中国石油网消息：9月16日获悉，长庆石化收到国家数据管理能力成熟度（DCMM）四级证书，成为中国石油首家取得该四级认证的炼化企业。

China Oil News: On September 16th, it was learned that Changqing Petrochemical has obtained the national Data Management Capability Maturity Model (DCMM) level 4 certification, becoming the first refining and chemical enterprise in China to achieve this level 4 accreditation.

DCMM是工业和信息化部牵头制定的国内数据治理领域权威国家标准，分为五个成熟度等级。受员工人数规模条件限制，四级是长庆石化可申报的最高等级。这一认证也是长庆石化9年深耕数据治理、推进数智化转型的重要成果。

DCMM is an authoritative national standard in the field of data governance in China, jointly formulated by the Ministry of Industry and Information Technology. It is divided into five maturity levels. Due to the limitation of the number of employees, level four is the highest level that Changqing Petrochemical can apply for. This certification is also an important achievement of Changqing Petrochemical's nine-year deep engagement in data governance and the promotion of digital and intelligent transformation.

长庆石化数据治理分三阶段稳步推进。2017年，启动智能工厂建设，开展数据摸底，搭建数据仓库，建立八大数据标准规范框架。2021年，被列入集团公司数字化转型试点名单，成立数据治理组织，建设企业级数据湖，对全厂44套业务系统实施治理，消除系统分散、跨部门取数难等痛点。2025年7月后，工作重心转向数据应用，推动AI模型在生产装置上落地，实现4项智能业务场景落地，入选集团公司人工智能应用试点名单。

The data governance of Changqing Petrochemical has been advancing steadily in three phases. In 2017, the construction of an intelligent factory was initiated, data surveys were conducted, a data warehouse was established, and eight data standardization frameworks were established. In 2021, it was included in the list of digital transformation pilot projects of the group company, a data governance organization was established, an enterprise-level data lake was built, and the governance of 44 business systems across the factory was implemented to eliminate problems such as system dispersion and difficulties in cross-department data retrieva l. After July 2025, the focus of the work shifted to data application, promoting the implementation of AI models in production facilities, achieving the implementation of 4 intelligent business scenarios, and being selected as a pilot project for artificial intelligence applications of the group company.

经过持续建设，公司完成44套业务系统的数据治理，梳理形成637张贴源数据表，接入2.2万余个PHD实时数据位号，整合图纸、设备档案、工艺资料等，形成数据资产地图。以往跨部门“找人要数”，如今可自助检索调取，统一对外数据接口，切实提升业务效率。

Through continuous construction, the company has completed data governance for 44 business systems, sorted out and formed 637 source data tables, connected 22,000+ real-time data tags of PHD, integrated drawings, equipment archives, process materials, etc., and formed a data asset map. Previously, cross-departmental "asking someone for data" was common; now, users can independently search and retrieve data, and there is a unified external data interface, effectively improving business efficiency.