A Unified Approach to Multisource Data Analyses

Franck Ravat (1, 2) , Jiefu Song (1)

1 IRIT-SIG - Systèmes d’Informations Généralisées
2 UT Capitole - Université Toulouse Capitole

Classically, Data Warehouses (DWs) supports business analyses on data coming from the inside of an organization. Nevertheless, Lined Open Data (LOD) might sensibly complete these business analyses by providing complementary perspectives during a decision-making pro-cess. In this paper, we propose a conceptual modeling solution, named Unified Cube, which blends together multidimensional data from DWs and LOD datasets without materializing them in a stationary repository. We complete the conceptual modeling with an implementation frame-work which manages the relations between a Unified Cube and multiple data sources at both schema and instance levels. We also propose an analysis processing process which queries different sources in a transparent way to decision-makers. The practical value of our proposal is illustrated through real-world data and benchmarks.

Mots clés: Experimental assessments; Data warehouse; Linked open data; Conceptual modeling; Multisource analyses

Domaines: Modélisation et simulation

Franck Ravat, Jiefu Song. A Unified Approach to Multisource Data Analyses. Fundamenta Informaticae, 2018, 162 (4), pp.311-359. ⟨10.3233/FI-2018-1727⟩. ⟨hal-02348263⟩