One of the reasons data analysts create data visualizations is to find unexpected and unusual scenarios. The easier it is to get some more detailed information directly within the viz, the better off we all are. Tableau has helped fill that need with their feature, Explain Data. Said to be driven by ‘AI,’ additional insights are provided when Explain Data is requested.
Using a workbook I created for an earlier article, I can further investigate my candy sales data. This is a straightforward example based on very simple data for ease of replication.
First thing first
Correlation does NOT mean Causation
How to activate Explain Data
Within the Tableau Public desktop application, I can click on a data point. For available data points, you will see a small lightbulb. Click that lightbulb.

This creates a pop-up with some more analysis on that data point. If you click on the marked icon (circled in yellow below), the chart is added to the workbook as a new sheet.


Behind the scenes
The focus of the AI-enable analysis of Explain Data is on correlations and relationships between the different data features. This is where I remind you; once again, correlation does not mean causation! The process tries to develop explanations for the value of your data point based on these correlations.

Another Example
My example was very simplistic. Here is an example provided by Tableau:

Resources
Conclusion
As you can see, it is effortless to start using Explain Data within the Tableau application. This can help indicate which data points may require further analysis. This may save you time and can save you from hidden surprises. While the statistical analysis appears limited to relationships and correlation at this time, the door is open for Tableau to develop even more sophisticated analysis.