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Article Dans Une Revue IEEE Transactions on Knowledge and Data Engineering Année : 2021

A semi-automatic design methodology for (Big) Data Warehouse transforming facts into dimensions

Résumé

A decision support system is used by decision makers for a long time. But, in some cases, the originally designed multidimensional schema does not cover the entire needs of decision makers, which can change over time. One such unfulfilled needs, is using facts to describe dimension members. In this article, we propose a methodology to transform the constellation schema of a data warehouse by integrating factual data into a dimension. The proposed methodology and algorithms enrich a constellation multidimensional schema with new analytical possibilities for decision makers. This enrichment has repercussions for the entire multidimensional schema that are managed by multidimensional modeling, hierarchy calculation and the hierarchy version. In this article, we present a theoretical view of the proposed methodology supported by a case study, an implemented prototype and a complete evaluation based on a standard benchmark.
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Dates et versions

hal-02272160 , version 1 (01-12-2022)

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Citer

Lucile Sautot, Sandro Bimonte, Ludovic Journaux. A semi-automatic design methodology for (Big) Data Warehouse transforming facts into dimensions. IEEE Transactions on Knowledge and Data Engineering, 2021, 33 (1), pp.28-42. ⟨10.1109/TKDE.2019.2925621⟩. ⟨hal-02272160⟩
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