The Effective Statistician - in association with PSI
Exploration Or Explanation: 10 Key Differences For Data Visualisations
May 21, 2024
Data visualization expert Alexander Schacht discusses key differences between exploratory and explanatory data visualizations, emphasizing design, audience, interaction, and impact. Understanding these concepts can enhance data communication and insight discovery.
24:47
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Quick takeaways
- Data visualizations can serve two primary purposes: explaining and exploring, each tailored to deliver specific messages or uncover patterns within the data.
- The design of data visualizations varies based on their purpose, with explanatory visuals focusing on customization for specific audiences and exploratory visuals having a technical appearance supporting in-depth analysis.
Deep dives
Explaining vs. Exploring Data Visualization
Data visualizations can serve two primary purposes: explaining and exploring. When explaining data, visualizations are tailored to deliver a specific message to a known audience, like figures in clinical trial reports for regulators. On the other hand, exploratory visualizations, facilitated by tools such as Spotfire or Shiny apps, emphasize understanding and uncovering patterns within the data without a predefined story. Understanding these distinctions is crucial to harnessing the full potential of data visualization.
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