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Multidimensional Model Design using Data Mining: A Rapid Prototyping Methodology

Author

Listed:
  • Sandro Bimonte

    (IRSTEA, Clermont Ferrand, France)

  • Lucile Sautot

    (TETIS, AgroParisTech, Montpellier, France)

  • Ludovic Journaux

    (LE21, AgroSupDijon, Dijon, France)

  • Bruno Faivre

    (University of Burgundy Franche-Comté, Dijon, France)

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.

Suggested Citation

  • Sandro Bimonte & Lucile Sautot & Ludovic Journaux & Bruno Faivre, 2017. "Multidimensional Model Design using Data Mining: A Rapid Prototyping Methodology," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 13(1), pages 1-35, January.
    • Handle: RePEc:igg:jdwm00:v:13:y:2017:i:1:p:1-35
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