With the spread of compulsory education emerged continuous school management problems, and the quality of school management in compulsory education has attracted a great deal of attention in China. However, the application of information technology in the field is not yet detailed and wide, resulting in problems concerning heavy workloads and high difficulty in the whole evaluation process. As such, we have utilized big data technologies, including Apache Spark, Apache Hive, and SPSS, to effectively carry out data cleaning, correlation analysis, dynamic factor analysis, principal component analysis, and visual display on a sample of 1760 data points from 40 primary and secondary schools located in the Q Province of China. This has enabled us to construct a model for evaluating school management quality in the compulsory education stage, reducing the previous 22 management tasks required for evaluation down to just 5. Such streamlining has greatly reduced the workload and difficulty previously associated with evaluation, providing a more efficient and effective solution for assessing quality management in schools. It has improved the efficiency and accuracy of evaluation and further promoted the simultaneous development of education and education equity in the compulsory education stage.