Device state monitoring data quality evaluation system

Abstract

The invention discloses a device state monitoring data quality evaluation system. The system comprises an influence factor analysis module, an evaluation dimension analysis module, a check rule establishment module and an evaluation model building module. According to the system, by analyzing main factors which influence data quality, key characteristics such as data consistency, data accuracy, data integrity, data timeliness and the like are researched, and a data quality evaluation index and a data check rule are established; real-time automatic processing of data quality index calculation, statistical analysis and comprehensive evaluation is realized; and the requirements of the system in performing data quality quantitative diagnosis and evaluation dynamically in real time are met.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to an equipment status monitoring data quality evaluation system. Background technique [0002] In the information age, information technology represented by big data is rapidly integrating with power grid production, operation and management in an unprecedented breadth and depth, playing an increasingly important role and becoming a booster for the lean transformation of power grid production management in the new era. The core of big data is to mine and analyze the massive data generated, so as to quickly obtain valuable information, transform it into knowledge, and make decisions and predictions. Due to the large amount of production data, which is scattered in various information systems and isolated from each other, it has not been effectively integrated and shared, and quality problems such as data integrity, accuracy, and consistency still exist. At present, the main...

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Problems solved by technology

[0004] (2) Poor quality: including a large amount of ambiguous or even meaningless data due to imperfect dictionary items, some of the data handed over from the factory exist in paper form, and the structured data of the old system has changed due to lack of good maintenance. into meaningless structured data;

[0005] (3) Slow processing: the current power grid company's production domain information system is in a transitional stage from historically decentralized and independent construction to integrated construction, so the promotion of system construction and historical data migration are in a dominant position, and the progress of data quality governance is slightly weak status without significant improvement

[0006] Therefore, in view of the current situation of low data quality caused by the large amount of business data, various types, and multiple disciplines, how to use existing data to improve data quality and meet the needs of different enterprises is an important problem currently facing

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