The Formal Model for Multiversion Data Warehouse Evolution
Darja Solodovnikova · Frontiers in artificial intelligence and applications · 2009
Schemata of data warehouses often need to be adapted because of evolving business requirements or changes in data sources. To accumulate the history of schemata and data, it is possible to maintain multiple versions of data warehouse schemata. We propose the formal model to store the data about data warehouse logical and physical schemata and their versions. For each modification of a data warehouse schema, we outline the changes that need to be made to the formal model. We present the data warehouse framework that is able to track evolution process and adapt data warehouse schemata and data extraction, transformation and loading (ETL) processes.