Abstract

A data warehouse (DW) is a large data repository system designed for decision-making purposes. Its design relies on a specific model called multidimensional. This multidimensional model supports analyses of huge volumes of data that trace the enterprise's activities over time. Several design methods were proposed to build multidimensional schemas from either the relational data model or the entity-relationship data model. Almost all proposals that treated the object-oriented data model assume the presence of the data source UML class-diagram. However, in practice, either such a diagram does not exist or is obsolete due to multiple changes/evolutions of the information system. Furthermore, these few proposals require an intense manual intervention of the designer, which requires a high expertise both in the DW domain and in the object database domain. To overcome these disadvantages, this work proposes an automatic DW schema design method starting from an object database (schema and its instances). This method applies a set of extraction rules to identify multidimensional concepts and to generate star schemas. It is defined for the standard ODMG model and, thus, can be adapted with slight changes for other object database models. In addition, its extraction rules have the merit of being independent of the domain semantics. Furthermore, they automatically generate schemas classified according to their analytical potential; this classification helps the DW designer in selecting the most relevant schemas among the generated ones. Finally, being automatic, our method is supported by a toolset that also prepares for the automatic generation of the Extract Transform and Load procedures used to load the DW.

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