Time is one of the dimensions we frequently find in data warehouses allowing comparisons of data in different periods. In cur- rent multi-dimensional data warehouse technology changes of dimension data cannot be represented adequately since all dimensions are (implicitly) considered as orthogonal. We propose an extension of the multi- dimensional data model employed in data warehouses allowing to cope correctly with changes in dimension data: A temporal multi-dimensional data model allows the registration of temporal versions of dimension data. Mappings are provided to transfer data between different temporal versions of the instances of dimensions and enable the system to correctly answer queries spanning multiple periods and thus different versions of dimension data.
CITATION STYLE
Eder, J., & Koncilia, C. (2001). Changes of dimension data in temporal data warehouses. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2114, pp. 284–293). Springer Verlag. https://doi.org/10.1007/3-540-44801-2_28
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