Atigui, Faten, Ravat, Franck, Song, Jiefu, Teste, Olivier and Zurfluh, Gilles (2015) Facilitate effective decision-making by warehousing reduced data: is it feasible? International Journal of Decision Support System Technology, 7 (3). pp. 36-64.

Full text not available from this repository.


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.

Item Type: Article
Language: English
Date: 2015
Refereed: Yes
Uncontrolled Keywords: Multidimensional design - Data reduction - Experimental assessment
Divisions: Institut de Recherche en Informatique de Toulouse
Site: UT1
Date Deposited: 26 Mar 2019 13:10
Last Modified: 02 Apr 2021 15:59
View Item