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Ontology-based platform for conceptual guided dataset analysis

Abstract:

Nowadays organizations should handle a huge amount of both internal and external data from structured, semi-structured, and unstructured sources. This constitutes a major challenge (and also an opportunity) to current Business Intelligence solutions. The complexity and effort required to analyse such plethora of data implies considerable execution times. Besides, the large number of data analysis methods and techniques impede domain experts (laymen from an IT-assisted analytics perspective) to fully exploit their potential, while technology experts lack the business background to get the proper questions. In this work, we present a semantically-boosted platform for assisting layman users in (i) extracting a relevant subdataset from all the data, and (ii) selecting the data analysis technique(s) best suited for scrutinising that subdataset. The outcome is getting better answers in significantly less time. The platform has been evaluated in the music domain with promising results.