A methodology and tool for rapid prototyping of data warehouses using data mining: Application to birds biodiversity

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Abstract

Data Warehouses (DWs) are large repositories of data aimed at supporting the decision-making process by enabling flexible and interactive analyses via OLAP systems. Rapid prototyping of DWs is necessary when OLAP applications are complex. Some work about the integration of Data Mining and OLAP systems has been done to enhance OLAP operators with mined indicators, and/or to define the DW schema. However, to best of our knowledge, prototyping methods for DWs do not support this kind of integration. Then, in this paper we present a new prototyping methodology for DWs, extending [3], where DM methods are used to define the DW schema. We validate our approach on a real data set concerning bird biodiversity.

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Sautot, L., Bimonte, S., Journaux, L., & Faivre, B. (2014). A methodology and tool for rapid prototyping of data warehouses using data mining: Application to birds biodiversity. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8748, 250–257. https://doi.org/10.1007/978-3-319-11587-0_23

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