Temporal structures in data warehousing

Abstract

Following the paradigm of on-line analytical processing (OLAP) every representation of business objects in management support systems is multidimensional. Dynamic changes of business structures like consolidations have to be modeled in the data warehouse framework. For reasons of consistency in analytical applications it is necessary to add temporal components to the data model. Objects and relations between objects will be provided with time stamps corresponding to known methods of temporal data storage. This enhancement of the OLAP-approach allows even after changes of structural data (dimensions) an appropriate comparative analysis between arbitrary periods. But any access to multidimensional cubes make it necessary to evaluate a meta cube.