Differentiated Multiple Aggregations in Multidimensional Databases

Ali Hassan (1) , Franck Ravat (1, 2) , Olivier Teste (1, 3) , Ronan Tournier (1, 2) , Gilles Zurfluh (1, 2)

1 IRIT-SIG - Systèmes d’Informations Généralisées
2 UT Capitole - Université Toulouse Capitole
3 UT2J - Université Toulouse - Jean Jaurès

Many models have been proposed for modeling multidimensional data warehouse and most consider a same function to determine how measure values are aggregated according to different data detail levels. We provide a conceptual model that supports (1) multiple aggregations, associating to the same measure a different aggregation function according to analysis axes or hierarchies, and (2) differentiated aggregation, allowing specific aggregations at each detail level. Our model is based on a graphical formalism that allows controlling the validity of aggregation functions (distributive, algebraic or holistic). We also show how conceptual modeling can be used, in an R-OLAP environment, for building lattices of pre-computed aggregates.

Mots clés: Aggregation functions; Aggregate lattice; Multiple aggregations; Data warehouse; Conceptual modeling

Domaines: Théorie de l'information [cs.IT]; Recherche d'information [cs.IR]

Ali Hassan, Franck Ravat, Olivier Teste, Ronan Tournier, Gilles Zurfluh. Differentiated Multiple Aggregations in Multidimensional Databases. Transactions on Large-Scale Data- and Knowledge-Centered Systems, 2015, vol. 21, pp. 20-47. ⟨hal-01334717⟩