%A Faten Atigui
%A Franck Ravat
%A Jiefu Song
%A Olivier Teste
%A Gilles Zurfluh
%J International Journal of Decision Support System Technology
%T Facilitate effective decision-making by warehousing reduced data: is it feasible?
%X The authors' aim is to provide a solution for multidimensional data warehouse's reduction based on analysts' needs which will specify aggregated schema applicable over a period of time as well as retain only useful data for decision support. Firstly, they describe a conceptual modeling for multidimensional data warehouse. A multidimensional data warehouse's schema is composed of a set of states. Each state is defined as a star schema composed of one fact and its related dimensions. The derivation between states is carried out through combination of reduction operators. Secondly, they present a meta-model which allows managing different states of multidimensional data warehouse. The definition of reduced and unreduced multidimensional data warehouse schema can be carried out by instantiating the meta-model. Finally, they describe their experimental assessments and discuss their results. Evaluating their solution implies executing different queries in various contexts: unreduced single fact table, unreduced relational star schema, reduced star schema and reduced snowflake schema. The authors show that queries are more efficiently calculated within a reduced star schema.
%N 3
%K Multidimensional design - Data reduction - Experimental assessment
%P 36-64
%V 7
%D 2015
%I IGI Global
%L publications29412