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TP3319

Data Storytelling with Tableau Training

Our Data Storytelling with Tableau training course teaches participants how to effectively navigate data to ask the right questions and define metrics, focusing on context, design, communication, and automation using Tableau. This class will include time for workshopping with your own data to make improvements and create more impactful data-driven narratives.
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Course Details

Duration

2 days

Prerequisites

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

Skills Gained

  • 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 analyze data for insights appropriately
  • Build advanced charts for immediate insights
  • Ask the right questions to impact business decisions
  • Determine which metrics are important and how to analyze, and 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
      • Question/problem statement/ obtain context
      • Analysis
        • Exploratory to get to Explanatory
      • Select your data story type
      • Sketch
      • Communicate
        • Which storybook (the different ways to communicate your data story) should you use
    • Starting in Tableau
      • Simple Data Connections and the Data Connection Interface
      • The Main Tableau Interface and Navigation Menu
      • Building Simple Visualizations
      • Saving Options
  • Part 1 Question: What is the problem statement?
    • Tableau Piece:
      • 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
    • Storytelling Piece:
      • Context and Logistics
        • Obtaining context
          • Focus on the why (why -> root cause)
          • Challenging assumptions
          • Identifying key metrics
        • Logistics
          • Does the data exist for what's being asked?
          • Do you need permission to access the data set?
  • Part 2: Analysis
    • Storytelling piece: Five types of analyses overview
      • Tableau piece:
        • 1 - 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
        • 2 - 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
        • 3 - Trends and patterns over time
          • Advanced Time Series Analytics
            • Line Chart with Year-over-Year Growth
            • Running Total Charts
        • 4 - Geographical and spatial relationships
          • Filled Map
          • Symbol Map
          • Dual Axis Map
        • 5 - 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
    • Data Storytelling Piece:
      • Narrate Change over Time.
      • Start Big and Drill Down.
      • Start Small and Zoom Out.
      • Highlight Contrasts.
      • Explore the Intersection.
      • Dissect the Factors.
      • Profile the Outliers.
    • Tableau/data secondary characters:
      • Using KPIs and BANS
      • KPI Indicators with YTD vs. Prev YTD (or similar types of time periods)
  • Part 4: Sketch
    • Data Storytelling piece:
      • Review the purpose of the story (aka the plot)
      • Review who the audience is for the story
      • Story Mountain, translated for data
        • Setting it up
        • Rising Action (your analysis)
        • Climax/Peak: (Your insights)
        • Conclusion/Ending: What’s the call to action for your audience?
      • How will this be visually represented? (Sketch it out)
    • Tableau Piece:
      • Walk through how to build the first dashboard, elements, etc.
  • Part 5: Communicate
    • Data Storytelling piece:
      • 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
      • Slide Deck/Story Points
    • Tableau Piece:
    • Build dashboard
    • Dashboard filters for end-user use
    • Labeling, Annotations, Tooltips, and Data Highlighting
      • Axis Labels
      • Annotations
      • Tooltips
    • Story points
  • Choose your own Adventure Stories (for more advanced Tableau users):
    • Using Actions to Create Interactive Dashboards
      • Filter Actions
      • Highlight Actions
      • URL Actions
      • Parameters