Research on Power Data Quality Analysis Method Based on Verification Rules in Big Data Environment
Zheng Zhu, Yingjie Tian, Hongshan Yang · 2024
This article designs a relevant data governance system for power enterprises in response to the governance issues of power big data. Firstly, it analyzes the opportunities and challenges faced by power companies in big data application governance, and gives development suggestions in the context of big data. Then it analyzes the main factors affecting the quality of power data. According to the characteristics of power data, it selects seven attribute indicators including data authenticity, data accuracy, data uniqueness, data integrity, data consistency, data relevance, and data timeliness to construct a data quality evaluation index system, and establishes a data quality evaluation model under big data. At the same time, it uses information entropy to eliminate data uncertainty, making the quality evaluation results more realistic. Finally, it realizes real-time and automatic processing of quality indicator calculation, statistical analysis, and comprehensive evaluation, satisfying the requirements of dynamic and real-time quantitative diagnosis and evaluation of data quality in the system.