VA-TABLEAU.AP1
Visual Analytics Fundamentals: Creating Compelling Data Narratives with Tableau
Learn to create visually stunning data analytics with Tableau to communicate insights that drive decisions and inspire action.
- Practice in 20 Hands-On Labs — nothing to install
- 14 Interactive Lessons and 70 topics mapped to the official exam objectives
- 86 Practice Test Questions
Intermediate Self-paced · 1 year access
20 Hands-On LiveLabs
Practice real IT tasks in guided environments.
- Real environments
- Auto-graded
- No installation
14Interactive Lessons
70Topics
20LiveLab
86Practice Test Questions
52Flashcards
52Glossary of terms
01 / Skills you'll get
What you will be able to do
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No credit card required
In our Visual Analytics fundamentals course, you’ll learn how to master the art of data visualization and storytelling. This course is designed to give you skills to turn raw data into clear, visually engaging narratives that drive decision-making. You’ll cover key concepts such as data preparations, visualization best practices, dashboard creation, and interactive data exploration. Through hands-on labs, you’ll use Tableau’s powerful tools to create impactful visual analytics that not only organize data but also tell stories.
- Install and use Tableau Desktop
- Connect to and work with data sources
- Perform basic data preparation using Tableau's Data Interpreter tool
- Understand the difference between dimensions and measures
- Create various fundamental visualizations including bar charts, scatter plots, tree maps, heat maps, and more.
- Structure data and visual analytics stories using storyboarding techniques
- Create dashboards for data storytelling
- Determine the contrast between exploratory and explanatory data analysis.
- Identify the target audience for data stories.
Target Career Roles
- Data Scientist
- Data Analyst
- Business Intelligence Developer
- Tableau Consultant
- Business Analyst
- Tableau Developer
02 / Lessons & labs
See exactly what you will learn and practice
Lessons
14 Interactive Lessons · 70 topics01 Preface 9 topics +
- Three Core Takeaways
- What You’ll Learn in This Book
- Who This Course Is For
- Assumptions
- Why Tableau?
- Installing Tableau Desktop
- How to Use This Text
- Supporting Materials
- Contents of This Course
02 Acknowledgment +
03 About the Author +
04 Welcome to Visual Analytics 5 topics +
- A Visual Revolution
- The Evolution from Data Visualization to Visual Data Storytelling
- A Brief Look at the State of the Industry
- From Visual to Story: Bridging the Gap
- Summary
05 The Power of Visual Analytics 3 topics · 1 LiveLab +
- The Science of Storytelling
- The Power of Stories
- Summary
1 LiveLab in this lesson — see the labs panel →
06 Getting Started with Tableau 11 topics · 2 LiveLab +
- Using Tableau
- Why Tableau?
- The Tableau Product Portfolio
- Getting Started
- Installing Tableau Desktop
- Connecting to Data
- Adding and Replacing Data Sources
- Basic Data Prep with Data Interpreter
- Navigating the Tableau Interface
- Understanding Dimensions and Measures
- Summary
2 LiveLab in this lesson — see the labs panel →
07 Keeping Visual Analytics in Context 5 topics +
- Context in Action
- Exploratory Versus Explanatory Analysis
- Structuring Visual Analytic Stories
- Audience Analysis for Storytelling
- Summary
08 Fundamental Data Visualizations 8 topics · 8 LiveLab +
- The Bar Chart
- The Line Chart
- Pie and Doughnut Charts
- The Scatter Plot
- The Packed Bubble Chart
- The Tree Map
- The Heat Map
- Summary
8 LiveLab in this lesson — see the labs panel →
09 Fundamental Maps 2 topics · 2 LiveLab +
- Types of Maps
- Summary
2 LiveLab in this lesson — see the labs panel →
10 Design Tips for Curating Visual Analytics 10 topics · 3 LiveLab +
- Visual Design Building Blocks
- Color
- Color Effects
- Pre-attentive Colors
- Important Color Considerations
- The Truth About Red and Green
- Lines
- Formatting, Shading, and Banding
- Shapes
- Summary
3 LiveLab in this lesson — see the labs panel →
11 Structuring Analytics for Storytelling: Prep, Dashboards, and Stories 3 topics +
- Basic Data Prep in Tableau: Data Interpreter
- Storyboarding Your Visual Analytics
- Summary
12 Beyond Fundamentals: Advanced Visualizations 6 topics · 4 LiveLab +
- Timelines
- Bar-in-Bar Charts
- Likert-Scale Visualizations
- Lollipop Charts
- Word Clouds
- Summary
4 LiveLab in this lesson — see the labs panel →
13 Closing Thoughts 3 topics +
- Five Steps to Visual Data Storytelling
- The Important Role of Feedback
- Ongoing Learning
14 Appendix A. Tableau Services 5 topics +
- eLearning
- Instructor-Led Training
- Tableau Help
- Tableau Community
- Tableau Knowledge Base
Hands-On Labs Our edge
20 LiveLabs- Creating a Story
- Creating a Connection in a New Workbook
- Using the Show Me Card
- Creating a Bar Chart
- Creating a Line Chart
- Creating a Doughnut Chart
- Creating a Pie Chart
- Creating a Scatter Plot
- Creating a Bubble Chart
- Creating a Tree Map
- Creating a Heat Map
- Creating a Choropleth Map
- Creating a Hierarchy
- Using the PROPER() Function
- Creating a Calculated Field
- Using the Shape Marks Card
- Creating a Bar-in-Bar Chart
- Creating a Divergent Stacked Bar Chart
- Creating a Stacked Bar Chart
- Creating a Lollipop Chart
Labs run in your browser — nothing to install.
03 / FAQs
Questions before you start
What are Tableau fundamentals?+
Tableau fundamentals are the building blocks for using Tableau software for data visualization. This includes connecting to data, creating basic charts (bar, line, pie, etc.), understanding data types (dimensions & measures), and cleaning data with tools like Tableau's Data Interpreter.
What is Tableau in data visualization?+
Tableau is a powerful data visualization tool that lets you create interactive charts, graphs, and dashboards. You can connect to various data sources, explore trends and patterns, and communicate insights effectively. Tableau's drag-and-drop interface makes it user-friendly for beginners while offering advanced features for experienced users.
What are the four main visualization types?+
The four main visualization types are:
- Bar charts: Great for comparing categories or showing changes over time.
- Line charts: Ideal for showing trends and how data points connect over time.
- Pie charts: Useful for displaying proportions of a whole, but limited to a few categories.
- Scatter plots: Reveal relationships between two measures, highlighting correlations or clusters.
What are the benefits of this course? +
The benefits of this course includes high marketability, higher earning potential, improved problem-solving and data analytical skills.
Improve Your Analytical Skills For Career Advancement
This visual analytics course introduces the expertise needed to visually communicate data narratives that resonate with stakeholders.
- 1 year of full access
- 20 LiveLab included
- Certificate of completion
No credit card required