Integration and dimensional modeling approaches for complex data warehousing |
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Authors: | O Boussaid Adrian Tanasescu Fadila Bentayeb Jérôme Darmont |
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Institution: | (1) ERIC, Université Lumière Lyon2, 5 avenue Pierre-Mendès-France, 69676 Bron Cedex, France;(2) LIRIS, Université Claude Bernard Lyon 1, 43 boulevard. du 11 novembre 1918, 69422 Villeurbanne Cedex, France |
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Abstract: | With the broad development of the World Wide Web, various kinds of heterogeneous data (including multimedia data) are now
available to decision support tasks. A data warehousing approach is often adopted to prepare data for relevant analysis. Data
integration and dimensional modeling indeed allow the creation of appropriate analysis contexts. However, the existing data
warehousing tools are well-suited to classical, numerical data. They cannot handle complex data. In our approach, we adapt
the three main phases of the data warehousing process to complex data. In this paper, we particularly focus on two main steps
in complex data warehousing. The first step is data integration. We define a generic UML model that helps representing a wide
range of complex data, including their possible semantic properties. Complex data are then stored in XML documents generated
by a piece of software we designed. The second important phase we address is the preparation of data for dimensional modeling.
We propose an approach that exploits data mining techniques to assist users in building relevant dimensional models. |
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Keywords: | Complex data Data integration Data mining Dimensional modeling Data preparation Data warehousing |
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