A Model-Driven Framework for Meta-Data Harmonization in Business Intelligence

Datasets obtained from different sources are often heterogeneous: they do not share a common internal structure, even though they are nominally about the same subject matter. This makes reporting against datasets difficult without laborious, manual efforts to clean and transform the data. This project will investigate the feasibility of an approach to abstract the harvesting […]

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