Fusion Cubes: Towards Self-Service Business Intelligence

Abello A., Darmont J., Etcheverry L., Golfarelli M., Mazon J.N., Naumann F., Bach Pedersen T., Rizzi S., Trujillo J., Vassiliadis P., Vossen G.

Abstract
Self-service business intelligence is about enabling non-expert users to make well-informeddecisions by enriching the decision process with situational data, i.e., data that have a narrowfocus on a specific business problem and, typically, a short lifespan for a small group of users.Often, these data are not owned and controlled by the decision maker; their search, extraction,integration, and storage for reuse or sharing should be accomplished by decision makers withoutany intervention by designers or programmers. The goal of this paper is to present the frameworkwe envision to support self-service business intelligence and the related research challenges; theunderlying core idea is the notion of fusion cubes, i.e., multidimensional cubes that can bedynamically extended both in their schema and their instances, and in which situational data andmetadata are associated with quality and provenance annotations.

Keywords
Metadata discovery; metadata quality; schema discovery; data integration; data; warehouses; data cube; data fusion; business intelligence; ETL; open data