Data-Driven Analysis of Skeet Shooting Training: Multi-Modal Data Collection and Lake-Warehouse Unified Architecture Design

As times evolve and technology advances, the speed and scale of data generation have increased dramatically, giving rise to new technologies for big data processing and analysis. The Bidirectional Skeet Shooting Analysis Project aims to enhance the training levels of skeet shooters. Traditional training methods primarily rely on coaches' experiences and lack systematic data analysis. To address this issue, this paper applies big data technologies by comprehensively collecting data from athletes' training processes and constructing a data warehouse based on a lake-warehouse architecture. This approach assists coaches in accurately understanding each athlete's training status while providing analysis and visualization capabilities. It promotes the shift of skeet shooting training towards a data-driven direction, thereby enhancing training effectiveness and offering significant theoretical and practical references for improving traditional training methods in skeet shooting.