Metadata-oriented Methodology for Building a Data Warehouse: a Medical Center Case

Abstract

Data warehouse is an intelligent store of data that can manage and aggregate vast amounts of information. A metadata is critical for implementing data warehouse. Therefore, integrating data warehouse with its metadata offers a new opportunity to create a more adaptive and flexible information system. This paper proposes a metadata-oriented methodology for building data warehouse that consists of seven components: legacy, extracting operational data store, data warehouse, data mart, application, and metadata. A taxonomy for dataflow and metaflow is proposed for better understanding of the methodology. In addition, a metadata schema is built within the framework of the seven components. The methodology by using its metadata component is applied to real-life data warehouse for a large medical center in order to illustrate its practical usefulness.