Sunburst Chart: How It Works and When to Use It

Key Takeaways

• A sunburst chart shows hierarchical part-to-whole data as concentric rings, with each ring adding another level to the structure.
• Use one when parent-child relationships matter as much as the values, and keep the visible hierarchy small enough to trace.
• Choose a bar chart for precise comparisons, a donut chart for one level, an icicle chart for deep paths, or a treemap for many categories.
• Prepare one clean row for each leaf-level path, use positive values, and remove subtotals before you build the chart.
• Add filtering, tooltips, breadcrumbs, or drill-down when readers need to move beyond the first visual answer.

A sunburst chart can clarify a hierarchy in seconds, or leave you tracing tiny wedges around a crowded circle. The difference starts with chart choice, clean data, and a clear question, long before you pick colors.

In this guide, you will learn how a sunburst diagram works, when it fits your analytical task, and how to prepare the source table. You will also see practical design checks that make each ring easier to read and use as a starting point for analysis.

What Is a Sunburst Chart?

A sunburst chart is a hierarchical data visualization built from concentric rings. The center represents the root, total, or highest level, while each ring moving outward adds another level of detail.

Each wedge represents a category, and its angular span shows that category’s value within its parent. Children sit directly outside their parent. You can follow one branch from the center to the edge and see how a total breaks into smaller parts.

Suppose you want to analyze revenue by region, country, and product line. The center could represent total revenue, the first ring could split that total by region, the second by country, and the third by product line.

To read the sunburst plot, start near the center and follow one branch outward. If you jump between outer wedges without checking their parent categories, you may compare values that belong to different totals.

A sunburst graph may look like a multilevel donut chart, but the two serve different questions. A donut chart shows one level of part-to-whole composition, while a sunburst chart preserves several connected hierarchy levels.

That distinction matters when lineage is part of the question. For regional revenue alone, a donut or bar chart may be clearer. Nested rings add context when you also need country and product line contributions inside each region.

Research also shows why you should describe hierarchy studies precisely. A 2019 IEEE study of hierarchy visualization used a six-person pilot that included sunbursts. Its separate 12-person controlled study compared treemaps, icicle plots, and sundown charts.

The controlled study did not compare the full sunburst chart. That boundary keeps the research useful without stretching it into a claim the paper did not test.

When Should You Use a Sunburst Chart Instead of Another Chart?

Use a sunburst chart when your data has a meaningful parent-child structure and your reader needs to see composition across several levels. The chart works best when the hierarchy is compact, values are positive, and the branches remain large enough to follow.

A strong use case might show support volume by business unit, team, and issue type. Another could show expenses by department, cost center, and category, as long as each child belongs to one clear parent.

The radial structure earns its space when nesting carries meaning. If the hierarchy is incidental, or if your main task is comparing close values, another chart will usually answer the question faster.

A 2020 IEEE evaluation of hierarchical charts tested five methods. The charts were treemaps, icicle plots, sunbursts, circular treemaps, and bubble treemaps.

The 2020 IEEE study favored sunbursts and circular treemaps overall for its large-hierarchy condition. Treemaps, icicle plots, and circular treemaps performed best for its small-hierarchy condition.

Those findings were task- and hierarchy-size-dependent, so they do not make sunbursts universally best. The study used synthetic data, static images, size and color comparison tasks, and 17 participants, which differs from an interactive business intelligence workflow.

Treat chart selection as the start of analysis rather than a styling decision at the end. Pick the view that matches the question, test whether readers can complete the task, and keep another chart ready when the question changes.

Before you commit, ask what the reader must judge: composition, comparison, depth, or density. A sunburst chart is a good answer only when nested composition is the real task.

How Should You Prepare Data for a Sunburst Chart?

A readable sunburst chart starts with a tidy hierarchy table. Use one column for each level, one row for each leaf-level path, and one positive numeric measure for the wedge size.

Here is a compact revenue example. The columns move from the broadest level to the most detailed level:

Each row describes one complete path from region to country to product line. Your charting layer can aggregate the revenue values upward, so the source table should not include region or country subtotal rows.

Subtotal rows can double-count values if the chart sums both parents and leaves. Keep the lowest-level observations in the source, then let the aggregation logic calculate each parent total.

Consistent labels also matter. “United States,” “US,” and “U.S.” may become three separate nodes, so standardize names before you build the hierarchy.

Blanks need an explicit decision as well. You can correct the source value, map a missing level to a clearly named category, or remove the record when your analysis rules permit it.

Use the following validation checklist before charting. These checks catch common rollup errors before they reach the visual:

• Confirm that every child belongs to one parent within the hierarchy.

• Check that leaf values roll up to the expected parent totals.

• Review duplicate paths and decide whether to aggregate or correct them.

• Resolve blank labels at every hierarchy level.

• Apply one consistent metric definition across every row.

