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Article dans une revue

Multidimensional Model Design using Data Mining: A Rapid Prototyping Methodology

Abstract : 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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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01464597
Déposant : Le2i - Université de Bourgogne <>
Soumis le : vendredi 10 février 2017 - 12:27:09
Dernière modification le : jeudi 2 juillet 2020 - 14:01:44

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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), IGI Global, 2017, INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING, 13 (1), pp.1-35. ⟨10.4018/IJDWM.2017010101⟩. ⟨hal-01464597⟩

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