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Data storytelling

As explained in Everyday Data Visualization

The practice of communicating data insights through a narrative shaped for an intended audience.

Data storytelling communicates an insight through a narrative shaped for a particular audience. The audience is not a decorative afterthought: a beautiful visualization fails if people cannot understand its message or use it. Talk with intended viewers early and often, then check whether the developing work answers their questions without becoming too complex. section 1.3

A practical storytelling pattern keeps the narrative clear:

  • State what viewers will see in the title. section 6.1.5
  • Show the message visually through the chart, using gestalt principles and preattentive attributes. section 6.1.5
  • Reinforce the point with data labels, annotations, and callouts. section 6.1.5
  • Choose a specific audience rather than trying to satisfy everyone; focus makes the message more useful. section 1.3

The rhino-poaching chart

A chart titled “The Dramatic Rise of Rhino Poaching” reveals its conclusion immediately, then supports it with a trendline and a callout. Giving away the ending does not spoil the story; repeating the message through words and visuals helps viewers grasp it. section 6.1.5

How Everyday Data Visualization covers it

How deep it goes
Explains audience alignment and a title-chart-annotation structure, but stops short of tool-specific implementation.
Examples
Uses a rhino-poaching chart whose title, trendline, and callout repeat the same central message.
What you can do after
Evaluate visualizations for audience understanding, message clarity, and potential action.
How it connects
Connects data visualization with gestalt principles, preattentive attributes, trendlines, data labels, annotations, and callouts.

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This explainer was generated by Manning's knowledge graph from the text of Everyday Data Visualization. The section links point to the parts of the book it draws on.