Schema evolution in data warehousing environments — a schema transformation-based approach

Abstract. In heterogeneous data warehousing environments, autonomous data sources are integrated into a materialised integrated database. The schemas of the data sources and the integrated database may be expressed in different modelling languages. It is possible for either the data source schemas or the warehouse schema to evolve. This evolution may include evolution of the schema, or evolution of the modelling language in which the schema is expressed, or both. In such scenarios, it is important for the integration framework to be evolvable, so that the previous integration effort can be reused as much as possible. This paper describes how the AutoMed heterogeneous data integration toolkit can be used to handle the problem of schema evolution in heterogeneous data warehousing environments. This problem has been addressed before for specific data models, but AutoMed has the ability to cater for multiple data models, and for changes to the data model