American Research Journal of Humanities and Social Sciences

The growing use of data-driven technologies has created a widening need for graduates who can combine analytical knowledge with practical workplace capabilities. To address the gap between university-based learning and the evolving expectations of industry, this study proposes a university–industry cooperation framework for strengthening the quality of data analytics talent development. The framework connects academic preparation with workplace-oriented learning through several complementary mechanisms, including collaborative curriculum design, industry-recognized certification, and structured practical training. By bringing educators and industry practitioners into the talent-development process, the approach encourages closer alignment between what students learn and the competencies required in professional data analytics environments. It also supports the continuous development of students’ technical knowledge, problem-solving abilities, and professional skills. Overall, the framework offers an integrated pathway for developing graduates who are better prepared to respond to changing industry requirements and contribute effectively to data-driven organizations.

Keywords: Data Analytics Talent, University–Industry Collaboration, Talent Development, Curriculum Design, Professional Certification, Experiential Learning, Industry-Oriented Training.