On designing multidimensional oil and gas business data structures for effective data warehousing and mining

Incomplete, improper and untimely information flow among operational units makes operations untidy and slow. Representing petroleum business data in multidimensional data structuring in a data warehousing environment is a solution for a manager?s strategic planning, and operationalmanagement. Concep...

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Main Authors: Nimmagadda, Shastri, Dreher, Heinz
Other Authors: Chang, E.
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers (IEEE) Industrial Electronics Society 2009
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/39557
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author Nimmagadda, Shastri
Dreher, Heinz
author2 Chang, E.
author_facet Chang, E.
Nimmagadda, Shastri
Dreher, Heinz
author_sort Nimmagadda, Shastri
building Curtin Institutional Repository
collection Online Access
description Incomplete, improper and untimely information flow among operational units makes operations untidy and slow. Representing petroleum business data in multidimensional data structuring in a data warehousing environment is a solution for a manager?s strategic planning, and operationalmanagement. Conceptual multidimensional-relational (MR) and EMR (extended multidimensional-relationships) data mapping approaches are proposed for key exploration industry data management. These conceptual models facilitate in developing future implementation data models and help anexploration data analyst, for better understanding of data integration and effective data mining.
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format Conference Paper
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T08:59:14Z
publishDate 2009
publisher Institute of Electrical and Electronics Engineers (IEEE) Industrial Electronics Society
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-395572022-12-09T07:12:33Z On designing multidimensional oil and gas business data structures for effective data warehousing and mining Nimmagadda, Shastri Dreher, Heinz Chang, E. Damiani, E. Hussain, F.K. multidimensional and extended multidimensional data - modelling Exploration industry business data dimensions Incomplete, improper and untimely information flow among operational units makes operations untidy and slow. Representing petroleum business data in multidimensional data structuring in a data warehousing environment is a solution for a manager?s strategic planning, and operationalmanagement. Conceptual multidimensional-relational (MR) and EMR (extended multidimensional-relationships) data mapping approaches are proposed for key exploration industry data management. These conceptual models facilitate in developing future implementation data models and help anexploration data analyst, for better understanding of data integration and effective data mining. 2009 Conference Paper http://hdl.handle.net/20.500.11937/39557 Institute of Electrical and Electronics Engineers (IEEE) Industrial Electronics Society restricted
spellingShingle multidimensional and extended multidimensional data - modelling
Exploration industry
business data dimensions
Nimmagadda, Shastri
Dreher, Heinz
On designing multidimensional oil and gas business data structures for effective data warehousing and mining
title On designing multidimensional oil and gas business data structures for effective data warehousing and mining
title_full On designing multidimensional oil and gas business data structures for effective data warehousing and mining
title_fullStr On designing multidimensional oil and gas business data structures for effective data warehousing and mining
title_full_unstemmed On designing multidimensional oil and gas business data structures for effective data warehousing and mining
title_short On designing multidimensional oil and gas business data structures for effective data warehousing and mining
title_sort on designing multidimensional oil and gas business data structures for effective data warehousing and mining
topic multidimensional and extended multidimensional data - modelling
Exploration industry
business data dimensions
url http://hdl.handle.net/20.500.11937/39557