000698103 000__ 02636cam\a2200445Ii\4500 000698103 001__ 698103 000698103 005__ 20230306135812.0 000698103 006__ m\\\\\o\\d\\\\\\\\ 000698103 007__ cr\cnu|||unuuu 000698103 008__ 140508s2014\\\\sz\a\\\\ob\\\\000\0\eng\d 000698103 019__ $$a878559600 000698103 020__ $$a9783319042268 $$qelectronic book 000698103 020__ $$a3319042262 $$qelectronic book 000698103 020__ $$z9783319042251 000698103 0247_ $$a10.1007/978-3-319-04226-8$$2doi 000698103 035__ $$aSP(OCoLC)ocn879377346 000698103 035__ $$aSP(OCoLC)879377346$$z(OCoLC)878559600 000698103 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dCOO 000698103 049__ $$aISEA 000698103 050_4 $$aQA76.9.D37 000698103 08204 $$a005.74/5$$223 000698103 1001_ $$aFasel, Daniel,$$eauthor. 000698103 24510 $$aFuzzy data warehousing for performance measurement$$h[electronic resource] :$$bconcept and implementation /$$cDaniel Fasel. 000698103 264_1 $$aCham :$$bSpringer,$$c2014. 000698103 300__ $$a1 online resource (xxiv, 236 pages) :$$billustrations. 000698103 336__ $$atext$$btxt$$2rdacontent 000698103 337__ $$acomputer$$bc$$2rdamedia 000698103 338__ $$aonline resource$$bcr$$2rdacarrier 000698103 4901_ $$aFuzzy Management Methods,$$x2196-4130 000698103 504__ $$aIncludes bibliographical references. 000698103 506__ $$aAccess limited to authorized users. 000698103 520__ $$aThe numeric values retrieved from a data warehouse may be difficult for business users to interpret, and may even be interpreted incorrectly. Therefore, in order to better understand 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 no longer be possible.This book addresses this problem by presenting a fuzzy classification-based approach for a data warehouses. Moreover, it introduces a modeling approach for fuzzy data warehouses that makes it possible to integrate fuzzy linguistic variables in a meta-table structure. The essence of this structure is that fuzzy concepts can be integrated into the dimensions and facts of an existing classical data warehouse without affecting its core. This allows a simultaneous analysis, both fuzzy and crisp. A case study of a movie rental company underlines and exemplifies the proposed approach. 000698103 588__ $$aDescription based on online resource; title from PDF title page (SpringerLink, viewed May 8, 2014). 000698103 650_0 $$aData warehousing. 000698103 650_0 $$aFuzzy systems. 000698103 830_0 $$aFuzzy management methods,$$x2196-4130 000698103 852__ $$bebk 000698103 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://dx.doi.org/10.1007/978-3-319-04226-8$$zOnline Access 000698103 909CO $$ooai:library.usi.edu:698103$$pGLOBAL_SET 000698103 980__ $$aEBOOK 000698103 980__ $$aBIB 000698103 982__ $$aEbook 000698103 983__ $$aOnline 000698103 994__ $$a92$$bISE