Following recent trends in Data Warehousing, companies realized that there is a great potential in combining their information repositories to obtain a broader view of the economical market. Unfortunately, even though Data Warehouse (DW) integration has been defined from a theoretical point of view, until now no complete, widely used methodology has been proposed to support the integration of the information coming from heterogeneous DWs. This paper deals with the automatic integration of dimensional attributes from heterogeneous DWs. A method relying on topological properties that similar dimensions maintain is proposed for discovering mappings of dimensions, and a technique based on clustering algorithms is introduced for integrating the data associated to the dimensions.
Mapping and Integration of Dimensional Attributes Using Clustering Techniques / Guerra, Francesco; Marius Octavian, Olaru; Vincini, Maurizio. - STAMPA. - 123:(2012), pp. 38-49. (Intervento presentato al convegno 13th International Conference on Electronic -Commerce and Web Technologies, EC-Web 2012 tenutosi a Vienna, aut nel September 4-5, 2012) [10.1007/978-3-642-32273-0_4].
Mapping and Integration of Dimensional Attributes Using Clustering Techniques.
GUERRA, Francesco;VINCINI, Maurizio
2012
Abstract
Following recent trends in Data Warehousing, companies realized that there is a great potential in combining their information repositories to obtain a broader view of the economical market. Unfortunately, even though Data Warehouse (DW) integration has been defined from a theoretical point of view, until now no complete, widely used methodology has been proposed to support the integration of the information coming from heterogeneous DWs. This paper deals with the automatic integration of dimensional attributes from heterogeneous DWs. A method relying on topological properties that similar dimensions maintain is proposed for discovering mappings of dimensions, and a technique based on clustering algorithms is introduced for integrating the data associated to the dimensions.
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