• Title/Summary/Keyword: Intelligence Informaiotn Society

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A Study on the Necessary Factors to Establish for Public Institutions Big Data System (공공기관 빅데이터 시스템 구축 시 고려해야 할 측정항목에 관한 연구)

  • Lee, Gwang-Su;Kwon, Jungin
    • Journal of Digital Convergence
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    • v.19 no.10
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    • pp.143-149
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    • 2021
  • As the need to establish a big data system for rapid provision of big data and efficient management of resources has emerged due to rapid entry into the hyper-connected intelligence information society, public institutions are pushing to establish a big data system. Therefore, this study analyzed and combined the success factors of big data-related studies and the specific aspects of big data in public institutions based on the measurement of environmental factors for establishing an integrated information system for higher education institutions. In addition, 19 measurement items reflecting big data characteristics were derived from big data experts using brainstorming and Delphi methods, and a plan to successfully apply them to public institutions that want to build big data systems was proposed. We hope that this research results will be used as a foundation for the successful establishment of big data systems in public institutions.

A Study on the Success Model for the Establishment of Big Data System in Public Institutions (공공기관 빅데이터 시스템 구축을 위한 성공모형에 관한 연구)

  • Lee, Gwang-Su;Kwon, Jungin
    • Journal of Digital Convergence
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    • v.20 no.1
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    • pp.129-139
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    • 2022
  • This study aims to identify which factors affect successful big data system construction, identify the relationship between the factors, and identify the success model and success factors necessary for public institutions to build big data systems. Therefore, the preceding and related studies related to this study were reviewed, and success factors for the establishment of a big data system were derived based on this. As a research method, a survey was conducted on users of institutions that have established or planned to build a big data system, and a structural equation (AMOS) was conducted to verify the impact relationship between success factors. As a result of the analysis, organizational support factors, development support factors, user support factors, information quality, service quality, system quality, use, and net benefit were derived as success factors for building big data systems, and a success model was presented. This can be seen as significant and academic contributions in that it is the first study of the success model for building an information system reflecting big data characteristics, and it is expected that this study will be used as basic data for building a big data system in public institutions in the future.