Data Visualization Best Practices
Program Information
- 🎓 Delivery Method:
- On-site (available now, on demand)
- Remote (live, on demand)
- Online (self-paced, coming soon)
- ⏳ Duration:
- 3 days, 4 hours per day
- Custom options available for internal teams
- 🧩 Format:
- Interactive workshops
- Hands-on exercises
- 👨🎓 Maximum Participants:
- 12 per session (to ensure personalized interaction)
- 📋 Course Requirements:
- No prior technical background required.
- 📅 Scheduling:
- Flexible scheduling available on demand
- 📞 Contact to Schedule:
- 📧 training@vizacta.com
Course Description
This course equips professionals and students with the knowledge and skills to transform complex data into clear, compelling visual narratives.
You’ll explore the foundational principles of visual perception, design, and storytelling, and learn how to choose the right chart types for different data and objectives. From time series and part-to-whole visuals to geospatial maps and outlier detection, you’ll gain hands-on techniques to craft visuals that inform, engage, and persuade, all while avoiding common design pitfalls.
Whether you’re building dashboards, presentations, or reports, this course will help you master the art and science of impactful data visualization.
What you will learn
- Apply core design principles (Tufte, Gestalt, pre-attentive attributes) to create effective visualizations
- Choose the right chart type for specific data stories and analytical goals
- Visualize time-based data using line charts, sparklines, and trend lines
- Represent proportions and parts-to-whole without relying on ineffective pie charts
- Build accurate and insightful geospatial visualizations
- Detect patterns, outliers, and trends using visual exploration techniques
- Design visuals that are accessible, readable, and free of clutter
- Tell compelling data stories using sequencing, emphasis, and annotation
Course Curriculum
- Why visualize data?
- Information vs. data vs. insight
- Visualization as a decision-making aid
- Good vs. bad examples: visual impact
- Tufte’s principles
- Gestalt laws (proximity, similarity, enclosure, etc.)
- Pre-attentive attributes
- Reducing cognitive load
- How humans interpret visual elements
- Position, length, area, shape, color, and angle
- Ranking effectiveness of visual encodings
- Avoiding visual distortion
- Visual goals: comparison, trend, correlation, distribution, composition
- Bar, line, scatter, dot, box, heatmap, treemap, etc.
- Choosing charts based on questions, not just data type
- Best practices for visualizing change over time
- Line, area, step, and sparkline charts
- Showing seasonality, volatility, and trends
- Time aggregation and smoothing techniques
- Representing proportions and share
- Alternatives to pie charts: stacked bars, treemaps, waterfalls, waffle charts
- Pitfalls in misrepresenting part-to-whole relationships
- Visualizing location-based data
- Choropleth maps, symbol maps, density/heat maps
- Geographic granularity, projections, and map bias
- When maps enhance vs mislead
- Visual techniques to uncover trends, clusters, outliers
- Emphasizing variation and change
- Common traps: overplotting, hidden bias, pattern illusions
- Layout and composition: use of space and alignment
- Labeling and hierarchy for clarity
- Color theory and accessibility (e.g., color blindness considerations)
- Interactive vs static: what adds value
- Crafting narrative structure in visualizations
- Leading the viewer: focus, context, and emphasis
- Using annotations, sequencing, and dashboards to tell a story