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dc.contributor.authorNimmagadda, Shastri
dc.date.accessioned2017-01-30T15:39:14Z
dc.date.available2017-01-30T15:39:14Z
dc.date.created2015-10-07T04:04:44Z
dc.date.issued2015
dc.identifier.citationNimmagadda, S. 2015. Data Warehousing for Mining of Heterogeneous Data Sources. Saarbrϋcken, Germany: Scholar's Press.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/48381
dc.description.abstract

With explosive growth and size of data sources, oil & gas exploration and production businesses face data and information overload. Due to voluminous heterogeneous and multidimensional data in multiple primary sources and company web servers, the oil & gas industry needs a robust and flexible database organization. To address the major issues, an integrated framework is articulated, incorporating domain and data modelling, schema design, data warehousing and mining and visualization and interpretation artefacts. Data warehouse, accommodating the comprehensive multidimensional domain-ontologies, facilitates the integration of data schemas from different knowledge domains. This integrated framework conforms the concept of a digital ecosystem that has further led to the development of a petroleum digital ecosystem (PDE). The artefacts are further extended to big data systems for data analytics and adding values to business. The holistic approach delivers an accurate and precise digital oil field information solution in multi-billion dollar projects in the upstream and integrated business environments. This book is an invaluable contribution for IS researchers and oil & gas explorers.

dc.publisherScholar's Press
dc.subjectMultidimensionality
dc.subjectData Warehousing
dc.subjectInterpretation
dc.subjectOil & Gas Data Sources
dc.subjectVisualization
dc.subjectMining
dc.subjectHeterogeneity
dc.titleData Warehousing for Mining of Heterogeneous Data Sources
dc.typeBook
dcterms.source.isbn978-3-639-76460-4
dcterms.source.placeGermany
curtin.departmentSchool of Information Systems
curtin.accessStatusFulltext not available


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