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Data Analytics and Visualization to Support Library Decisions

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dc.contributor.advisor Anutariya, Chutiporn Dr.
dc.contributor.author Karna, Neha Ms.
dc.contributor.other Dailey, Matthew N. Prof.
dc.contributor.other Esichaikul, Vatcharapon Dr.
dc.date.accessioned 2020-08-14T03:52:18Z
dc.date.available 2020-08-14T03:52:18Z
dc.date.issued 2020-08-14
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/983
dc.description.abstract Data analytics in libraries have been increased in fields like medicine, politics, tourism, etc. But compared to other fields, data analytics in libraries have been falling behind. Data analytics in the library has been a relatively new domain in academic libraries. Within time, the libraries have accumulated large amounts of data related to patrons, books, digital libraries for years. Despite the availability of data and the benefits of using data analytics in libraries, library analytics has still a huge scope. Thus, this study focuses on detailed data analytics and different techniques used for data analytics. This study discusses the previous research done using data mining techniques in academic libraries. It discusses the decisions made in the library in different four sections and by three levels of management in the library. The study explores the use of descriptive analytics as a library dashboard and predictive analytics to analyze the acquisition purchase in academic libraries. The dashboard provides us the scope to explore the digital management of the library. Also, the dashboard for library visits helps to explore the patrons visiting the library. These analyses support library decisions directly or indirectly. We have used the third-party software Google Data Studio for the descriptive analytics. en_US
dc.language.iso en_US en_US
dc.title Data Analytics and Visualization to Support Library Decisions en_US
dc.type Thesis en_US

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