicity criteria. We present the underlying multidimensional model and address the problem of measuring and finding the right balance between analyzability and simplicity of multidimensional schemas. Analyzability and simplicity are assessed using quality metrics which are described and illustrated based on a case study. The main objective of our approach is to provide the data warehouse designer with precise measures to support him in the choice among several alternative multidimensional schemas.
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Cherfi, S.SS., Prat, N. (2003). Multidimensional Schemas Quality: Assessing and Balancing Analyzability and Simplicity. In: Jeusfeld, M.A., Pastor, Ó. (eds) Conceptual Modeling for Novel Application Domains. ER 2003. Lecture Notes in Computer Science, vol 2814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39597-3_14
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DOI: https://doi.org/10.1007/978-3-540-39597-3_14
Publisher Name: Springer, Berlin, Heidelberg
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