Sunburst Chart

The Sunburst chart is a hierarchical visualization that displays categorical data as concentric rings, enabling users to explore part-to-whole relationships across multiple dimensions. It is particularly useful for analyzing breakdowns where categories have a natural parent–child structure.

When to Use

Use a Sunburst chart when you want to:

• Visualize hierarchical or multi-level categorical data
• Compare proportions across nested dimensions
• Enable intuitive drill-down exploration within a single chart

Common use cases include population counts by region → country → population, or revenue breakdown by category → item → brand.

Chart Configuration

Query Mode

Sunburst charts operate in Aggregate query mode.

Dimensions

Add one or more categorical columns to define the hierarchy:

• The first dimension represents the inner ring (top-level category)
• Each subsequent dimension adds an outer ring

Example:

1. Region
2. Country
3. Population

The order of dimensions determines the hierarchy displayed in the chart.

Metric

Select a single metric that determines the size of each segment.

• Typically a SUM, COUNT, or COUNT DISTINCT
• The metric is aggregated at each level of the hierarchy

Example:

• SUM(population)
• COUNT(region)

Customize Tab

Color Scheme

Choose a color scheme to differentiate categories.

• Colors are applied consistently across hierarchy levels
• Inner-ring categories define the base color palette

Sort By

Controls how segments are ordered within each ring:

• Metric value
• Alphabetical order of dimension values

Labels

• Labels are shown when there is sufficient space
• Hover tooltips always display full context, including all hierarchy levels and metric values
  

Drill Behavior

Clicking a segment:

• Highlights the selected path across all rings
• Can trigger cross-filters if enabled on the dashboard

This allows the Sunburst chart to function as an interactive control for other charts.

Dashboard Behavior

When added to a dashboard, the Sunburst chart supports:

• Cross-filtering (acting as a filter source)
• Native filters (responding to dashboard-level filters)
• Hover tooltips for detailed context without clutter

Best Practices

• Limit hierarchy depth to 2–4 levels for readability
• Avoid high-cardinality dimensions in outer rings
• Use meaningful ordering of dimensions to reflect analytical intent
• Pair with tables or bar charts when exact values are required