Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/8763
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dc.contributor.authorPatel, Bhumi-
dc.date.accessioned2019-08-21T09:06:19Z-
dc.date.available2019-08-21T09:06:19Z-
dc.date.issued2017-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/8763-
dc.description.abstractThere are so many departments in hospital. Radiology is one of the department. It mainly works with the medical imaging technology. Radiology machines are used to perform scans on human body. This scans are performed by technologists. Results of this scans are stored as a DICOM image in PACS. Radiologist takes this DICOM images, observe them and then prepare a report which is used by the physicians. Radiology is one of the most revenue generating department of the hospital and resource utilization is one of the big challenge for this department. PMT is one which helps this department in resource utilization. PMT provides a UI which displays some default dashboards and give user privilage to create dashboards based on their roles. Philips is using many third party tools for PMT. BI tool, which philips is using, performs well for adhoc queries but the only problem with this tool is, it is very costly. So, our aim is to find a low cost alternative with the same performance. This BI tool uses in-chip technology which is new and no other tools are using it. Other BI tools like Tableau, QlikView uses in-memory technology. But still this tools are also costly. Low cost big data analytic solution for PMT is given in this report. For the demo purpose we will use any public dataset, for the data processing we will use spark SQL, for data caching we will use tachyon.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries15MCEC17;-
dc.subjectComputer 2015en_US
dc.subjectProject Report 2015en_US
dc.subjectComputer Project Reporten_US
dc.subjectProject Reporten_US
dc.subject15MCEen_US
dc.subject15MCECen_US
dc.subject15MCEC17en_US
dc.titleLow Cost Big Data Analytic Solution for PMTen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, CE

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