Heterogeneous data analysis method and device based on machine learning model and medium

Abstract

The invention discloses a heterogeneous data analysis method and device based on a machine learning model and a medium, and aims to solve the technical problem that data in a multi-source heterogeneous system cannot be unified due to the fact that an existing machine learning model cannot be directly applied to ETL. The method comprises the following steps: deploying a machine learning model to a server; analyzing the machine learning model into a standard format through a prediction model markup language, and outputting the analyzed machine learning model according to a data stream mode; based on the analyzed machine learning model, analyzing the to-be-processed heterogeneous data; and outputting an analysis result of the to-be-processed heterogeneous data. According to the method, the machine learning model is analyzed into the standard format, so that the heterogeneous data in the heterogeneous system is unified, the problem that the machine learning model can be integrated with the heterogeneous data only by manually writing codes is avoided, and the labor cost is reduced.

Description

technical field [0001] The present application relates to the technical field of enterprise informatization, and in particular to a heterogeneous data analysis method, device and medium based on a machine learning model. Background technique [0002] With the wide application of new Internet technology and big data technology, the information development of enterprises pays more and more attention to data asset management. When enterprises carry out informatization construction, the first task is to establish their own data management system, and the construction of data management system often involves the aggregation of data from various business systems. In the daily production and operation process, enterprises often include multi-source heterogeneous business systems, such as: human resource system (HR), financial management system (FM), enterprise resource management system (ERP), product life cycle management system (PLM), Product Data Management System (PDM), Supply...

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present application provides a heterogeneous data analysis method and device based on a machine learning model to solve the problem that the existing machine learning model cannot be directly applied to ETL, and therefore cannot unify data in multi-source heterogeneous systems technical problem

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