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Fuzzy Data Warehouse for Performance Analysis
Abstract
The numeric values retrieved from a data warehouse may be difficult to interpret by business users, or may be interpreted incorrectly. Therefore, for more accurate understanding of numeric values, business users may require an interpretation in meaningful, non-numeric terms. However, if the transition between non-numeric terms is crisp, true values cannot be measured, and smooth transition between classes may not take place. To address that problem, the authors employ a fuzzy classification-based approach for data warehouse. For that, they present a fuzzy data warehouse modeling approach, which allows integration of fuzzy concepts without affecting the core of a classical data warehouse. The essence of the approach is that a meta-tables structure is added for relating non-numeric terms with numeric values. This enables integration of fuzzy concepts in dimensions and facts, while preserving the time-invariability of the data warehouse. Additional to that, the use of fuzzy approach allows analysis of data in both sharp and fuzzy manners. The proposed approach is demonstrated through a case study of a movie rental company.
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