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Journal article Open Access 2 Citations Peer Reviewed

QMBE: A Data Mining Language for Business Intelligence

Ana Azevedo , Manuel Filipe Santos
ISLA — Instituto Politécnico de Gestão e Tecnologia
International Journal of Data Mining and Warehousing, Volume 1, Issue 1, 2011, pp. 22–29

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Abstract
Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. BI is oriented to business activities. Over the past years, the evolution in this area has been considerable. Similarly, in the past years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but DM models are not directly accessible to business users, thus its power is not completely explored. This paper introduces a new DM language, named as QMBE that is iterative and interactive in nature and is also oriented to business activities. This paper suggests that the effective usage of DM in BI can be achieved by making DM models accessible to business users, through the use of the presented DM language.

Keywords

#Business intelligence #Data mining languages #Query-by-example #Business users #Relational calculus #Data mining models #Inductive databases #Data mining language

Bibliographic Details

Publication Type Journal article
Publication Year 2011
Journal / Conference / Work International Journal of Data Mining and Warehousing
ISSN 2249-3212
ISBN 978-1-60960-067-9
Volume / Issue Vol. 1 (1)
Pagination pp. 22–29
Publication Status Published

ISLA Authors & Affiliations

A
Ana Isabel Rojão Lourenço Azevedo
aazevedo@iscap.ipp.pt ID: D913-646F-CE08
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