Analyze and Optimize Pricing with Tableau and R

Overview

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.

Syllabus

Building Business Intelligence Foundations with Tableau

This module introduces learners to business-driven analytics using Tableau by focusing on understanding business requirements, defining key measures, designing dashboards, and deploying analytics solutions to support informed decision-making.

Pricing Strategy and Economic Foundations

This module builds foundational knowledge of pricing analytics by exploring pricing strategies, cost structures, elasticity concepts, and regression-based approaches to support data-driven pricing decisions.

Applied Pricing Analytics and Decision Intelligence

This module applies descriptive, predictive, and prescriptive analytics techniques to real-world pricing datasets, enabling learners to generate insights, forecast outcomes, and recommend optimal pricing actions.