Centered closely on the field of business data analysis, this course adopts a "Theory + Practice" dual-track integrated framework to systematically present core knowledge and practical skills.
The theoretical module comprehensively covers data fundamentals, collection planning, processing, and cleaning, along with multi-dimensional analysis across market, customer, product, operations management, sales, and supply chain sectors. It combines AI technologies with classic methods such as the RFM model, inventory turnover analysis, and trend forecasting, utilizing rich case studies to explain the underlying logic of data-driven decision-making.
The practical training module focuses on Excel applications, detailing techniques for PivotTables, function calculations, and visualization charts. It provides enterprise-level datasets to guide learners through the complete process of data collection, cleaning, analysis reporting, and strategy derivation.
The course content is presented in an accessible manner, allowing students to master skills step-by-step. With a strong emphasis on practice, it guides learners to develop the ability to analyze and solve problems independently, helping them apply their knowledge effectively and enhance their business data analysis and application capabilities.
