Automating data warehouse conceptual schema design and evaluation.

Abstract

The popularity of data warehouses for analysis of data has grown tremendously, but much of the creation of data warehouses is done manually. We propose and illustrate algorithms for automatic conceptual schema development and evaluation. Our creation algorithm uses an enterprise schema of an operational database as a starting point for source-driven data warehouse schema design. Candidate conceptual schemas are created using the ME/R model, extended to note where additional user input can be used to further refine a schema. Our evaluation algorithm follows a user-driven requirements approach that utilizes queries to guide selection of candidate schemas most likely to meet user needs. In addition, we propose a guideline of manual steps to refine a conceptual schema to suit additional user needs, for example, the level of detail needed for date fields. The algorithms are illustrated using the TPC-H Benchmark schema and queries. Our algorithms provide a foundation for a software tool to create and evaluate data warehouse conceptual schemas.

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