Logical design of multi-model data warehouses
In: ISSN: 0219-1377, 2023
Online
academicJournal
Zugriff:
International audience ; Multi-model DBMSs, which support different data models with a fully integrated backend, have been shown to be beneficial to data warehouses and OLAP systems. Indeed, they can store data according to the multidimensional model and, at the same time, let each of its elements be represented through the most appropriate model. An open challenge in this context is the lack of methods for logical design. Indeed, in a multi-model context, several alternatives emerge for the logical representation of dimensions and facts. The goal of this paper is to devise a set of guidelines for the logical design of multi-model data warehouses so that the designer can achieve the best trade-off between features such as querying, storage, and ETL. To this end, for each model considered (relational, document-based, and graph-based) and for each type of multidimensional element (e.g., non-strict hierarchy) we propose some solutions and carry out a set of intra-model and inter-model comparisons. The resulting guidelines are then tested on a case study that shows all types of multidimensional elements.
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Logical design of multi-model data warehouses
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Autor/in / Beteiligte Person: | Bimonte, Sandro ; Gallinucci, Enrico ; Marcel, Patrick ; Rizzi, Stefano ; Technologies et systèmes d'information pour les agrosystèmes (UR TSCF) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) ; Department of Computer Science and Engineering Bologna (DISI) ; Alma Mater Studiorum Università di Bologna = University of Bologna (UNIBO) ; Laboratoire d'Informatique Fondamentale et Appliquée de Tours (LIFAT) ; Université de Tours (UT)-Institut National des Sciences Appliquées - Centre Val de Loire (INSA CVL) ; Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS) ; Université de Tours (UT) |
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Zeitschrift: | ISSN: 0219-1377, 2023 |
Veröffentlichung: | HAL CCSD ; Springer, 2023 |
Medientyp: | academicJournal |
DOI: | 10.1007/s10115-022-01788-0 |
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