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DAWAK
2010
Springer

A Model-Driven Heuristic Approach for Detecting Multidimensional Facts in Relational Data Sources

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A Model-Driven Heuristic Approach for Detecting Multidimensional Facts in Relational Data Sources
Facts are multidimensional concepts of primary interests for knowledge workers because they are related to events occurring dynamically in an organization. Normally, these concepts are modeled in operational data sources as tables. Thus, one of the main steps in conceptual design of a data warehouse is to detect the tables that model facts. However, this task may require a high level of expertise in the application domain, and is often tedious and time-consuming for designers. To overcome these problems, a comprehensive model-driven approach is presented in this paper to support designers in: (1) obtaining a CWM model of business-related relational tables, (2) determining which elements of this model can be considered as facts, and (3) deriving their counterparts in a multidimensional schema. Several heuristics
Andrea Carmè, Jose-Norberto Mazón, S
Added 08 Nov 2010
Updated 08 Nov 2010
Type Conference
Year 2010
Where DAWAK
Authors Andrea Carmè, Jose-Norberto Mazón, Stefano Rizzi
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