COULIBALY, Fagnine Alassane; BIMONTE, Sandro; RIZZI, Stefano; MALEMBIC-MAHER, Sylvie; FABRE, Frédéric

Métadonnées

Afficher la notice complète

Licence d’utilisation du document

COULIBALY, Fagnine Alassane
Technologies et systèmes d'information pour les agrosystèmes [UR TSCF]

BIMONTE, Sandro
Technologies et systèmes d'information pour les agrosystèmes [UR TSCF]

RIZZI, Stefano
Dipartimento di Scienze dell'Informazione [Bologna] [DISI]
Alma Mater Studiorum Università di Bologna = University of Bologna [UNIBO]

Langue

Communication dans un congrès

Ce document a été publié dans

CEUR Workshop Proceedings, CEUR Workshop Proceedings, 2nd International Workshop on Data Platform Design, Management, and Optimization (DataPlat 2023), 2023-03-28, Ioannina. 2023, vol. 3379

Résumé en anglais

Information systems have evolved into complex data platforms supporting end-to-end data-intensive needs, aimed at coping with the different V's that characterize Big Data. In particular, multi-model databases (MMDBs) have been proposed to natively support storing and querying data in different (schemaless) models, so as to better handle Variety. In this work we envision a new data warehouse architecture in which an MMDB is used to enable on-the-fly user-driven extensions of multidimensional cubes with additional data, while ensuring support to variable and complex data and keeping the impact on ETL low. After proposing the architecture with the aid of a case study on the management of emerging plant disease, we discuss the main associated open issues.< Réduire

Mots clés

Entrepôt de Données

Base de données multi-modèle

OLAP

Données massives

Mots clés en anglais

Data Warehouses

Multi-model databases

OLAP

Big Data

Project ANR

Building epidemiological surveillance and prophylaxis with observations both near and distant - ANR-20-PCPA-0002

Origine

Importé de hal

Unités de recherche

Biologie du Fruit & Pathologie (BFP) - UMR 1332