Visualization Based On The Data Center System Design And Implementation

In modern enterprise and government applications,there are various forms of software for PCs,clients and mobile terminals,and various data management systems such as finance,inventory,and customer relations behind those front-end applications are important in the back-end system link.The types of data are complex and large in scale,which may require a suitable middle office system to manage,analyze and integrate big data,so that users can quickly extract effective information from complex data and improve development efficiency.Provide guarantee for the digital development of enterprises.The visualization system of the data center in this article came into being under this background.The core of the system is to realize the coordinated planning of data resources.The core requirements for the convergence and governance of internal and external data information resources,this system unified management,control and governance of data involved in business projects,so as to provide support services for unified data resources for upper-level business applications and external business systems.This paper analyzes the development and key realization of the data visualization system at home and abroad in detail;through the research requirements,the detailed requirements of the system are obtained.The system mainly includes data access,data quality,data cleaning and other parts.The visualization part is designed with a reasonable architecture scheme.The visualization layer adopts a design combining micro-front-end and single-page applications.The data service layer is built with springboot.At the same time,the core development parts of the system are designed and implemented: data source management,data access task management,Data cleaning conversion,data cleaning task management,data quality monitoring,quality inspection reports and other key parts.The big data middle-stage visualization system designed in this article has a wide range of applicability.It can be quickly accessed to realize data governance for data scenarios in various industries.After sufficient testing,the system finally meets the needs of users’ expectations and is put into production use.