Tableau Desktop III: Advanced
Make your Tableau charts and dashboards more innovative and able to support complex data analysis. Explore scenario-based data visualization challenges to acquire greater proficiency with calculations and to learn advanced chart techniques.
Live Virtual Classes |eLearning
You will be taken to Trailhead Academy for live virtual course registration.
Who should take this course?:
This course is designed for intermediate Tableau users who have completed Tableau Desktop I: Fundamentals and Tableau Desktop II: Intermediate or have at least six months of product experience. You should have proficiency in creating calculations, visualizations, and interactive dashboards. Bring a desire to learn advanced techniques to apply to your visualizations and dashboards in Tableau.
When you complete this course, you will be able to:
- Apply advanced calculations to gain additional insight into your data
- Incorporate advanced chart types into your analysis
- Apply advanced dashboarding techniques
- Use calculations, parameters, and table calculations together.
- Use Tableau techniques to address common use case scenarios.
- Format your visualizations and dashboards for maximum impact
View the full course description in Trailhead Academy.
Prerequisites
- Desktop I: Fundamentals and Desktop II: Intermediate or comparable product experience.
Course includes
- A course manual containing key concepts on each topic covered and hands-on activities to reinforce the skills and knowledge attained
- A digital student resources folder containing Tableau workbooks and data sources to support the hands-on activities
- Trial access to Tableau eLearning to discover self-paced, guided learning paths and earn digital badges (public classroom attendees only)
- This course provides a Certification of Completion
- Continuing Education Credit (CPE) Hours: 13 or 11.25 depending on the course you select (the 2 days/8 hrs per day option or the 5 days/2.5 hours per day option, respectively)
This course is part of the Analyst and Data Scientist Learning Paths. Find out more.