Learn advanced Tableau Desktop skills for data analysis, visualization & dashboard design, w/ a top Tableau instructor!

Tableau Desktop - Advanced Data Visualization & Dashboards

Name: High-level Tableau techniques through project-led instruction
Rating: 7.1

InstructorMaven Analytics • 1,500,000 Learners

Duration11h 15m

Students10.6K

Rating4.5 (1,196)

High-level Tableau techniques through project-led instruction

Strengths

Advanced Calculation Workflows

Instruction covers complex logic including regular expressions, table calculations with addressing and partitioning, and Level of Detail (LOD) expressions.

Predictive and Geospatial Depth

The curriculum includes regression models, forecasting, clustering, and specialized geospatial mapping using spatial functions and custom territories.

Project-Led Application

Technical skills are applied through specific assignments and high-level projects that include dedicated video solutions.

Limitations

Rapid Instructional Pace

One signal from a pre-update review suggests the instructor moves and speaks very quickly, which may necessitate adjusting playback speeds to follow complex calculations; note that the current update label does not prove this has been corrected.

Best suited to

Tableau users seeking advanced calculation workflows
Aspiring business intelligence professionals
Learners preparing for Tableau Desktop Specialist exams

Less suited to

Learners who prefer a slow, methodical instructional pace
Those requiring deep exploration of foundational data flows

Comidoc Score

7.1/10

Recommended

Advanced focus

Comidoc verdict

The curriculum provides a technical deep dive into advanced Tableau features, specifically targeting complex calculation logic and predictive analytics. By utilizing a pattern of assignments followed by video solutions, the course facilitates hands-on mastery of tools like LOD expressions and geospatial mapping.

However, learners should be prepared for an accelerated teaching style. The rapid pace of instruction and occasional lack of granular detail regarding data connectivity may require careful attention or playback adjustments.

This path is best suited for those who already possess a functional understanding of Tableau and wish to prepare for professional certification or advanced analyst roles.

Score breakdown

Curriculum depth: 8.8
Applied learning: 8.8
Clarity & experience: 5.0
Currency & reliability: 5.0

Editorial course preview

What the public course preview actually shows

These 4 complementary views highlight concrete, legible examples from the course presentation.

A presentation slide titled 'Tableau Data Model' featuring a diagram that illustrates the separation between the Logical Layer and Physical Layer, with text descriptions explaining — Preview 1 of 4
This slide explains the Tableau Data Model by distinguishing between the Logical Layer for relationships and the Physical Layer for joins and unions.

A presentation slide titled Smart Aggregation comparing Physical Layer Joins and Relationships using diagrams and bar charts to illustrate differences in sales data aggregation. — Preview 2 of 4
This slide explains smart aggregation by contrasting physical layer joins with relationships, showing how each method affects the calculation of sales totals across different store IDs.

A screenshot of a Tableau Desktop dashboard displaying business metrics for Maven Roasters, including KPI circles for sales and customers, a geographic map with store locations, a — Preview 3 of 4
This Tableau dashboard visualizes key performance indicators like sales and customer count alongside a geographic map of store locations and a treemap chart breaking down revenue by product category.

Preview 4 of 4

This slide introduces the course project scenario involving Maven Roasters, outlining the business situation, project brief requirements, and specific Tableau Desktop objectives.