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基于数据血缘的电力企业主数据质量管控系统设计

Design of a Master Data Quality Control System for Power Enterprises Based on Data Lineage

  • 摘要: 针对电力企业主数据跨系统分布导致质量问题难定位、影响难评估和整改难闭环的问题,设计一种基于数据血缘的主数据质量管控系统。系统采用静态解析、运行事件和接口登记构建字段级血缘,将质量规则绑定至血缘节点,并贯通质量检测、根因追溯、影响分析、工单处置与版本审计。场景走查表明,该系统可实现异常来源定位、传播范围识别和整改恢复验证,为电力企业主数据治理提供技术框架。

     

    Abstract: A master data quality control system based on data lineage is proposed for power enterprises. Field-level lineage is built by combining static parsing, runtime events, and interface registration, and quality rules are bound to lineage nodes. Quality inspection, root-cause tracing, impact analysis, work-order handling, and version auditing form a closed loop. Scenario walkthroughs show that the system can locate anomaly sources, identify propagation scope, and verify recovery, providing an implementable framework for master data governance.

     

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