Existing digital governance monitoring platforms generally have problems such as insufficient data analysis and slow response speed, which cannot timely and effectively find out the hidden dangers and problems in the governance process. To this end, this paper proposes a data analysis method based on the improved particle swarm optimization (PSO) algorithm for digital governance monitoring platform. Firstly, an improved adaptive PSO algorithm is proposed for the traditional PSO algorithm, which is easy to fall into the problem of local optimization, and improves the global search ability by dynamically adjusting the parameters of the algorithm. Then, the algorithm is applied to the data analysis of monitoring platform, which realizes the efficient mining and anomaly detection of massive governance data. The experimental results show that compared with the traditional monitoring platform, the proposed method can more quickly and accurately find the potential hidden dangers in the process of digital governance and provide more timely and effective analytical support for decision-makers.