Abstract: 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 requirement for the training of logistics professionals in society. In order to better adapt to the demand for logistics professionals in the era of big data, it is urgent to reform the existing curriculum and teaching system, and the construction of data analysis experiments is an important part of teaching reform. The article combines 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 were designed from the aspects of data collection, preprocessing, analysis of qualified suppliers and logistics service quality in the supply chain, data visualization, and data analysis report writing. Based on the characteristics of the experiments, targeted experimental teaching and evaluation assessment models were proposed. Teaching practice has proven that through experiments, students can initially master the practical abilities of data collection, processing, analysis, and application exploration, and enhance their logistics research and innovation practical abilities.