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dc.contributor.authorNimmagadda, Shastri
dc.contributor.authorDreher, Heinz
dc.date.accessioned2017-01-30T11:11:29Z
dc.date.available2017-01-30T11:11:29Z
dc.date.created2008-11-12T23:32:31Z
dc.date.issued2006
dc.identifier.citationNimmagadda, Shastri and Dreher, Heinz. 2006. : Mapping and modeling of oil and gas relational data objects for warehouse development and efficient data mining, International IEEE Conference on Industrial Informatics (INDIN), Aug 16 2006, pp. 1201-1206. Singapore: IEEE Computer Society Press.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/9244
dc.identifier.doi10.1109/INDIN.2006.275809
dc.description.abstract

Oil and gas industries archive volumes of heterogeneous data. These companies, by virtue of their diverse operations, comprise of complicated organizational structure. The nature of organizational set-up with several operational units, often results with communication barriers among operational units. In order to effectively and efficiently perform oil and gas company's business activities, the flow of data and information must be consistent and sharing among its units. In order to improve information sharing among oil and gas company's personnel, heterogeneous data from various sources are integrated. Data warehouse is a solution, in which, oil and gas data entities, identified as class objects, are used for multidimensional modeling. Relational data structures constructed using these class objects, are stored in a warehousing environment to minimize the complexity of heterogeneous data and enhances power of data integration and information sharing among different operational units.

dc.publisherIEEE Computer Society Press
dc.subjectrelational data objects
dc.subjectdata mining
dc.subjectwarehouse development
dc.subjectdata
dc.subjectmapping
dc.subjectmodelling
dc.subjectwarehouse
dc.subjectOLAP
dc.subjectoil and gas
dc.subjectoil
dc.subjectgas
dc.subjectdata warehouse
dc.subjectorganizational
dc.subjectmodeling
dc.titleMapping and modeling of oil and gas relational data objects for warehouse development and efficient data mining
dc.typeConference Paper
dcterms.source.startPage1201
dcterms.source.endPage1206
dcterms.source.titleProceedings of the 4th International IEEE Conference on Industrial Informatics (INDIN)
dcterms.source.seriesProceedings of the 4th International IEEE Conference on Industrial Informatics (INDIN)
dcterms.source.conferenceInternational IEEE Conference on Industrial Informatics (INDIN)
dcterms.source.conference-start-dateAug 16 2006
dcterms.source.conferencelocationSingapore
dcterms.source.placeUSA
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Copyright 2006 IEEE

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This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

curtin.departmentCentre for Extended Enterprises and Business Intelligence
curtin.identifierEPR-1544
curtin.accessStatusOpen access
curtin.facultyCurtin Business School


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