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

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Publicado en:PLoS One vol. 20, no. 12 (Dec 2025), p. e0334127
Autor principal: Li, Yan
Otros Autores: Huang, Tao, Li, Xiang
Publicado:
Public Library of Science
Materias:
China
Talent management
Cultivation
Misalignment
Data analysis
Big Data
Social networks
Curricula
Content analysis
Training
Data science
Supply & demand
Network analysis
Data management
Employment
Data processing
Social organization
Science education
Best practice
Professionals
Social
Economic
Acceso en línea:Citation/Abstract
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Resumen: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.
ISSN:1932-6203
DOI:10.1371/journal.pone.0334127
Fuente:Health & Medical Collection