Fusion Cubes: Towards Self-Service Business Intelligence

Alberto Abelló, Jérôme Darmont, Lorena Etcheverry, Matteo Golfarelli, Jose-Norberto Mazón, Felix Naumann, Torben Pedersen, Stefano Bach Rizzi, Juan Trujillo, Panos Vassiliadis and Gottfried Vossen
Additional contact information
Alberto Abelló: School of Informatics, Universitat Politècnica de Catalunya, Barcelona, Spain
Jérôme Darmont: Université de Lyon (Laboratoire ERIC), Lyon, France
Lorena Etcheverry: Computer Science Institute, Universidad de la Republica, Montevideo, Uruguay
Matteo Golfarelli: DISI – Department of Computer Science and Engineering, University of Bologna, Bologna, Italy
Jose-Norberto Mazón: Department of Software and Computing Systems, Universitat d’Alicante, Alicante, Spain
Felix Naumann: Department of Information Systems, Hasso Plattner Institute, Potsdam, Germany
Torben Pedersen: Department of Computer Science, Aalborg University, Aalborg, Denmark
Stefano Bach Rizzi: Department of Computer Science and Engineering, Università di Bologna, Bologna, Italy
Juan Trujillo: Department of Information Systems and Languages, Universitat d’Alicante, Alicante, Spain
Panos Vassiliadis: Department of Computer Science, University of Ioannina, Ioannina, Greece
Gottfried Vossen: Department of Information Systems, Universität Münster, Münster, Germany

International Journal of Data Warehousing and Mining (IJDWM), 2013, vol. 9, issue 2, 66-88

Abstract: Self-service business intelligence is about enabling non-expert users to make well-informed decisions by enriching the decision process with situational data, i.e., data that have a narrow focus 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 without any intervention by designers or programmers. The goal of this paper is to present the framework we envision to support self-service business intelligence and the related research challenges; the underlying core idea is the notion of fusion cubes, i.e., multidimensional cubes that can be dynamically extended both in their schema and their instances, and in which situational data and metadata are associated with quality and provenance annotations.

Date: 2013
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