RT Journal Article
SR 00
A1 Atigui, Faten
A1 Ravat, Franck
A1 Song, Jiefu
A1 Teste, Olivier
A1 Zurfluh, Gilles
T1 Facilitate effective decision-making by warehousing reduced data: is it feasible?
JF International Journal of Decision Support System Technology
YR 2015
FD 2015
VO 7
IS 3
SP 36
OP 64
K1 Multidimensional design - Data reduction - Experimental assessment
AB 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.
PB IGI Global
SN 1941-6296
LK https://publications.ut-capitole.fr/id/eprint/29412/