In the era of digitalization, educational resources are also developing in the direction of digitalization, so digital educational resources are born. Digital education resources play an important role in education and teaching, so it is very important to strengthen the construction of this resource. The student Management System (MS) is an important component of the university MS, which can play a certain role in guiding and standardizing students' learning and life. However, there are many problems in the existing student MS, which has been difficult to adapt to the management concept of the new era. In order to solve this problem, this paper integrated big data technology to optimize the construction of digital education resources, and analyzed the existing problems of student MS, which also gave corresponding solutions. At the same time, the student MS was also constructed, and the cluster analysis algorithm was used to test the system. The experimental results showed that in terms of average response time, the maximum of this algorithm was 1.83s, and the maximum of traditional algorithm was 3.31s; in terms of memory utilization, the maximum of this algorithm was 50.21%, and the maximum of traditional algorithm was 66.29%; in terms of Central Processing Unit (CPU) utilization, the maximum of this algorithm was 43.21%, and the maximum of traditional algorithm was 53.24%. In conclusion, clustering analysis algorithm could effectively optimize the performance of student MS.