电力大数据质量评价模型及动态探查技术研究

Research for electric power big data quality evaluation model and dynamic exploration technology

针对电力数据数量多、种类庞杂、横跨专业多等特点而引起的数据质量不高的现状,该项目以数据中心数据为研究对象,通过分析产生数据质量问题的原因,以元数据、数据质量、数据建模等理论为基础,对数据流动过程中的质量检查、质量控制和质量评估等进行深入的研究。构建电力大数据质量评价指标体系,研究电力大数据质量实时监控、快速动态检测方法与关键技术,提出了适合于电力大数据数据质量控制与评估体系模型,实现数据质量管控平台开发,确保企业数据质量,提升数据应用价值。

For the status quo of bad electric power data quality caused by mass data,complex species,multi-profession in-volvement and so on,quality inspection,quality control and quality assessment in the flow process of the data from the data cen-ter are studied based on metadata,data quality and data modeling theories,and cause analysis of poor data quality. The electric power big data quality evaluation index system was built. The real-time monitoring,rapid motion detection methods and key tech-nologies of the electric power big data quality were researched. The data quality control and assessment system model suitable for the power big data are proposed in thispaper. The development of a data quality control platform was achieved. It ensured the data quality of the enterprise and raised the value of data applications.