Data warehouses are mainly based on multidimensional modeling. Using OLAP tools, decision makers analyze data at different aggregation levels. Therefore, aggregation knowledge should be adequately represented in conceptual multidimensional models, and mapped in subsequent logical and physical models. However, current conceptual multidimensional models poorly represent aggregation knowledge. In order to account for the characteristics of this knowledge, we propose to represent it with objects (UML class diagrams) and rules in Production Rule Representation (PRR) language. We present our approach and illustrate it with an application scenario.
PRAT, N., COMYN-WATTIAU, I. et AKOKA, J. (2010). Representation of Aggregation Knowledge in OLAP Systems. Dans: 18th European Conference on Information Systems (ECIS 2010). Pretoria: University of Pretoria, pp. 1-12.