Choosing the right chart type
Match the chart to the relationship you want to show. Trends over time → line or area charts. Part-to-whole → bar or stacked bar (pie only for few segments). Comparison across categories → horizontal bar when labels are long.
Scatter plots reveal correlation; heatmaps show density across two dimensions. Tables still beat the wrong chart — use them when exact values matter more than shape.
DashBoardly AI can suggest chart types from your columns, but you should override when domain knowledge says a different view tells the story better.
Reducing clutter
Remove gridlines, borders, and data labels that do not change the conclusion. Whitespace is not wasted space — it guides the eye.
Limit series count: if a legend has more than five items, consider small multiples, faceting, or a “top N + other” summary.
Use interactive filters instead of static copies of the same chart for every region or program.
- One idea per chart
- Short titles that state the takeaway
- Consistent date formats and number precision
- Annotations only for events that explain a spike or drop
Using color effectively
Sequential palettes work for ordered values (low → high). Categorical palettes work for distinct groups — assign colors once and reuse them across related dashboards.
Check contrast for accessibility: color-blind-friendly palettes and sufficient contrast between text and background improve reach and compliance.
Do not encode two meanings in one color (e.g., red = bad and red = Category A). Use shape or position for a second dimension when needed.
Common visualization mistakes to avoid
Truncated y-axes exaggerate small changes. Start at zero for bar charts unless there is a documented reason not to.
Dual axes invite misleading correlations. Prefer normalized indexes or separate charts when scales differ wildly.
Animation and 3D rarely add clarity in business dashboards. Prefer static views with clear labels for reports and exports.
- Pie charts with many thin slices
- Unlabeled axes or missing units
- Cherry-picked date ranges
- Decorative icons that compete with data