000			01978nam a2200277Ia 4500
003			OSt
005			20250711162917.0
008			220909b |||||||| |||| 00| 0 eng d
020			_a9783319042251
037			_cTextual
040			_aCSL _beng _cCSL
041			_aeng
084			_aB217:(D65,8(B)) Q4 _qCSL
100			_aFasel, Daniel _eAuthor. _9815415
245		0	_aFuzzy data warehousing for performance measurement _b: Concept and implementation
260			_aNew York : _bSpringer, _c2014.
300			_axxiv, 236p. _b; ill.
500			_aAppendices A-D195-230p.; Bibliography 231-236p.
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			_a Architectural overview _9815416
650			_a Fuzzy data warehouse _9815417
650			_a Movie rental company _9815418
650			_aData warehouse concepts _9815419
942			_hB217:(D65,8(B)) Q4 _cTEXL _2CC _n0
999			_c14661 _d14661