Design And Implementation Of Data Visualization System For Decision Support

At present,the data analysis for big data has become a research hotspot and an inevitabletrend.It is still unable to fully satisfy the demand for decision analysis based on human cognitive laws simply relying on machine learning and other automated calculation methods.The task of performing human-robot collaborative analysis through data visualization has received more and more attention.Therefore,this paper develops a data visualization analysis system based on this urgent need.Through the research of self-service analysis business process,and fully considering the future data sources,interactive effects and other variable demand factors,this paper adopts B/S three-tier application architecture to construct the system architecture,front-end adopts Angular JS,Bootstrap,Echarts and other technologies.Back-end uses SSM(Spring + Spring MVC + My Batis)mainstream framework,using My SQL and Neo4 j as background database,Tomcat for application server development to achieve a data visualization analysis system.The goal of the system is to reduce the difficulty of data analysis and improve the efficiency of analysis and decision making.The data visualization analysis system consists of five major sections: theme data set,data visualization chart,theme panel,user management and knowledge management.The highlight of this system is to support the integration of visualized chart information from a variety of data sources,to support data modeling and theme panel configuration through drag-and-drop interaction,and to support the interactive analysis of visualized charts in a multi-screen linkage.In addition,the system also supports for switching between a variety of theme color schemes,and can visually manage the model based on the knowledge graph.By using this system for data analysis,the operational,intuitive and practical nature of the business can be enhanced,which can reduce the workload of data analysts to a certain extent and improve the efficiency of decision-making.This system has good scalability,cross-platform nature,reusability and other characteristics.After testing and actual feedback,the system architecture designed in this paper has good performance,stable overall operation,it can meet the needs of data analysts for human-computer interaction analysis and decision-making decision support.