面向数字产业需求的大数据岗位胜任力模型构建研究

Research on Constructing a Competency Model for Big Data Positions to Meet the Needs of the Digital Industry

摘要: 数字经济高质量发展对大数据人才提出结构性新要求。本文结合文本分析方法，对数据分析师、数据产品经理等企业核心岗位展开系统调研，基于岗位描述的词频分析与语义归类，构建了包含4个一级指标及12个二级指标的岗位胜任力模型。研究发现：数字产业对人才的需求正从“学科匹配”转向“能力匹配”，其中“数据要素化”能力成为区分传统数据人才与新型数据人才的关键标识。基于此，本文提出大数据管理与应用专业在培养目标精准化、实践教学体系重构、产教融合机制创新等方面的优化路径，为应用型高校的大数据人才培养提供决策参考。

Abstract: The high-quality development of the digital economy has created new, structural demands for big data talent. Employing text analysis methods, this study conducts a systematic survey of core corporate roles—such as data analysts and data product managers—and constructs a competency model comprising four primary indicators and twelve secondary indicators based on word frequency analysis and semantic categorization of job descriptions. The findings reveal that the digital industry’s demand for talent is shifting from “disciplinary alignment” to “competency alignment”, with the ability to handle “data as a factor of production” serving as the key differentiator between traditional and new-generation data professionals. Based on these insights, the paper proposes optimization pathways for “Big Data Management and Application” majors—focusing on refining training objectives, restructuring practical teaching systems, and innovating industry-education integration mechanisms—thereby providing a decision-making reference for talent cultivation in applied universities.