%0 Journal Article
%T Business Intelligence for Small and Middle-Sized Entreprises
%+ Equipe de Recherche en Ingénierie des Connaissances (ERIC)
%+ Kharkov National University
%A Grabova, Oksana
%A Darmont, Jérôme
%A Chauchat, Jean-Hugues
%A Zolotaryova, Iryna
%< avec comité de lecture
%Z ERIC:10-022
%@ 0163-5808
%J SIGMOD record
%I ACM
%V 39
%N 2
%P 39-50
%8 2010-06
%D 2010
%Z 1102.0115
%R 10.1145/1893173.1893180
%K Business Intelligence
%K Small and Middle-sized Enterprises
%K Web-based DataWarehouses
%K Main Memory Databases
%K On-line Analytical Processing
%K Business Intelligence
%Z Computer Science [cs]/Databases [cs.DB]Journal articles
%X Data warehouses are the core of decision support sys- tems, which nowadays are used by all kind of enter- prises 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 ex- isting solutions and approaches, which are appropriate for large-scaled enterprises, but are inadequate for small and middle-sized enterprises. Small enterprises require cheap, lightweight architec- tures and tools (hardware and software) providing on- line 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 re- view in-memory processing. Consequently, this paper discusses the existing approa- ches and tools working in main memory and/or with web interfaces (including freeware tools), relevant for small and middle-sized enterprises in decision making.
%G English
%2 https://hal.science/hal-00560976/document
%2 https://hal.science/hal-00560976/file/article.pdf
%L hal-00560976
%U https://hal.science/hal-00560976
%~ UNIV-LYON2
%~ ERIC
%~ LABEXIMU
%~ UDL