Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/6681
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dc.contributor.authorPujara, Aarohi-
dc.date.accessioned2016-07-20T07:55:22Z-
dc.date.available2016-07-20T07:55:22Z-
dc.date.issued2016-06-01-
dc.identifier.urihttp://hdl.handle.net/123456789/6681-
dc.description.abstractA decision-making process is a consequential process for any organization; decisions made by Business Leaders, Program/Project Managers or higher authority executives are very crucial for the prosperity of any organization. Business direction, time saving , efficient storage and effort saving are the key outcome achievable by converting un- processed data to information and insights. This Project aims to converting real-time raw data into consequential and subsidiary information for business analysis motive.For optimal decision making graphical representation render various report aspects like Risk Involved, Bugs (open, incoming, age of bug, bench-marking), Defects, Issues, Product Change Requests (PCRs)/ Design change request, Org Learning, Schedule tracking etc. These reports are useful for Business Leaders, analysts and Program/Project Managers to improve decision making, bringing predictability, identifying new opportunity, increase accuracy and timeliness of project / program execution.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries14MCEI19;-
dc.subjectComputer 2014en_US
dc.subjectProject Report 2014en_US
dc.subjectComputer Project Reporten_US
dc.subjectProject Reporten_US
dc.subject14MCEIen_US
dc.subject14MCEI19en_US
dc.subjectINSen_US
dc.subjectINS 2014en_US
dc.subjectCE (INS)en_US
dc.titlePredictive and Optimal Decision Making for Intel's Global Business Units with ETL Processed Data using MSBIen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, CE (INS)

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