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A Semi-Automatic Design Methodology for (Big) Data Warehouse Transforming Facts into Dimensions

Authors :
Ludovic Journaux
Lucile Sautot
Sandro Bimonte
Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS)
Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)
Technologies et systèmes d'information pour les agrosystèmes (UR TSCF)
Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)
Laboratoire d'Informatique de Bourgogne [Dijon] (LIB)
Université de Bourgogne (UB)
Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
AgroParisTech
ANR-17-CE04-0012,VGI4Bio,Méthodes d'analyse des indicateurs de biodiversité dans le contexte agricole centrés données et utilisateurs VGI(2017)
Source :
IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers, In press, ⟨10.1109/TKDE.2019.2925621⟩, IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers, 2021, 33 (1), pp.28-42. ⟨10.1109/TKDE.2019.2925621⟩
Publication Year :
2021
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2021.

Abstract

International audience; A decision support system is used by decision makers for a long time. But, in some cases, the originally designed multidimensional schema does not cover the entire needs of decision makers, which can change over time. One such unfulfilled needs, is using facts to describe dimension members. In this article, we propose a methodology to transform the constellation schema of a data warehouse by integrating factual data into a dimension. The proposed methodology and algorithms enrich a constellation multidimensional schema with new analytical possibilities for decision makers. This enrichment has repercussions for the entire multidimensional schema that are managed by multidimensional modeling, hierarchy calculation and the hierarchy version. In this article, we present a theoretical view of the proposed methodology supported by a case study, an implemented prototype and a complete evaluation based on a standard benchmark.

Details

ISSN :
23263865 and 10414347
Volume :
33
Database :
OpenAIRE
Journal :
IEEE Transactions on Knowledge and Data Engineering
Accession number :
edsair.doi.dedup.....d1c110b3fbb50b8cf83573d3e20149a3
Full Text :
https://doi.org/10.1109/tkde.2019.2925621