Fusion Cubes

Author:

Abelló Alberto1,Darmont Jérôme2,Etcheverry Lorena3,Golfarelli Matteo4,Mazón Jose-Norberto5,Naumann Felix6,Pedersen Torben7,Rizzi Stefano Bach8,Trujillo Juan9,Vassiliadis Panos10,Vossen Gottfried11

Affiliation:

1. School of Informatics, Universitat Politècnica de Catalunya, Barcelona, Spain

2. Université de Lyon (Laboratoire ERIC), Lyon, France

3. Computer Science Institute, Universidad de la Republica, Montevideo, Uruguay

4. DISI – Department of Computer Science and Engineering, University of Bologna, Bologna, Italy

5. Department of Software and Computing Systems, Universitat d’Alicante, Alicante, Spain

6. Department of Information Systems, Hasso Plattner Institute, Potsdam, Germany

7. Department of Computer Science, Aalborg University, Aalborg, Denmark

8. Department of Computer Science and Engineering, Università di Bologna, Bologna, Italy

9. Department of Information Systems and Languages, Universitat d’Alicante, Alicante, Spain

10. Department of Computer Science, University of Ioannina, Ioannina, Greece

11. Department of Information Systems, Universität Münster, Münster, Germany

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.

Publisher

IGI Global

Subject

Hardware and Architecture,Software

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2. Situational Data Integration in Question Answering systems: a survey over two decades;Knowledge and Information Systems;2024-06-18

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4. Search Approach for External Data Sources for Data Warehouse Enrichment in Business Intelligence Context;2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA);2023-12-04

5. Hypernym and Hyponym Improve the Conformed Dimension Identification of Fusion Cube in Self-Service Business Intelligence;2023 8th International Conference on Information Technology and Digital Applications (ICITDA);2023-11-17

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