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A Data Warehouse Model for Integrating Fuzzy Concepts in Meta Table Structures

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2 Author(s)
Fasel, D. ; Dept. of Inf., Univ. of Fribourg, Fribourg, Switzerland ; Shahzad, K.

In classical data warehouses (DWH), classification of values takes place in a sharp manner, because of this true values cannot be measured and smooth transition between classes does not occur. In this paper, a fuzzy data warehouse (FDWH) modeling approach, which allows integration of fuzzy concepts without affecting the core of a DWH is presented. This is accomplished through the addition of a meta-table structure, which enables integration of fuzzy concepts on dimensions and facts, while preserving the time-invariability of the DWH and allowing analysis of data both sharp and fuzzy. A comparison to existing approaches for integrating fuzzy concepts in DWH is presented. Guidelines for modeling the fuzzy meta-tables and a meta-model for the FDWH are also outlined in this paper. The use of the proposed approach is demonstrated by a retail company example. Finally, a comparison of fuzzy and classical data warehousing approaches is presented.

Published in:

Engineering of Computer Based Systems (ECBS), 2010 17th IEEE International Conference and Workshops on

Date of Conference:

22-26 March 2010