How do you use Power BI to show heatmaps on a map to represent concentrations of data points such as sales hotspots or customer locations

Question

How do you use Power BI to show heatmaps on a map to represent concentrations of data points, such as sales hotspots or customer locations?

How do you create heatmaps in Power BI to visually represent data point concentrations on a map, such as identifying sales hotspots or customer location density? What steps and considerations are involved in setting up a heatmap using Power BI's mapping features?

pooja · Answer 1 · 5 days

Power BI includes the Azure Maps visual, which can easily be used to heatmap data points, location, or other data attributes, for example, sales hotspots and customer locations. Heat is, in general, understood as an action to visualize and analyze the geographical density of data. Important considerations and steps are listed below for properly setting up such a heatmap:

How to Create Heatmaps in Power BI

Enable Azure Maps Visual:

Open your Power BI report and go to the "Visualizations" pane.

Ensure the Azure Maps visual is enabled in the "Options" menu under "Preview features." If necessary, Restart Power BI Desktop.

Add the Azure Maps Visual:

Drag and drop the Azure Maps visual from the "Visualizations" pane onto the canvas.

Select your dataset that composes location-based attributes of, say, latitude, longitude, or addresses.

Configure the Heatmap Layer:

In the Azure Maps visual, go to the "Layer" settings and, most importantly, add a" Heatmap layer."

Map fields accordingly:

Drag latitude and longitude fields to "Location."

If you intend to modify the impacts of heat intensity, e.g., sales volume or the number of customers, add a measure, optionally, in case or field to the "Weight" input.

Modify Visualization Settings:

Refine your visualization using the "heatmap" parameters:

Adjust the Radius to determine the area of influence exerted by each point.
Modify the Intensity to fine-tune color density as a function of the density of data concentration.
Set the Color Gradient according to which a color gradient would suffice to view the heatmap as visually distinguishable from the adjacent area.

Customize the Map View:

Under "Map settings," select the base map style you prefer, such as road, satellite, or dark mode.

Zoom and Pan Around a Location:

Test Interactivity:

Add slicers and filters to let users interact with a heat map over time or temporal, area-specific, or otherwise differentially slice data.

Considerations for Effective Heatmap Creation:

Data Quality: Ensure the location data is accurate and complete; incorrect or missing coordinates skew the heat map. Scalability: Aggregate the data before plotting for large datasets to improve performance and readability. Context: Add contextual labels, tooltips, or legends to help users interpret the heatmap correctly. Privacy: Be sensitive when visualizing customer locations.