Ontology based data warehousing for mining of heterogeneous and multidimensional data sources
dc.contributor.author | Nimmagadda, Shastri Lakshman | |
dc.contributor.supervisor | Prof Heinz Dreher | |
dc.contributor.supervisor | Dr Douglas Atkinson | |
dc.contributor.supervisor | Dr Ananda Jeeva | |
dc.date.accessioned | 2017-01-30T10:20:25Z | |
dc.date.available | 2017-01-30T10:20:25Z | |
dc.date.created | 2015-06-23T01:57:34Z | |
dc.date.issued | 2015 | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/2322 | |
dc.description.abstract |
Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals. | |
dc.language | en | |
dc.publisher | Curtin University | |
dc.title | Ontology based data warehousing for mining of heterogeneous and multidimensional data sources | |
dc.type | Thesis | |
dcterms.educationLevel | PhD | |
curtin.department | School of Information Systems, Curtin Business School | |
curtin.accessStatus | Open access |