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There are 3 modules in this course
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.
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.
What's included
6 videos4 assignments
Show info about module content
6 videos•Total 55 minutes
Introduction to Tableau Project•7 minutes
Business Requirement•12 minutes
Measure Value•10 minutes
Dashboard•13 minutes
Project Deploymaent•5 minutes
Introduction to Pricing Analytics Using R and Tableau•8 minutes
4 assignments•Total 60 minutes
Introduction to Business-Driven Analytics•10 minutes
Measures, Metrics, and Dashboards•10 minutes
What is the main objective of deploying a Tableau project?•10 minutes
Building Business Intelligence Foundations with Tableau•30 minutes
Pricing Strategy and Economic Foundations
Module 2•2 hours to complete
Module details
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.
What's included
6 videos4 assignments
Show info about module content
6 videos•Total 50 minutes
What is Pricing Analytics•8 minutes
Pricing Strategy in Business•11 minutes
Different Pricing Strategies•10 minutes
Understanding Cost•7 minutes
Elasticity•6 minutes
Calculating Elasticity from Regression Model•8 minutes
4 assignments•Total 60 minutes
Fundamentals of Pricing Analytics•10 minutes
Pricing Models and Cost Considerations•10 minutes
Elasticity and Regression-Based Pricing•10 minutes
Pricing Strategy and Economic Foundations•30 minutes
Applied Pricing Analytics and Decision Intelligence
Module 3•3 hours to complete
Module details
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.
What's included
8 videos4 assignments
Show info about module content
8 videos•Total 63 minutes
Pricing Strategy of Ratio Taxis and Toll Booths•10 minutes
Snapshot of Dataset•10 minutes
Toll Gate 1 Results•4 minutes
Descriptive Analytics•5 minutes
Predictive Analytics•8 minutes
Descriptive Analytics - Graph•6 minutes
Predictive Analytics - Understanding the Future•10 minutes
Prescriptive Analytics - Advice on Possible Outcomes•10 minutes
4 assignments•Total 60 minutes
Real-World Pricing Case Studies•10 minutes
Descriptive and Predictive Analytics in Action•10 minutes
From Insights to Recommendations•10 minutes
Applied Pricing Analytics and Decision Intelligence•30 minutes
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