Data fusion method and device, electronic equipment and storage medium

Abstract

The invention relates to the field of data processing, and discloses a data fusion method and device, electronic equipment and a storage medium, the method comprises the following steps: receiving a data fusion request sent by a data demand side, and identifying a fusion object of the data fusion request, the fusion object comprising a data source end and a data field; constructing a data acquisition channel of the data source end, and searching service data of the data field from the data source end according to the data acquisition channel; performing format standardization on the business data according to a preset data code table to obtain standard business data; and defining a data loading node in the pre-constructed data fusion template, matching the standard service data with the data loading node according to a preset matching rule, loading the standard service data to the successfully matched data loading node, and then returning the standard service data to the data demand side. In addition, the invention also relates to a block chain technology, and the standard business data can be stored in a block chain. According to the invention, the data fusion efficiency can be improved.

Description

technical field [0001] The present invention relates to the field of data processing, in particular to a data fusion method, device, electronic equipment and computer-readable storage medium. Background technique [0002] With the development of big data, business data generated in different business scenarios will be scattered in different databases, message queues, and file systems. When performing data fusion processing across business applications, data warehouse technology is usually used to integrate data After collecting and cleaning from different data sources, they are collected into the data warehouse to achieve data fusion across business applications. However, due to the different storage locations of different data sources, different configurations need to be configured when performing data fusion through data warehouse technology. The rules of data acquisition and conversion lead to more time-consuming data fusion process, which affects the efficiency of data f...

AI Technical Summary

Problems solved by technology

[0002] With the development of big data, business data generated in different business scenarios will be scattered in different databases, message queues, and file systems. When performing data fusion processing across business applications, data warehouse technology is usually used to integrate data After collecting and cleaning from different data sources, they are collected into the data warehouse to achieve data fusion across business applications. However, due to the different storage locations of different data sources, different configurations need to be configured when performing data fusion through data warehouse technology. The rules of data acquisition and conversion lead to more time-consuming data fusion process, which affects the efficiency of data fusion

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