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Data Mining in Knowledge Management Processes: Developing an Implementing Framework

Analyzing a huge amount of data becomes a tricky challenge and an opportunity for data miners and businessmen today. Knowledge management processes can deal with big knowledge source to find tacit intelligence making businesses more agile and effective. Data mining is a powerful tool working with big data to create capabilities of forecasting and analysis. Yet there is a lack of research on where and how data mining can add value in knowledge management processes in organizations to maximize valuable knowledge for innovation and business management. The knowledge management processes of a psychiatry section in a Swedish hospital was used as a case study for this thesis. Interviews with manager, psychiatrist, auxiliary nurse and data scientists are conducted. Collected data is analyzed to create values of data mining based on a value creation framework through the knowledge management processes of psychiatry section in the hospital. Relying on this process, the limitations and strengths are exposed; whereby, a data mining implementing framework is formulated, and potentials of data mining for the process are suggested to support for all employees of psychiatry section in the hospital in decision making and caring for patients.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-149668
Date January 2018
CreatorsNguyen, Ngoc Buu Cat
PublisherUmeå universitet, Institutionen för informatik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationInformatik Student Paper Master (INFSPM) ; SPM 2018.09

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