By completing this course, learners will be able to analyze business requirements, design interactive Tableau dashboards, evaluate pricing strategies, interpret price elasticity using regression models, and recommend data-driven pricing actions through descriptive, predictive, and prescriptive analytics. This course equips learners with practical skills to translate business problems into analytical solutions by combining Tableau-based visualization with pricing analytics concepts and R-driven statistical insights. Learners will start by understanding how organizations define business requirements, select meaningful measures, and build decision-ready dashboards. They will then progress into pricing analytics fundamentals, including pricing strategies, cost considerations, elasticity, and regression-based analysis. Finally, learners will apply advanced analytics techniques to real-world pricing case studies, moving from historical analysis to future forecasting and prescriptive recommendations. What makes this course unique is its end-to-end, case-driven approach that bridges business intelligence, economic theory, and advanced analytics within a single learning journey. Rather than focusing only on tools or theory, the course emphasizes how analytics supports real pricing decisions across industries. This makes it ideal for aspiring data analysts, business analysts, and professionals seeking to strengthen pricing and decision intelligence skills using Tableau and R.
What you'll learn
analyze business requirements
design interactive dashboards in Tableau
evaluate pricing strategies
interpret price elasticity using regression models
recommend data-driven pricing actions
Course objectives
understand how organizations define business requirements
apply pricing analytics fundamentals
utilize advanced analytics techniques for pricing decisions