Ontology based data warehousing for mining of heterogeneous and multidimensional data sources
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 da...
| Main Author: | |
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| Format: | Thesis |
| Language: | English |
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Curtin University
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/2322 |
| _version_ | 1848743922290917376 |
|---|---|
| author | Nimmagadda, Shastri Lakshman |
| author_facet | Nimmagadda, Shastri Lakshman |
| author_sort | Nimmagadda, Shastri Lakshman |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T05:53:16Z |
| format | Thesis |
| id | curtin-20.500.11937-2322 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T05:53:16Z |
| publishDate | 2015 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-23222017-02-20T06:38:10Z Ontology based data warehousing for mining of heterogeneous and multidimensional data sources Nimmagadda, Shastri Lakshman 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. 2015 Thesis http://hdl.handle.net/20.500.11937/2322 en Curtin University fulltext |
| spellingShingle | Nimmagadda, Shastri Lakshman Ontology based data warehousing for mining of heterogeneous and multidimensional data sources |
| title | Ontology based data warehousing for mining of heterogeneous and multidimensional data sources |
| title_full | Ontology based data warehousing for mining of heterogeneous and multidimensional data sources |
| title_fullStr | Ontology based data warehousing for mining of heterogeneous and multidimensional data sources |
| title_full_unstemmed | Ontology based data warehousing for mining of heterogeneous and multidimensional data sources |
| title_short | Ontology based data warehousing for mining of heterogeneous and multidimensional data sources |
| title_sort | ontology based data warehousing for mining of heterogeneous and multidimensional data sources |
| url | http://hdl.handle.net/20.500.11937/2322 |