论公安机关数据治理体系的创新

当前,公安机关运用的各类数据相对分散,无法形成统一的资源汇聚接口,从而使各个部门在数据调用时存在壁垒,影响了警务工作的效率。传统的大数据治理存在诸如数据不可知、不可控、不可联等一系列弊端,无法满足大数据环境下所面临的多源数据整合和数据业务化需求。基于数据治理的定义,通过离线计算技术、流式计算技术、机器学习技术的应用,可以构建起包括数据资产管理、数据资源目录、数据运维管理、智能化治理在内的科学数据治理体系,从而推动公安机关合理使用不断增长的信息数据,深挖海量数据背后的巨大价值,强有力地保证警务工作的顺利开展,提高网络案件的破案效率,并为刑侦、经侦等警务部门提供重要的信息来源和破案手段。

On the Innovation of Data Management System of Public Security Organs

At present,public security data is scattered,and a unified resource aggregation interface cannot be formed.As a result,barriers exist when data is called by various departments,which affects the efficiency of police work.Traditional public security big data governance is implemented under the guidance of development strategies and plans.There are a series of disadvantages that cannot meet the needs of multi-source organization data integration and data business in the big data environment.A scientific data governance system is the basis for improving the overall quality of public security data,standardizing public security data management,and achieving sustainable data application.With the help of a scientific data governance system,public security organs are encouraged to make rational use of ever-increasing information and data.Mining the huge value behind massive data has strongly guaranteed the smooth development of police work.In the application of police affairs,it has played an important role in maintaining the stability of the overall society,preventing and combating crimes,and assisting command and decision-making.