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The numeric values retrieved from a data warehouse may be difficult to interpret by business users. They may be even interpreted incorrectly. Therefore, for a 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 a smooth transition between classes may not take place. This book addresses this problem by presenting a fuzzy classification-based approach for a data warehouse. Moreover, it introduces as well a modelling approach for fuzzy data warehouses that allows to integrate fuzzy linguistic variables in a meta-table structure. The essence of this structure is that fuzzy concepts can be integrated in the dimensions and facts of an existing classical data warehouse without affecting the core of the data warehouse. This allows for a simultaneous analysis, both fuzzy and crisp. A case study of a movie rental company underlines and exemplifies the proposed approach.
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