Abstract: Data treatment is a difficult and complicated task calling for continuous efforts. Data treatment tools play an important role in effectively improving work efficiency of data treatment, providing professionals with high-quality data services and making data “visible, understandable, usable and operable.” This article focuses on the bottlenecks in construction of data treatment tools, such as complicated demands, variety of metadata and integrated communication. Combined with CNOOC data treatment work and data treatment tool construction practice, the article makes detailed introduction of the construction methods for key functions and the achievements in the area, such as data asset catalogue, data standards management, data model management, metadata management,data quality management, data safety management and data service management. It also proposes to establish a set of systematic data treatment tools to help enterprises so that they can tap the value of data elements in their efforts for continual improvement of data management work.

Key words: data treatmen; data asset catalogue; data standards; data quality; data safety; data service management

摘要： 数据治理是一项复杂且需要持续开展的艰巨工作，为有效提升数据治理人员的工作效率，为业务人员提供高质量的数据服务，实现数据“可见、可懂、可用、可运营”，数据治理工具发挥着极其重要的作用。文章聚焦数据治理工具建设过程中面临的需求复杂、元数据多样、集成联通等难点，结合中国海油数据治理工作及数据治理工具建设实践，详细介绍了数据资产目录、数据标准管理、数据模型管理、元数据管理、数据质量管理、数据安全管理、数据服务管理等核心功能的建设方法及建设成果，形成一套体系化数据治理工具的参考建议，助力企业在持续推进的数据治理工作中发掘数据要素的价值。

关键词: 数据治理；数据资产目录；数据标准；数据质量；数据安全；数据服务管理