The Dilemma and Countermeasures of Music Education under the Background of Big Data

Abstract

The fundamental subject matter in the area of quality research in education is music education, which is significant. Based on a big data theory, this study proposes a data management platform of music education that can use data analysis techniques to perform analysis and research on the situation facing music education. According to the layered concept through a demand analysis of the music education big data analysis platform, the model divides the platform into a data support layer, data storages and calculation layer, platform function layers, and platform application layer. Based on a platform function layer, the technical route is formulated, and functional modules are designed to solve the issue of quantitative data analysis. The plan uses the data aggregating component to combine music data into a real-time data stream for 3D visualization simulation and then distributes a data stream using messaging middleware. Through a real-time computing framework, the downstream completes a real-time calculation of musical information. Weak and strong real-time needs for music apps can be processed using features. The greatest average relative inaccuracy of the model, as determined by testing a simulation verification module, is 5.1374 percent, and getting the specifics of the visualization work using getViewTaskInfo is a trustworthy technique. It successfully encourages the capacity to overcome the challenges of music education in order to achieve the accuracy standards of high-quality music education.