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A Unified Approach to Multisource Data Analyses
Author(s) -
Franck Ravat,
Jiefu Song
Publication year - 2018
Publication title -
fundamenta informaticae
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.311
H-Index - 67
eISSN - 1875-8681
pISSN - 0169-2968
DOI - 10.3233/fi-2018-1727
Subject(s) - data warehouse , data cube , computer science , online analytical processing , schema (genetic algorithms) , data mining , cube (algebra) , process (computing) , data science , dimensional modeling , business intelligence , information retrieval , programming language , mathematics , combinatorics
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.

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