Fusion cubes: Towards self-service business intelligence

Alberto Abelló, Jérôme Darmont, Lorena Etcheverry, Matteo Golfarelli, Jose Norberto Mazón, Felix Naumann, Torben Bach Pedersen, Stefano Rizzi, Juan Trujillo, Panos Vassiliadis, Gottfried Vossen

Research output: Contribution to journalJournal articleResearchpeer-review

92 Citations (Scopus)

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.

Original languageEnglish
JournalInternational Journal of Data Warehousing and Mining
Volume9
Issue number2
Pages (from-to)66-88
Number of pages23
ISSN1548-3924
DOIs
Publication statusPublished - 1 Apr 2013

Keywords

  • Business Intelligence
  • Data Cube
  • Data Fusion
  • Data Integration
  • Data Warehouses
  • ETL
  • Metadata Discovery
  • Metadata Quality
  • Open Data
  • Schema Discovery

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