AN APPROACH TO SCHEMA MAPPING GENERATION FOR DATA WAREHOUSING
In data warehousing, the source schemas are defined independently from the warehouse schemas, which are typically designed based on the information need of the warehouse users. The mappings between the source and warehouse schemas are also determined manually. Typically, more than one mapping between the warehouse schema and the source schemas is possible and the designer might miss the most appropriate mapping from the viewpoint of updates and maintenance of the warehouse.
Automated generation of the mappings between the source and the warehouse schemas would generate a complete list of mappings from which the warehouse designer can choose the appropriate mapping.
The issues encountered during automation are numerous, including but not restricted to the presence of synonyms, homonyms and derived attributes in the source and warehouse schemas. This thesis focuses on automating mapping generation in data warehousing for the relational domain and handles select, project, join, union and intersection mappings.