Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
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PLS Path Modeling to Investigate the Relations between Competencies of Data Scientist and Big Data Analysis Performance : Focused on Kaggle Platform

데이터 사이언티스트의 역량과 빅데이터 분석성과의 PLS 경로모형분석 : Kaggle 플랫폼을 중심으로

  • Han, Gyeong Jin (Management of Technology, Sungkyunkwan University) ;
  • Cho, Keuntae (Management of Technology, Sungkyunkwan University)
  • 한경진 (성균관대학교 기술경영학과) ;
  • 조근태 (성균관대학교 기술경영학과)
  • Received : 2015.07.16
  • Accepted : 2015.12.24
  • Published : 2016.04.15
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Abstract

This paper focuses on competencies of data scientists and behavioral intention that affect big data analysis performance. This experiment examined nine core factors required by data scientists. In order to investigate this, we conducted a survey to gather data from 103 data scientists who participated in big data competition at Kaggle platform and used factor analysis and PLS-SEM for the analysis methods. The results show that some key competency factors have influential effect on the big data analysis performance. This study is to provide a new theoretical basis needed for relevant research by analyzing the structural relationship between the individual competencies and performance, and practically to identify the priorities of the core competencies that data scientists must have.

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References

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