000 02895nam a22005055i 4500
003 DE-He213
005 20151013141910.0
007 cr nn 008mamaa
008 140228s2014 gw | s |||| 0|eng d
020 _a9783319042268
_9978-3-319-04226-8
024 7 _a10.1007/978-3-319-04226-8
_2doi
050 4 _aHF54.5-54.56
072 7 _aKJQ
_2bicssc
072 7 _aUF
_2bicssc
072 7 _aBUS083000
_2bisacsh
072 7 _aCOM039000
_2bisacsh
082 0 4 _a650
_223
100 1 _aFasel, Daniel.
_eauthor.
245 1 0 _aFuzzy Data Warehousing for Performance Measurement
_h[electronic resource] :
_bConcept and Implementation /
_cby Daniel Fasel.
260 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXXIV, 236 p. 109 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aFuzzy Management Methods,
_x2196-4130
505 0 _aIntroduction -- Fundamental Concepts -- Fuzzy Data Warehouse -- Application of Fuzzy Data Warehouse -- Implementation -- Evaluation and Conclusion.
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.
650 0 _aEconomics.
650 0 _aInformation systems.
650 0 _aData mining.
650 0 _aManagement information systems.
650 1 4 _aEconomics/Management Science.
650 2 4 _aBusiness Information Systems.
650 2 4 _aInformation Systems and Communication Service.
650 2 4 _aData Mining and Knowledge Discovery.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319042251
830 0 _aFuzzy Management Methods,
_x2196-4130
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-04226-8
912 _aZDB-2-SBE
942 _2ddc
_cEBOOK
999 _c2990
_d2990