Data confidence coefficient calculation method and device, computer equipment and readable storage medium

Abstract

The invention provides a data confidence coefficient calculation method and device, computer equipment and a readable storage medium, and relates to the technical field of big data processing. After the target business data set comprising the stored business data subset and the to-be-stored business data subset with the same business primary key type is obtained, the rule is constructed according to the preset content of the non-primary key data type corresponding to the target business data set; the initial confidence coefficient of each piece of business data in the target business data set is processed to obtain the temporary confidence coefficient of the target data content in each piece of business data, and the temporary confidence coefficient of the target data content in each piece of business data is acquired according to the total occurrence frequency of each piece of target primary key content in the target business data set; and the data confidence of each target data content is calcualted in the target business data set according to the target data content in the target business data set and the occurrence frequency and temporary confidence of all the target data contents in each business data subset, thereby reducing the manpower dependence during data confidence calculation, and improving the accuracy and reliability of the data confidence.

Description

technical field [0001] The present application relates to the technical field of big data processing, in particular, to a data confidence calculation method and device, computer equipment and a readable storage medium. Background technique [0002] With the rapid development of Internet technology, big data processing technology is more and more widely used in various industries. In the specific implementation of big data processing technology, it is usually necessary to collect a large amount of business data for data precipitation in order to perform subsequent business operations. It should be noted that multiple factors such as data collection cycle, means, technology, misoperation of input personnel, and inconsistent input by different input personnel often lead to a lot of uncertainty in the collected data, and it is necessary to determine the confidence of the collected data degree to know the credibility of the data. [0003] At present, the confidence level of col...

AI Technical Summary

Problems solved by technology

Therefore, this confidence degree determination scheme is very dependent on manpower, and the accuracy of the determined data confidence degree cannot be guaranteed. At the same time, the manually determined data confidence degree can only be trusted at a specific time node, and the determined data confidence degree is often Will gradually become obsolete and invalid as time nodes change

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