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What is Dimension Matching

Handbook of Research on Organizational Transformations through Big Data Analytics
The process of identifying similar elements in two different and heterogeneous Data Warehouse dimensions.
Published in Chapter:
A Data Warehouse Integration Methodology in Support of Collaborating SMEs
Marius Octavian Olaru (University of Modena and Reggio Emilia, Italy) and Maurizio Vincini (University of Modena and Reggio Emilia, Italy)
DOI: 10.4018/978-1-4666-7272-7.ch014
Abstract
Collaborative business making is emerging as a possible solution for the difficulties that Small and Medium Enterprises (SMEs) are having in recent difficult economic scenarios. In fact, collaboration, as opposed to competition, may provide a competitive advantage to companies and organizations that operate in a joint business structure. When dealing with multiple organizations, managers must have access to unified strategic information obtained from the information repositories of each individual organization; unfortunately, traditional Business Intelligence (BI) tools are not designed with the aim of collaboration so the task becomes difficult from a managerial, organizational, and technological point of view. To deal with this shortcoming, the authors provide an integration, mapping-based, methodology for heterogeneous Data Warehouses that aims at facilitating business stakeholders' access to unified strategic information. A complete formalization, based on graph theory and the RELEVANT clustering approach, is provided. Furthermore, the authors perform an experimental evaluation of the proposed method by applying it over two DW instances.
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