Assessment of Data Warehouse Model Quality

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Hunny Gaur
Rakhee, Rakhee


Data Warehouse (DW)is always used in making strategic decisions thus ensuring its quality is very much crucial for any organization. Data Warehouse consists of huge and unorganized data. The information in Data Warehouse is needed to make important decisions; its quality is thus a matter of concern. The Data Warehouse quality can be improved in many aspects for example it can be improved by improving the quality of information it holds, can be further improved by improving the data Warehouse design, here in this paper we have surveyed about the impact of conceptual model metrics on Data Warehouse quality. There have been so many approaches to design the Data Warehouse from the conceptual, logical, and physical perspectives. In our point of view there is lack of objective indicators to guide the designers in obtaining an outstanding model that allow us to guarantee the quality of the DW. However only M. Serrano and M. Piattini had provided a set of empirically validated metrics to help the designers. The paper summarizes the set of metrics defined for DW conceptual models and their formal and empirical validation to assure their correctness.

Keywords: Data Warehouse, Multidimensional Modeling, Conceptual Model, Metrics, UML.


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