Combining Objects with Rules to Represent Aggregation Knowledge in Data Warehouse and OLAP Systems
Data warehouses are based on multidimensional modeling. Using On-Line Analytical Processing (OLAP) tools, decision makers navigate through and analyze multidimensional data. Typically, users need to analyze data at different aggregation levels (using roll-up and drill-down functions). 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, which (1) has a complex structure and dynamics and (2) is highly contextual. 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. Static aggregation knowledge is represented in the class diagrams, while rules represent the dynamics (i.e. how aggregation may be performed depending on context). We present the class diagrams, and a typology and examples of associated rules. We argue that this representation of aggregation knowledge allows an early modeling of user requirements in a data warehouse project.
|Date of creation:||Dec 2009|
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- Baroni, Michel & Barthélémy, Fabrice & Mokrane, Mahdi, 2005. "A PCA Factor Repeat Sales Index (1973-2001) To Forecast Apartment Prices in Paris (France)," ESSEC Working Papers DR 05002, ESSEC Research Center, ESSEC Business School.
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