A Data Warehouse Model for Integrating Fuzzy Concepts in Meta Table Structures
2010 (English)In: 17th- International Conference on Engineering of Computer-Based Systems, IEEE , 2010Conference paper (Other academic)
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 ware- house (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. Guide- lines 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.
Place, publisher, year, edition, pages
IEEE , 2010.
Research subject Computer and Systems Sciences
IdentifiersURN: urn:nbn:se:su:diva-51831ISBN: 978-0-7695-4005-4OAI: oai:DiVA.org:su-51831DiVA: diva2:386291