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Data Storytelling

Course Summary

The Data Storytelling training course teaches participants how to effectively find and communicate insights in data, with a focus on context, design, communication, and automation. Class will include time for working with your own data to make improvements and create more impactful data-driven narratives.

The course begins with students learning how to understand stakeholders, their needs and use cases, how to obtain context and know what questions to answer, and how to tie analyses back to key business outcomes. Next, the course data visualization best practices and analyzing time series data. The course concludes with formatting and presentation.

Learn how to identify the right context for analysis, perform the analysis and tell a story to drive action.
Students with prior experience working with data visualization and corporate reporting.
Business Analyst - Data Engineer - Data Scientist - Software Developer - Technical Manager - Web Developer
Skill Level
Learning Spikes - Workshops
2 Days
Related Technologies


Productivity Objectives
  • Understand how to get the right context for any analysis.
  • Determine what kinds of analyses to do.
  • Explain common pitfalls of data visualization and storytelling.
  • Master best practices of data visualization and storytelling.

What You'll Learn:

In the Data Storytelling training course, you'll learn:
  • Understanding stakeholders and their needs and use cases
  • Obtaining context and knowing what questions to answer
  • Tying analyses back to key business outcomes
  • Common pitfalls of data visualization
  • Best practices of data visualization
    • How to avoid a "data puke" and create graphs that communicate insights
    • How to use data, charts, and dashboards to help drive change and action across the company by designing for understanding.
  • Creating better tables
  • Analyzing time series data
    • Time series with averages
    • Moving Averages
    • Cumulative Charts
    • Cycle Plots
    • Control charts to identify outliers
      • Basic
      • Advanced
    • Using regression and confidence intervals to look for outliers
    • Using changepoint detection
  • Formatting and Presentation
    • Using color to effectively call out insights and not be distracting
    • Color blind safe colors
    • Maximizing "data-to-ink" ratio
    • Reviewing the "high impact data visualization checklist"
  • Adding written context to charts to better communicate insight and impact
  • Including Recommended Actions or Insights
“I appreciated the instructor's technique of writing live code examples rather than using fixed slide decks to present the material.”


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