Data Visualization Principles for Tableau

Audience:
Data analysts, data scientists, front-end developers

Set-up Requirements:
Not needed

This course assumes you understand the tools within Tableau and have some knowledge of the fundamental concepts of data visualization.

Course milestones:

Format of the Course:

This course teaches you about human perception and how to leverage it to deliver the best insights. You will get familiar with design theory, including Gestalt Laws, pre-attentive attributes, and inclusivity. You will also understand the similarities and differences between exploratory and explanatory analysis. You will discover the usage of the charts and learn how to choose the most suitable one. At the end of the course, you will know how to implement the design principles is visualizations created using Tableau software.

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

• Learn about human perception.
• Get familiar with design theory.;
• Understand different types of charts.
• Define the goal of the data visualization.
• Examine and improve an ineffective visualization.

Data Relationships and corresponding charts

Design Principles

Introduction

Perception of data visualization

Practical examples of implementing design principles using Tableau

Summary and Next Steps:

• Chart selection
• Visual Hierarchy
• Formatting (labels, legends, tooltips)
• Custom palettes
• Layout
• Legibility
• Storytelling

• Distributions
• Correlations
• Geospatial
• Comparison
• Time Series
• Ranking
• Deviation
• Part-to-whole

• Helpful resources for further learning

• Human perception and cognitive load
• Reading patterns
• Pre-attentive attributes
• Gestalt laws
• Usage of the color
• Visual hierarchies
• Inclusive design

• Importance of data visualization
• Human perception
• Cognitive versus perceptual design
• Cognitive load