Data Visualisation Best Practices
Effective data visualisation communicates insights clearly and accurately. Poor visualisation distorts data, misleads audiences, and obscures rather than reveals patterns. These principles apply whether you are building dashboards, creating data reports, or presenting analysis to stakeholders.
Choosing the Right Chart Type
- Comparison across categories: Bar chart or column chart
- Change over time: Line chart (multiple series) or area chart (single series)
- Part-to-whole: Stacked bar chart or treemap (not pie charts for more than 3-4 segments)
- Distribution: Histogram, box plot, or violin plot
- Correlation / relationship: Scatter plot
- Geographical data: Choropleth map or bubble map
- Single important number: Metric card with trend indicator
Visual Design Principles
- Maximise data-ink ratio: Remove chart junk — gridlines, borders, unnecessary labels — that does not convey information
- Consistent colour encoding: Use colour to encode information, not just decoration. Use a consistent colour for the same category across all charts.
- Accessible colours: Ensure colour combinations are distinguishable for colour-blind users — avoid red/green combinations
- Y-axis starts at zero: For bar charts, always start the Y-axis at zero — truncated axes exaggerate differences
- Clear titles and labels: Every chart should have a title that states the insight, not just the metric name