社会保障体系在资源分布、覆盖精度与服务效率方面存在结构性难题，数据驱动机制为其提供了技术改善路径。文章研究了社会保障数据整合的实现方式，分析了参保行为监测、资金流动追踪与重点人群识别的技术流程，构建了面向对象分类、动态分配资源与反馈政策调整的优化策略，探讨了待遇测算自动化、服务平台集成化与区域服务匹配机制。研究内容有助于完善社会保障系统的数据支撑结构，提升制度运行的适应性、连续性与操作效率。

The social security system faces challenges in resource allocation, coverage, and efficiency. This study explores data integration methods, including behavior monitoring, fund tracking, and group identification, and proposes strategies such as classification, dynamic allocation, and policy adjustment. It also examines automated benefit calculation, service platform integration, and regional matching. The results improve data support and enhance system adaptability and efficiency.