New data warehouse designing approach based on principal component analysis


Decision making has become a strategic need for any business. Indeed, it is among the priorities of capital business. The establishment of decision information systems facilitates the data exploitation and analysis. We distinguish data warehouses as the core system of business intelligence to ensure the structuring and analysis of multidimensional data. Consequently, the design of data warehouses has become a major problem, leading to the development of appropriate approaches to implement data warehouses. In this paper, we propose an approach to design and to construct data warehouses based on a descriptive statistics technique for the analysis of multidimensional data in the Principal Components Analysis (PCA). The findings of this article appear in two main areas: (i) a conceptual model data warehouse, (ii) an algorithm for the determination of measures and dimensions. A case study is used to validate our proposal.

DOI: 10.1109/SNPD.2014.6888696

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@article{Tebourski2014NewDW, title={New data warehouse designing approach based on principal component analysis}, author={Wafa Tebourski and Wahiba Ben Abdessalem Karaa and Henda Ben Ghezela}, journal={15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)}, year={2014}, pages={1-6} }