Course Objective

All students will learn to:

  • Understand the difference between exploratory and explanatory analysis
  • Distinguish between data visualization and data storytelling
  • Learn the data storytelling process
  • Learn which charts to use to appropriately analyze data for insights
  • Build advanced charts for immediate insights
  • Ask the right questions to impact business decisions
  • Determine which metrics are important and how to analyze, visualize them appropriately
  • Choose the appropriate story type for the data story
  • Construct the data story
  • Identify common pitfalls of data analysis and visualization
  • Apply best practices of data visualization and storytelling
  • Communicate insights in a clear, simple way that tells a story to drive action
Course Outline

Part 1: Set Up/Context

  • Understanding the difference between data visualization and data storytelling
  • The data storytelling process overview
  • Starting in Tableau
    • Simple Data Connections and the Data Connection Interface
    • The Main Tableau Interface and Navigation Menu
    • Building Simple Visualizations
    • Saving Options
    • Dimensions vs. Measures and How They Affect a Viz
      • What if We Wanted to Convert a Measure to a Dimension? How Would the Viz Change?
    • Continuous vs. Discrete Variables
    • Basic Dates
      • Setting the Fiscal Year
    • Basic Aggregations

Part 2: Analysis

  • Distributions of Data, Rankings, Part-to-Whole
    • The Standard Bar Chart
    • The Side-by-Side Bar
    • Pie Charts with Percent of Total
    • Bar Chart with Max Color Calculated Field
  • Relationships between variables
    • Using Measure Names and Measure Values to Build a Data Table
      • Totals and Subtotals
    • Highlight Tables
    • Scatterplots
    • Creating Dual Axis Charts and Combo Charts
      • Actual vs. Target
  • Trends and patterns over time
    • Advanced Time Series Analytics
      • Line Chart with Year over Year Growth
      • Running Total Charts
  • Geographical and spatial relationships
    • Filled Map
    • Symbol Map
    • Dual Axis Map
  • Outlier Analysis
    • Box Plots
  • Secondary characters that help the protagonist (the analysis):
    • Advanced Tooltips
    • Annotations
    • Dynamic titles
    • Sets/Combined Sets
    • Conditional Filter (if needed)
    • Top/Bottom N Filter (if needed)

Part 3: Select Your Data Story

  • Seven types of data stories
  • Tableau/data secondary characters:
    • Using KPIs and BANS
    • KPI Indicators with YTD vs. Prev YTD (or similar types of time periods)

Part 4: Sketch

  • Story Mountain, translated for data
  • How will this be visually represented? (Sketch it out)

Part 5: Communicate

  • Communicating through story “books”
    • Dashboard
      • Advanced Formatting & Dashboard Best Practices
        • Layout Containers
        • Floating Elements
        • When to Use Which
        • Effective Dashboard Layouts
        • Layout Best Practices
          • Titles and Labeling
          • Color Choices
          • Dos & Don’ts
      • Dashboard filters for end user use
      • Labeling, Annotations, Tooltips and Data Highlighting
        • Axis Labels
        • Annotations
        • Tooltips
    • Storypoints

IF TIME:  Choose your own Adventure Stories (for more advanced Tableau users):

  • Using Actions to Create Interactive Dashboards
    • Filter Actions
    • Highlight Actions
    • URL Actions
    • Parameters
Duration 2 to 3

Related data and lab files provided


An introductory Tableau course and at least 2 months creating charts in Tableau.

Software Requirements
  • Tableau Desktop
  • Microsoft Excel 2010 or later (2013 or later recommended) with the latest update installed
  • Internet access

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