Constructing and Practicing an Industry-Education Integration Model for Big Data Graduate Programs Driven by Digital Intelligence

Abstract

Amid the surge of digital intelligence, persistent gaps between theory and practice and the limited depth of university–industry collaboration have constrained the quality of graduate training in big data and its alignment with labor‑market needs. This paper proposes an industry–education integration model tailored to the discipline, and articulates a theoretical framework for a tripartite collaboration among universities, enterprises, and technology. Grounded in digital‑intelligent technologies, the framework aims to cultivate graduates’ three‑dimensional capability profile-‘theory–technology–scenario’. The study not only offers a reproducible model for big data graduate education, but also positions industry–education integration as a ‘converter’ that smooths the transition from academia to industry, thereby supplying the digital economy with a cohort of professionals who combine academic depth with practical acuity.