Data integration system and method for realizing interconnected data virtualization

Abstract

The invention discloses a data integration system and method for realizing interconnected data virtualization. The system comprises a client, a transmission layer, a query engine, a connection layer and a source database, wherein the client is used for sending a request command through JDBC driving; the transmission layer is used for connecting the client with the query engine; the query engine comprises an active model and a view model; the view model is used for expressing a structure and a feature of an abstract structure disclosed to the client; the active model is used for being associated with the connection layer; the connection layer is used for connecting the source database and converting data of the source data into the abstract structure recognized by the query engine; and thesource database is used for storing source data. According to the system and method, various data sources are virtualized through the query engine, so that a uniform data model is abstracted, the distributivity and isomerism of bottom data resource access are shielded and interconnection of data is realized. The data integration system and method for realizing interconnected data virtualization can be widely applied to the field of data processing.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a data integration system and method for realizing interconnected data virtualization. Background technique [0002] In the context of big data, the collection and supply of data is becoming more and more important. However, due to historical reasons, there are quite a few systems in the school that have not published their outgoing interfaces. Data sources may vary, creating more and more islands of information, but in many cases, business leaders need to query multiple business systems and external systems based on various heterogeneous data sources to make a decision. System, the existing technology generally connects multiple heterogeneous data sources in the program, and performs data extraction and conversion in the program to complete the business logic. This approach makes the program extremely complicated. When the requirements change, the code changes are very large, so o...

AI Technical Summary

Problems solved by technology

[0002] In the context of big data, the collection and supply of data is becoming more and more important. However, due to historical reasons, there are quite a few systems in the school that have not published their outgoing interfaces. Data sources may vary, creating more and more islands of information, but in many cases, business leaders need to query multiple business systems and external systems based on various heterogeneous data sources to make a decision. System, the existing technology generally connects multiple heterogeneous data sources in the program, and performs data extraction and conversion in the program to complete the business logic. This approach makes the program extremely complicated. When the requirements change, the code changes are very large, so often cause the project to fail

Images