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dc.contributor.authorNimmagadda, Shastri
dc.contributor.authorDreher, Heinz
dc.identifier.citationNimmagadda, Shastri L. and Dreher, Heinz. 2011. Data warehousing and mining technologies for adaptability in turbulent resources business environments. International Journal of Business Intelligence and Data Mining. 6 (2): pp. 113-153.

Resources businesses often undergo turbulent and volatile periods, due to rapid increase of resource demand and poorly organised resources data volumes. This volatile industry operates multifaceted business units that manage heterogeneous data sources. Data integration and interactive businessprocesses, distributed across complex business environments, need attention. Historical resources data, geographically (spatial dimension) archived for decades (periodic dimension), are source of analysing past business data dimensions and predicting their future turbulences. Periodic data, modelled in an integrated and robust warehouse environment, are explored using data mining methodologies. The data models presented, will optimise future inputs in the turbulent resources business environments.

dc.publisherInderscience Enterprises Limited
dc.subjectresources business data
dc.subjectdata mining
dc.subjectdata warehousing
dc.titleData warehousing and mining technologies for adaptability in turbulent resources business environments
dc.typeJournal Article
dcterms.source.titleInternational Journal of Business Intelligence and Data Mining
curtin.departmentSchool of Information Systems
curtin.accessStatusOpen access

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