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Business Intelligence Analysis, the New Role of Enhancing and Complementing the Internship of Students from Information Technology Program

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Advances in Artificial Intelligence, Software and Systems Engineering (AHFE 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 787))

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Abstract

Internship programs are a vital course for most study programs in terms of integrating and demonstrating the body of knowledge of the real professional work domain. Most schools adopt this program and give it a very high priority due to its significance and core value. However, internship program management consists of several components - especially the work performance of interns, which is one of the most crucial factors. Business Intelligence or BI can address this concern well with its analytical capability to provide multi-dimensional or multi-pivotal reports and highly responsive interaction to any query regarding an internship’s work performance. Moreover, it features adaptive visualization and provides many insightful strategies for interns, advisors and stakeholders enabling them to manage the work of interns in the organization more effectively. One current study is employing Business Intelligence software called Microsoft Power BI. This desktop platform has been handling sets of cumulative data for the past 5 years (from 2013 to 2017) involving 470 students in Information Technology programs. It illustrates graphical outputs in a dashboard format that processes raw data and transforms it into meaningful information and insightful strategies, respectively.

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Acknowledgments

This research was supported by Research and Development Institute, Suan Sunandha Rajabhat University.

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Correspondence to Shutchapol Chopvitayakun .

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Chopvitayakun, S. (2019). Business Intelligence Analysis, the New Role of Enhancing and Complementing the Internship of Students from Information Technology Program. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2018. Advances in Intelligent Systems and Computing, vol 787. Springer, Cham. https://doi.org/10.1007/978-3-319-94229-2_31

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