During the last decades, the Data Warehouse has been one of the main components of a Decision Support System (DSS) inside a company. Given the great diffusion of Data Warehouses nowadays, managers have realized that there is a great potential in combining information coming from multiple information sources, like heterogeneous Data Warehouses from companies operating in the same sector. Existing solutions rely mostly on the Extract-Transform-Load (ETL) approach, a costly and complex process. The process of Data Warehous integration can be greatly simplified by developing a method that is able to semi-automatically discover semantic relationships among attributes of two or more different, heterogeneous Data Warehouse schemas. In this paper, we propose a method for the semi-automatic discovery of mappings between dimension hierarchies of heterogeneous Data Warehouses. Our approach exploits techniques from the Data Integration research area by combining topological properties of dimensions and semantic techniques.
Dimension matching in Peer-to-Peer Data Warehousing / Bergamaschi, Sonia; Marius Octavian, Olaru; Sorrentino, Serena; Vincini, Maurizio. - STAMPA. - 238:(2012), pp. 149-160. ((Intervento presentato al convegno Fusing Decision Support Systems into the Fabric of the Context tenutosi a Anávissos, Greece nel 28-30 june, 2012 [10.3233/978-1-61499-073-4-149].
Dimension matching in Peer-to-Peer Data Warehousing
BERGAMASCHI, Sonia;SORRENTINO, Serena;VINCINI, Maurizio
2012-01-01
Abstract
During the last decades, the Data Warehouse has been one of the main components of a Decision Support System (DSS) inside a company. Given the great diffusion of Data Warehouses nowadays, managers have realized that there is a great potential in combining information coming from multiple information sources, like heterogeneous Data Warehouses from companies operating in the same sector. Existing solutions rely mostly on the Extract-Transform-Load (ETL) approach, a costly and complex process. The process of Data Warehous integration can be greatly simplified by developing a method that is able to semi-automatically discover semantic relationships among attributes of two or more different, heterogeneous Data Warehouse schemas. In this paper, we propose a method for the semi-automatic discovery of mappings between dimension hierarchies of heterogeneous Data Warehouses. Our approach exploits techniques from the Data Integration research area by combining topological properties of dimensions and semantic techniques.
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