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Article Dans Une Revue International Journal of Data Warehousing and Mining (JDWM) Année : 2017

Multidimensional Model Design using Data Mining: A Rapid Prototyping Methodology

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Résumé

Designing and building a Data Warehouse (DW), and associated OLAP cubes, are long processes, during which decision-maker requirements play an important role. But decision-makers are not OLAP experts and can find it difficult to deal with the concepts behind DW and OLAP. To support DW design in this context, we propose: (i) a new rapid prototyping methodology, integrating two different DM algorithms, to define dimension hierarchies according to decision-maker knowledge; (ii) a complete UML Profile, to define a DW schema that integrates both the DM algorithms; (iii) a mapping process to transform multidimensional schemata according to the results of the DM algorithms; (iv) a tool implementing the proposed methodology; (v) a full validation, based on a real case study concerning bird biodiversity. In conclusion, we confirm the rapidity and efficacy of our methodology and tool in providing a multidimensional schema to satisfy decision-maker analytical needs.
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Dates et versions

hal-01464597 , version 1 (10-02-2017)

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Sandro Bimonte, Lucile Sautot, Ludovic Journaux, Bruno Faivre. Multidimensional Model Design using Data Mining: A Rapid Prototyping Methodology. International Journal of Data Warehousing and Mining (JDWM), 2017, INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING, 13 (1), pp.1-35. ⟨10.4018/IJDWM.2017010101⟩. ⟨hal-01464597⟩
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