Business intelligence for small and middle-sized entreprises

  • Authors:
  • Oksana Grabova;Jerome Darmont;Jean-Hugues Chauchat;Iryna Zolotaryova

  • Affiliations:
  • University of Lyon (ERIC Lyon2), Bron Cedex, France;University of Lyon (ERIC Lyon2), Bron Cedex, France;University of Lyon (ERIC Lyon2), Bron Cedex, France;Kharkiv National University of Economics, Kharkov, Ukraine

  • Venue:
  • ACM SIGMOD Record
  • Year:
  • 2010

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Abstract

Data warehouses are the core of decision support systems, which nowadays are used by all kind of enterprises in the entire world. Although many studies have been conducted on the need of decision support systems (DSSs) for small businesses, most of them adopt existing solutions and approaches, which are appropriate for large-scaled enterprises, but are inadequate for small and middle-sized enterprises. Small enterprises require cheap, lightweight architectures and tools (hardware and software) providing online data analysis. In order to ensure these features, we review web-based business intelligence approaches. For real-time analysis, the traditional OLAP architecture is cumbersome and storage-costly; therefore, we also review in-memory processing. Consequently, this paper discusses the existing approaches and tools working in main memory and/or with web interfaces (including freeware tools), relevant for small and middle-sized enterprises in decision making.