TY - JOUR
T1 - Ontology-based integration of business intelligence
AU - Cao, Longbing
AU - Zhang, Chengqi
AU - Liu, Jiming
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2006
Y1 - 2006
N2 - The integration of Business Intelligence (BI) has been taken bybusiness decision-makers as an effective means to enhance enterprise "soft power" and added value in the reconstruction and revolution oftraditional industries. The existing solutions based on structuralintegration are to pack together data warehouse (DW), OLAP, data mining(DM) and reporting systems from different vendors. BI system users arefinally delivered a reporting system in which reports, data models,dimensions and measures are predefined by system designers. As aresult of a survey in the US, 85% of DW projects based on the above solutions failed to meet their intended objectives. In this paper, wesummarize our investigation on the integration of BI on the basis ofsemantic integration and structural interaction. Ontology-basedintegration of BI is discussed for semantic interoperability inintegrating DW, OLAP and DM. A hybrid ontological structure isintroduced which includes conceptual view, analytical view and physicalview. These views are matched with user interfaces, DW and enterpriseinformation systems, respectively. Relevant ontological engineeringtechniques are developed for ontology namespace, semantic relationships,and ontological transformation, mapping and query in this ontologicalspace. The approach is promising for business-oriented, adaptive andautomatic integration of BI in the real world. Operational decisionmaking experiments within a telecom company have demonstrated that a BI system utilizing the proposed approach is more flexible.
AB - The integration of Business Intelligence (BI) has been taken bybusiness decision-makers as an effective means to enhance enterprise "soft power" and added value in the reconstruction and revolution oftraditional industries. The existing solutions based on structuralintegration are to pack together data warehouse (DW), OLAP, data mining(DM) and reporting systems from different vendors. BI system users arefinally delivered a reporting system in which reports, data models,dimensions and measures are predefined by system designers. As aresult of a survey in the US, 85% of DW projects based on the above solutions failed to meet their intended objectives. In this paper, wesummarize our investigation on the integration of BI on the basis ofsemantic integration and structural interaction. Ontology-basedintegration of BI is discussed for semantic interoperability inintegrating DW, OLAP and DM. A hybrid ontological structure isintroduced which includes conceptual view, analytical view and physicalview. These views are matched with user interfaces, DW and enterpriseinformation systems, respectively. Relevant ontological engineeringtechniques are developed for ontology namespace, semantic relationships,and ontological transformation, mapping and query in this ontologicalspace. The approach is promising for business-oriented, adaptive andautomatic integration of BI in the real world. Operational decisionmaking experiments within a telecom company have demonstrated that a BI system utilizing the proposed approach is more flexible.
KW - Business intelligence
KW - Ontological engineering
KW - Ontology
UR - http://www.scopus.com/inward/record.url?scp=33745664691&partnerID=8YFLogxK
UR - https://content.iospress.com/articles/web-intelligence-and-agent-systems-an-international-journal/wia00093
M3 - Journal article
AN - SCOPUS:33745664691
SN - 1570-1263
VL - 4
SP - 313
EP - 325
JO - Web Intelligence and Agent Systems
JF - Web Intelligence and Agent Systems
IS - 3
ER -