面向电力大数据的数据质量监测体系研究及应用

Research and Application of Data Quality Monitoring System for Electric Power Large Data

随着智能电网建设飞快发展,造成电力数据种类复杂多样化和数据质量参差不齐的现状。以传统的数据质量模型和数据质量管理等理论为基础,介绍了传统数据质量系统的优缺点。在其基础上提出基于自学体系的数据质量监测模型,并依据模型构建监测系统。分层面详细介绍数据质量监测系统,分析了有关构建策略,详细介绍了自学体系中构建的规则。为数据质量监测模型提供了理论支撑,健全了数据质量监测体系,完善数据质量监测系统,支持企业科学决策,推进信息化支撑企业管理水平的全面提升。

With the rapid development of smart grid construction, resulting in a variety of complex and diverse data types and da- ta quality of the status quo. Based on the traditional data quality ,model and data quality management theory, this paper introduc- es the advantages and disadvantages of the traditional data quality system. Based on the model, the data quality monitoring mod- el based on self- learning system is put forward, and the monitoring system is built according to the model. The data quality monitoring system is introduced in detail, and the construction strategy is analyzed, and the rules of the construction of the sys- tem are introduced in detail. To provide theoretical support for data quality monitoring model, and improve the data quality mon- itoring system, improve data quality monitoring system, support the enterprise scientific decision-making, enhance the manage- ment level of enterprise informatization support.