Data accuracy determination method, device, terminal and computer-readable storage medium

Abstract

The data accuracy determination method, device, terminal, and computer-readable storage medium, wherein the data accuracy determination method includes: obtaining a data set, wherein the data set is composed of at least one form; determining the type of the form; according to the type of the form, Determine the quality discrimination parameters of the form, where the quality discrimination parameters corresponding to the type of the form are pre-stored in the quality discrimination parameter library; according to the quality discrimination parameters of the form, calculate the discrimination characteristic parameters of the data set, and the discrimination characteristic parameters are used to judge the accuracy of the data in the data set The accuracy of the data set is judged according to the discriminant characteristic parameters, which solves the problem of repeated calculation of data caused by the data processing process of the existing data set, reduces the efficiency of judging the accuracy of the data, and uses various methods to verify the accuracy of the data Due to the different judgment results obtained in the process of evaluation, multiple judgment results may interfere with each other and affect the accuracy of the final data judgment.

Description

technical field [0001] The invention relates to the field of electric power data processing, in particular to a data accuracy judging method, a device terminal and a computer-readable storage medium. Background technique [0002] With the advent of the era of big data, data is growing explosively, and there are more and more types. However, the data quality problems of data sets, such as data missing, irregular, inaccurate, and illogical, have always affected users' understanding of data. usage of. [0003] In the process of processing big data, the accuracy of the data is very important. Only by judging the accuracy of the data can the accuracy of the information obtained from the subsequent use of the data be guaranteed, so judging the accuracy of the data is very important. At present, in the process of evaluating data quality, such as the evaluation process of electricity consumption data with large data scale and high data accuracy requirements, the existing method is ...

AI Technical Summary

Problems solved by technology

[0002] With the advent of the era of big data, data is growing explosively, and there are more and more types. However, the data quality problems of data sets, such as data missing, irregular, inaccurate, and illogical, have always affected users' understanding of data. usage of

At present, in the process of evaluating data quality, such as the evaluation process of electricity consumption data with large data scale and high data accuracy requirements, the existing method is to combine multiple evaluation indicators (such as data integrity, conformity, etc.) (regularity, accuracy, intra-table consistency, inter-table consistency, etc.) In each evaluation process, the entire electricity consumption data needs to be evaluated. Some data units have been judged not to meet the requirements of the relevant format during the compliance evaluation process, but in the process of accuracy index evaluation In addition to judging the accuracy of the data, it may also obtain an evaluation result that the data meets the accuracy requirements, resulting in a data unit that needs to be judged multiple times by different indicators, and the data is double-calculated, reducing the In order to improve the efficiency of judging the accuracy of the data, different judgment results may be obtained when evaluating the accuracy of the data in different ways, which may cause multiple judgment results to interfere with each other and affect the accuracy of the final judgment data

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