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dc.contributor.advisorDessureault, Seanen
dc.contributor.advisorPoulton, Maryen
dc.contributor.authorRogers, William Pratt
dc.creatorRogers, William Pratten
dc.date.accessioned2016-01-22T22:21:58Zen
dc.date.available2016-01-22T22:21:58Zen
dc.date.issued2015en
dc.identifier.urihttp://hdl.handle.net/10150/594674en
dc.description.abstractMost large contemporary mines already have considerable amounts of data, much of which goes largely unused. The key challenge in big data is increasing data utilization. Much of the data in the mine (not plant) come from a variety of systems, each with different databases and reporting environments. Standard technology deployments create a "silo-ification" of data leading to poor system usage. Through modern server monitoring, data utilization can quantifiably be measured. A host of other quantifiable, often automated approaches, to measuring data use and value can also be incorporated as a means of monitoring value generation. A data valuation tool is presented to measure the data assets at an operation. The Data Value Index (DVI) quantifies business intelligence best practices and user interaction considering managerial flexibility and data utilization rates. The DVI is built considering many case studies of data warehousing at various mining companies, some of which will be presented.
dc.language.isoen_USen
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.subjectData Utilizationen
dc.subjectmining technologyen
dc.subjectUse of data warehousesen
dc.subjectMining Geological & Geophysical Engineeringen
dc.subjectBusiness Intelligenceen
dc.titleFormal Assessment and Measurement of Data Utilization and Value for Minesen_US
dc.typetexten
dc.typeElectronic Dissertationen
thesis.degree.grantorUniversity of Arizonaen
thesis.degree.leveldoctoralen
dc.contributor.committeememberDessureault, Seanen
dc.contributor.committeememberPoulton, Maryen
dc.contributor.committeememberKemeny, Johnen
dc.contributor.committeememberMomayez, Moeen
dc.description.releaseRelease 24-Nov-2016en
thesis.degree.disciplineGraduate Collegeen
thesis.degree.disciplineMining Geological & Geophysical Engineeringen
thesis.degree.namePh.D.en
refterms.dateFOA2016-11-24T00:00:00Z
html.description.abstractMost large contemporary mines already have considerable amounts of data, much of which goes largely unused. The key challenge in big data is increasing data utilization. Much of the data in the mine (not plant) come from a variety of systems, each with different databases and reporting environments. Standard technology deployments create a "silo-ification" of data leading to poor system usage. Through modern server monitoring, data utilization can quantifiably be measured. A host of other quantifiable, often automated approaches, to measuring data use and value can also be incorporated as a means of monitoring value generation. A data valuation tool is presented to measure the data assets at an operation. The Data Value Index (DVI) quantifies business intelligence best practices and user interaction considering managerial flexibility and data utilization rates. The DVI is built considering many case studies of data warehousing at various mining companies, some of which will be presented.


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