Service data cleaning method, device and electronic equipment

Abstract

The invention discloses a service data cleaning method, a device, electronic equipment and a machine readable storage medium. The method comprises the steps of obtaining service data to be subjected to data cleaning from a butted service system; determining a data element associated with the service data; and obtaining a conversion type named entity, a verification type named entity and an interpretation type named entity associated with the data element, and performing data cleaning on the service data based on the obtained conversion type named entity, verification type named entity and interpretation type named entity. According to the method, ordered data cleaning is carried out in sequence based on the plurality of named entities which are what you see is what you get, so that tediousdata cleaning configuration of a user is avoided, the data cleaning maintenance efficiency is improved, and accumulation and sharing utilization of the named entities are facilitated.

Description

technical field [0001] One or more embodiments of the present application relate to the field of computer application technology, and in particular, to a business data cleaning method, device, electronic device, and machine-readable storage medium. Background technique [0002] With the development and popularization of IT technology, more and more business data are accumulated in various industries. When it is necessary to clean the accumulated massive business data through the data governance platform, the developers of the data governance platform usually need to configure complex regular expressions in the background of the data governance platform for data cleaning. However, regular expressions are usually complicated and obscure, and it is difficult for ordinary users to understand and use, resulting in extremely low configuration and maintenance efficiency during data cleaning. For example, the public security data in the e-government system involves tens of thousand...

AI Technical Summary

Problems solved by technology

However, regular expressions are usually complicated and obscure, and it is difficult for ordinary users to understand and use, resulting in extremely low configuration and maintenance efficiency during data cleaning

For example, the public security data in the e-government system involves tens of thousands of data elements to be cleaned. Configuring and maintaining complex regular expressions for each data element is extremely complex and difficult to manage and maintain.

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