Title: Data warehousing and mining technologies for adaptability in turbulent resources business environments

Authors: Shastri L. Nimmagadda, Heinz Dreher

Addresses: School of Information Systems, Curtin Business School, Curtin University, Perth, WA, Australia. ' School of Information Systems, Curtin Business School, Curtin University, Perth, WA, Australia

Abstract: 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 business processes, 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.

Keywords: resources business data; data warehousing; data mining; turbulence; volatility; data modelling; resource demand; business resources.

DOI: 10.1504/IJBIDM.2011.039409

International Journal of Business Intelligence and Data Mining, 2011 Vol.6 No.2, pp.113 - 153

Published online: 22 Apr 2015 *

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