Model-driven reverse engineering for data warehouse design
Data warehouses integrate several operational sources to provide a multidimensional analysis of data, thus improving the decision making process. Therefore, an in-depth analysis of these data sources is crucial for data warehouse development. Traditionally, this analysis has been based on a set of i...
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| Veröffentlicht in: | Revista IEEE América Latina 2008-08, Vol.6 (4), p.317-323 |
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| container_title | Revista IEEE América Latina |
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| creator | Mazon, J.N. Trujillo, J. |
| description | Data warehouses integrate several operational sources to provide a multidimensional analysis of data, thus improving the decision making process. Therefore, an in-depth analysis of these data sources is crucial for data warehouse development. Traditionally, this analysis has been based on a set of informal guidelines or heuristics to support the manually discovery of multidimensional elements on a well-known documentation. Therefore, this task may become highly tedious and prone to fail. In this paper, MDA (Model Driven Architecture) is used to design a reverse engineering process in which the following tasks are performed (i) obtain a logical representation of data sources (ii) mark this logical representation with multidimensional concepts, and (iii) derive a conceptual multidimensional model from the marked model. |
| doi_str_mv | 10.1109/TLA.2008.4815284 |
| format | Article |
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| subjects | Data analysis data warehouse Data warehouses Decision making Documentation Guidelines MDA multidimensional modeling Multidimensional systems Reverse engineering Silicon compounds |
| title | Model-driven reverse engineering for data warehouse design |
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