The role of data analysis and mining applications in the supply chain field is increasingly prominent in the digital economy era, and improving data analysis capabilities is a new social requirement for training logistics professionals. In order to better adapt to the demand for logistics professionals in the era of big data, it is necessary to reform the existing curriculum and teaching system, and the construction of data analysis experiments is an important part of teaching reform. The article integrates the teaching practice of the “Logistics Information System” course to explore the construction and practice of data analysis experiments in the course. Based on the product detail page data of e-commerce platforms, five experiments are designed covering aspects such as data collection, preprocessing, analysis of qualified suppliers and logistics service quality in the supply chain, data visualization, as well as data analysis report writing. Based on the characteristics of the experiments, targeted experimental teaching and assessment models are proposed. Teaching practice has shown that experiments help students develop initial practical skills in collecting, processing and analyzing data as well as exploring applications, thereby enhancing their practical abilities in logistics research and innovation.