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Charts and Data Story

How to use suggested charts, chart controls, exploratory visual checks, and AI-generated data story sections.

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Charts And Data Story

The Charts module turns profile outputs into visual checks. Suggested charts are generated from the profile and can be adjusted before saving.

Chart selection logic

Supported Chart Types

The workbench supports:

  • Column and Bar charts for category comparison
  • Line and Area charts for ordered or time-like trends
  • Scatter charts for numeric relationships
  • Histogram charts for distributions
  • BoxAndWhisker charts for spread and outliers
  • Heatmap views for correlation-like or matrix-like comparisons

Chart Controls

For each suggested chart, reviewers can choose the chart, switch chart type, change X and Y fields where valid, select a palette, and toggle labels or legend. These edits help prepare a chart for a report without changing the underlying profile metrics.

Choosing The Right Chart

Use charts as evidence checks:

  • distribution charts help identify skew, zero inflation, and tails
  • category bars help reveal concentration or unexpected levels
  • line or area charts help evaluate trend and seasonality
  • scatterplots help inspect relationships and possible clusters
  • box plots make outliers and spread easier to compare
  • heatmaps help scan many pairwise values

Avoid Overclaiming

A chart produced from a profile is exploratory. It should not be presented as causal proof. If a chart suggests a decision-relevant relationship, document the hypothesis and decide whether a deeper analysis is needed.

Data Story

When AI interpretation is available, the profile can include a data story. A story section links a narrative, columns, a supporting chart, a takeaway, and a next action. The report editor lets the team keep, revise, or remove that narrative before export.