Research on Training Mechanism and Energy Efficiency of Art Design Talents Based on Student Information Clustering Under the Background of Big Data

Abstract

Using student data clustering in the context of big data, this study explores the energy efficiency and training processes of art design skills. To overcome the shortcomings of existing talent information service platforms, it highlights the significance of smart school-based dynamic information services and multi-integration visualisation systems. This study lends credence to the idea that big data may revolutionise the educational landscape and calls for strong information fusion management systems to keep up with the changing needs of businesses. The study's overarching goal is to help students transition more smoothly from high school to college by utilising sensing technology and developing standardised platforms. The results highlight the interdependence between educational institutions and urban growth, highlighting the importance of dynamic management and ongoing data updates for successful talent cultivation. As a whole, this strategy will help bring smart city expansion into reality by improving public employment services and bolstering intelligent talent management.