Abstract: In response to the new era of transportation big data applications and the demand for cultivating innovative talents in the construction of emerging engineering education, this study, guided by the concept of “integration of science and education, mutual reinforcement of teaching and research,” introduces “big Data + cloud computing + virtualization” technology. It constructs an integrated transportation big data teaching and training platform based on the “knowledge acquisition-teaching interaction-practical application (Know-Teach-Act)” framework to support the whole-process training in transportation big data. The platform features modularization, scalability, and ease of operation, which enhances the teaching effectiveness of big data training courses in practice. Through recording students’ learning processes, dynamic evaluation, and real-time feedback, the platform fosters efficient interaction, temporal progression, and gradual deepening between teachers and students under unified educational objectives, ensuring comprehensive monitoring and improvement of teaching quality. An integrated bachelor-master-doctoral approach has been adopted to develop a platform application model that simultaneously promotes, trains, develops, researches, and constructs. This approach significantly contributes to the construction and sustainable development of future virtual teaching and research offices and virtual simulation laboratories for related disciplines.