Course

Foundations of Data Communication

Data is everywhere, but data alone doesn’t create understanding. Many teams struggle to explain insights clearly—using the wrong charts, cluttered visuals, or numbers without context. You don’t need to be a data scientist to communicate data effectively, but you do need a framework for turning information into insight. This course is designed for non-technical learners who work with data in reports, presentations, dashboards, or meetings and want to explain what the data means, why it matters, and how others should act on it.

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Part of the Data Literacy and AI Fundamentals path.

4.8 (359 reviews)
  • Beginner friendly
  • 6 hours
  • Self paced
  • 3 lessons
Otavio

“The learning paths on Dataquest are incredible. They give you a direction through the learning process – you don’t have to guess what to learn next.”

Otávio Silveira

Data Analyst @ Hortifruti

Foundations of Data Communication

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Course overview

Being data-driven isn’t about writing code—it’s about understanding and communicating insights clearly. In this course, you’ll learn how to tell effective data stories, choose the right charts, and design clear visuals that help others understand what the data is saying. This course is designed for non-technical learners who want to build data literacy and communicate insights with confidence in reports, presentations, and everyday work.

Key skills

  • Explaining data insights clearly using narrative and context
  • Selecting charts that match specific communication goals
  • Designing simple, effective visuals that reduce confusion
  • Improving reports and presentations without adding technical complexity
  • Communicating data-driven insights with confidence in business settings

Course outline

Foundations of Data Communication [3 lessons]

What Makes a Data Story? 2h

Lesson Objectives
  • Explain how data storytelling improves decision-making
  • Identify three core components: Narrative, Visuals, Context
  • Distinguish between simple reporting and effective storytelling
  • Apply narrative structure: hook, investigation, and recommendation
  • Tailor data presentations to different stakeholder audiences

Choosing the Right Chart for Your Data 2h

Lesson Objectives
  • Start visualization selection by defining your data question
  • Use bar charts to compare discrete categories (ideally under 15)
  • Apply line charts for tracking continuous changes over time
  • Choose scatter plots to explore relationships between numeric variables
  • Select histograms to understand distribution of numeric data
  • Use stacked bar charts for part-to-whole relationships across categories
  • Apply pie charts for proportions when categories sum to 100%
  • Choose box plots to compare distributions and identify outliers

Designing Clear and Impactful Visuals 2h

Lesson Objectives
  • Clarify visualization purpose before selecting chart type
  • Reduce chartjunk by maximizing data-ink ratio effectively
  • Apply jitter to reveal hidden data density patterns
  • Use color strategically to highlight key insights
  • Contextualize numbers through benchmarks and comparisons
  • Design colorblind-accessible visualizations for all audiences

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