4 Days Instructor-led
Discover the science behind the art of visualizing data in this example-rich course. You’ll learn which types of visualizations are best suited for different kinds of data, and the most effective ways to display your data insights in Tableau. Just as importantly, you’ll learn to avoid pitfalls that can result in misleading data presentation.
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.
Learning Objectives
After completing this course, you will be able to:
- Design visualizations that reduce cognitive load to effectively leverage short-term memory.
- Design visualizations that align with pre-attentive attributes to effectively leverage sensory memory.
- Design visualizations to inform viewers without misleading.
- Effectively use chart types to answer specific questions.
- Design dashboards and stories using visual best practices.
- 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.
Audience
You are an experienced Tableau user who wants to learn more about best practices for displaying information and insights in Tableau. Ideally, you have already taken the Tableau I – Fundamentals and Tableau II – Intermediate courses, but these are not official prerequisites. This course uses Tableau to develop and discuss visualizations, but does not include instruction on how to use Tableau.
Prerequisites
Tableau I – Fundamentals and Tableau II – Intermediate or equivalent experience are recommended before taking this class.
Course Outline
- Visual Analytics Process
- Visual Analytics
- Visual Analytics Process
- Advantages of Visual Analysis
- Memory and Processing
- Memory and Processing Types
- Short-Term Memory
- Cognitive Load
- Focus and Guide the Viewer
- Remove Visual Distractions
- Organize Information into Chunks
- Design for Contiguity
- Sensory Memory: Overview
- Preattentive Attributes
- Quantitatively-Perceived Attributes
- Categorically-Perceived Attributes
- Sensory Memory: Form
- Form Attributes
- Length
- Width
- Size
- Orientation
- Shape
- Enclosure
- Sensory Memory: Color
- Color Attributes
- Color Relativity
- Color Vision Deficiency
- Color Hue
- Color Intensity
- Sensory Memory: Position
- Position Attributes
- 2-D Position
- Spatial Grouping
- Informing without Misleading
- Gestalt Principles
- Visual Area Assumptions
- Axis Assumptions
- Color Assumptions
- Amount of Detail
- Charts for Viewing Specific Values
- Questions that Lead to Viewing Specific Values
- Chart Types for Viewing Specific Values
- Best Practices and Considerations for Viewing Specific Values
- Charts for Comparing and Ranking Categories
- Questions that Lead to Comparing and Ranking Categories
- Chart Types for Comparing and Ranking Categories
- Best Practices and Considerations for Comparing and Ranking Categories
- Charts for Comparing Parts to Whole
- Questions that Lead to Comparing Parts to Whole
- Chart Types for Comparing Parts to Whole
- Best Practices and Considerations for Comparing Parts to Whole
- Charts for Comparing Measures
- Questions that Lead to Comparing Measures
- Chart Types for Comparing Measures
- Best Practices and Considerations for Comparing Measures
- Charts for Viewing Correlation
- Questions that Lead to Viewing Correlation
- Chart Types for Viewing Correlation
- Best Practices and Considerations for Viewing Correlation
- Charts for Viewing Distributions
- Questions that Lead to Viewing Distributions
- Chart Types for Viewing Distributions
- Best Practices and Considerations for Viewing Distributions
- Charts for Viewing Data Over Time
- Questions that Lead to Viewing Data Over Time
- Chart Types for Viewing Data Over Time
- Best Practices and Considerations for Viewing Data Over Time
- Charts for Mapping
- Questions that Lead to Mapping
- Chart Types for Mapping
- Best Practices and Considerations for Mapping
- Dashboards and Stories
- Development Process for Dashboards and Stories
- Plan the Visualization
- Create the Visualization
- Test the Visualization
- Review: Calculations
- Introduction and Review
- Number Functions
- String Functions
- Date Functions
- Type Conversion Functions
- Logical Functions
- Aggregate Functions
- User Functions
- Considerations for Calculated Fields
- Advanced Table Calculations
- Advanced Table Calculations Review
- Table Calculation Types
- Table Calculation Scope and Direction
- Customizing Table Calculations
- Filters and Table Calculations
- Pareto Chart
- Level of Detail Expressions
- LOD Introduction and Review
- FIXED LOD Expressions
- Filters and LOD Expressions
- INCLUDE LOD Expressions
- EXCLUDE LOD Expressions
- Nested LOD Expressions
- Discussion: Comparing Types of Calculations
- Analyzing Time-Based Data
- Scenario: Sparklines
- Scenario: Control Charts
- Scenario: Bump Charts
- Scenario: Slope Chart
- Analyzing Customer Behavior
- Scenario: Cohort Analysis
- Scenario: Survey Data
- Geographical Analysis
- Scenario: Using Marks Layers for Maps
- Scenario: Mapping Density with Hexbins
- Scenario: Spatial Files
- Advanced Techniques for Dashboards
- Dashboard Audience
- Dashboard Layout
- Dashboard Visual Elements
- Dashboard Interactive Elements