A Model and Language for Bitemporal Schema Versioning in Data Warehouses

A data warehouse (DW) is a vast collection of historical data built to support multidimensional data analysis applications. In this context, an important problem is that of evolving the implementation (multidimensional, relational) schema of a DW to incorporate new requirements. This paper introduces a conceptual evolution model based on bitemporal versioning of multidimensional schemas, which allows one to modify the DW schema (a) in an implementation-independent manner, and (b) without affecting the operation of existing applications. It also presents a SQL-like language associated to this model, which offers expressions to create and change versions of multidimensional schemas