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Training path of big data management and application talents based on BERTopic-TOPSIS model

Author

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  • Yan Li
  • Tao Huang
  • Xiang Li

Abstract

This study examines the discrepancy between big data talent training and industry demand. The study analyzed 85 training programs and over 10,000 job postings from two job boards in China (51job and Zhaopin). Using content analysis, social network analysis, and the BERTopic-TOPSIS model, it mined implicit information from training programs and labeled key competencies in job descriptions. A key finding was a significant supply-demand misalignment: while “data application ability” was a stated goal in 52% of programs, only 11% of graduation requirements specified concrete, measurable skills to achieve it. The study identified three primary employment pathways for big data management and application majors: data management, data analysis, and data platform development. Institutions such as Peking University and Hefei University of Technology were identified as best practices. The study then delineated a cultivation path for the major by integrating the characteristics of these employment pathways, and optimised general knowledge and compulsory courses, core courses, graduation requirements, and the cultivation objectives of the major.

Suggested Citation

  • Yan Li & Tao Huang & Xiang Li, 2025. "Training path of big data management and application talents based on BERTopic-TOPSIS model," PLOS ONE, Public Library of Science, vol. 20(12), pages 1-26, December.
    • Handle: RePEc:plo:pone00:0334127
    DOI: 10.1371/journal.pone.0334127
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