So, finally, we need to get a good picture of how to create those heatmaps in Power BI, representing concentrations of sales all the way up to customer density. Ideally, it would be something like these:
Prepare your Data: Your dataset must have geographical coordinates, such as latitude and longitude, or else it should capture some location information, such as city, region, or postal code. Clear All: Remove duplicates and ensure that the necessary fields are correct.
Add Map Visual: Open your Power BI report and add either the "Map" or "Azure Maps" visual from the Visualizations pane. These are designed to work particularly for geographic data and can even provide heatmap functionality.
Plot Your Data: Drag the location fields (e.g., city or coordinates) into the "Location" bucket of the Map visual. To represent it as a heat map, also include a numeric field, like sales volume or customer count, in the "Size" bucket to determine the intensity for each site on the Map.
Enable Heatmap Layer (Azure Maps Visual): If you are working with the Azure Maps visual, go to the "Format" pane and into the "Layers" section to enable the "Heatmap" option. Set the Track Parameters: You might also set the parameters of the track set according to your data visualization objectives—for example, intensity, radius, and transparency.
Customizing the Visual: You can adjust Color gradients, Point Density, and Map Styles using formatting options. For instance, select a gradual, like blue to red, for high concentrations.
Test And Validate: Check that the heatmap accurately reflects the data. Validate it against other visuals or reports to ensure conformity, especially when dealing with sensitive business metrics.
With this, you will be ready to use everything that Power BI has to offer in its mapping features to create impressive-looking heatmaps that demonstrate patterns and insights.
