To enhance the decision-making proficiency in corporate financial management, a financial decision support system design based on big data mining is proposed. The overall design is carried out through the system's physical and software architectures. Data mining techniques are employed to identify financial data posing risks, while secure financial data is recorded for efficient management and querying. Additionally, research is conducted on designing financial data management and sharing modules. System testing results indicate that the system's financial data management and sharing functionalities meet user needs, reducing CPU usage to 4% and memory to 5.19 GB, thereby significantly enhancing system performance.