• Remove subtotal and grand total rows from the source table.

• Verify that the measure contains positive values suited to part-to-whole display.

Metric consistency becomes more important when the same hierarchy appears across several dashboards. If one view defines revenue as booked revenue and another uses recognized revenue, matching labels can still produce conflicting answers.

Governance gives each chart a shared definition for the metric, hierarchy, and aggregation. ThoughtSpot product pages describe governed live data connections across business apps, warehouses, databases, and data lakes. Those connections support governed live or cached queries.

A shared metric definition can support several views without changing the business meaning. ThoughtSpot describes governed analytics across more than 30 sources, giving you a consistent starting point when a hierarchy spans different systems.

Before publishing, reconcile the sunburst totals against a simple table. If the numbers disagree, fix the data model or aggregation before you adjust labels, colors, or ring spacing.

How Do You Design a Sunburst Chart People Can Actually Read?

A technically correct sunburst chart can still fail if readers cannot follow a branch. Start by limiting the visible hierarchy to the levels that support the question, then move deeper detail behind a filter or drill-down.

There is no universal number of rings that works for every dataset. A practical limit is the point where labels stop fitting, wedges become hard to select, or readers lose track of parent-child paths.

If a category has a long tail of tiny values, group them into an “Other” category with a stated rule. For example, you might group categories below 2% of their parent, but only when that threshold fits the analytical purpose.

Keep the sort order consistent within each parent. A stable order helps readers compare related branches, while arbitrary ordering makes each ring feel like a fresh puzzle.

Use color to show category identity or a second meaningful variable. Avoid using color to repeat the same measure already encoded by wedge size, since the duplicate encoding adds little information.

Color should never carry the full explanation by itself. Pair it with readable labels, tooltips, patterns where appropriate, or direct text that gives each category another cue.

Outer rings often contain more wedges than the center, so label space disappears quickly. Hide labels that do not fit rather than shrinking every label, and reveal the full category name in a tooltip.

For an interactive view, breadcrumbs help readers see the active path from root to leaf. Tooltips can show the value, share of parent, share of total, and category name without crowding the circle.

A clear title should state the analytical takeaway or question. “Revenue Mix by Region, Country, and Product Line” gives the reader useful context. “Where Services Revenue Is Concentrated” gives the view a sharper purpose.

Run this short pre-publish check. Review the chart at the same size your audience will see:

• Can you trace each visible branch from the center outward?

• Do the labels remain readable at the intended display size?

• Does “Other” follow a clear and repeatable grouping rule?

• Does color communicate meaning without becoming the only cue?

• Do tooltips show the value and its relevant parent context?

• Does the title state the question or takeaway?

• Can a table or alternate chart support precise comparisons?

When a close comparison matters, pair the sunburst diagram with a sortable table or bar chart. The sunburst can show structure, while the companion view handles exact ranking and small differences.

How Can You Turn a Sunburst Chart into a Starting Point for Analysis?

A sunburst chart often raises a better follow-up question than the one you started with. You may notice one region with an unusual product mix, a fast-growing branch, or a category whose share changes across periods.

That moment is where interaction matters. Let the reader filter the hierarchy, select a branch, or change the time range. They can also compare the same metric in a different chart.

Begin with a governed metric and a hierarchy that matches the business question. Build the first view, inspect the largest and smallest branches, then test the pattern with a table, bar chart, or another relevant visual.

Next, let stakeholders ask follow-up questions without changing the metric definition. They might filter to one country, drill into a product line, or compare the branch against a prior period.

ThoughtSpot describes SpotterViz as interpreting a business question, validating metrics against certified definitions, and building a dashboard; the same page describes interactive Liveboards.

The analytical sequence stays straightforward. Each step keeps the question and metric connected:

1. Start with a governed metric that everyone interprets the same way.

2. Select a hierarchy whose levels match the question.

3. Build a first visualization and check whether it communicates the structure.

4. Filter or drill into branches that need more context.

5. Test another chart when comparison, depth, or density becomes the main task.

6. Keep the metric definition fixed as the view changes.

You do not need to force every question into the sunburst format. When the task shifts, the chart should shift with it, while the underlying definition stays stable.

Use the sequence on your next hierarchy. Then ask a simple question: can your reader reach the next answer without losing trust in the metric?

Make the Hierarchy Clear, Then Make It Useful

Choose a sunburst chart when nested composition matters and the hierarchy is intentionally compact. Use clean positive values, stable parent-child paths, readable labels, and interaction that helps readers move beyond the first view.

When precise comparison, deep paths, or high category counts dominate, choose a bar chart, icicle chart, or treemap instead. The best result is not a particular shape; it is a clear answer backed by a definition your readers trust.

Start with the business question, keep the metric stable, and choose the clearest view for the task. Then let the next question guide the next view.