Requirements driven data warehouse design: We can go further

Abstract

Data warehouses (DW) are defined as data integration systems constructed from a set of heterogeneous sources and user’s requirements. Heterogeneity is due to syntactic and semantic conflicts occurring between used concepts. Existing DW design methods associate heterogeneity only to data sources. We claim in this paper that heterogeneity is also associated to users’ requirements. Actually, requirements are collected from heterogeneous target users, which can cause semantic conflicts between concepts expressed. Besides, requirements can be analyzed by heterogeneous designers having different design skills, which can cause formalism heterogeneity. Integration is the process that manages heterogeneity in DW design. Ontologies are recognized as the key solution for ensuring an automatic integration process. We propose to extend the use of ontologies to resolve conflicts between requirements. A pivot model is proposed for integrating requirements schemas expressed in different formalisms. A DW design method is proposed for providing the target DW schema (star or snowflake schema) that meets a uniformed and consistent set of requirements.