Schema Evolution publication categorizer

A data warehouse (DW) is fed with data that come from external data sources that are production systems. External data sources, which are usually autonomous, often change not only their content but also their structure. The evolution of external data sources has to be reflected in a DW, that uses the sources. Traditional DW systems offer a limited support for handling dynamics in their structure and content. A promising approach to handling changes in DW structure and content is based on a multiversion data warehouse. In such a DW, each DW version describes a schema and data at certain period of time or a given business scenario, created for simulation purposes. In order to appropriately analyze multiversion data, an extension to a traditional SQL language is required. In this paper we propose an approach to querying a multiversion DW. To this end, we extended a SQL language and built a multiversion query language interface with functionality that allows: (1) expressing queries that address several DW versions and (2) presenting their results annotated with metadata information.