Where is Heatmap in Power BI?

Trying to find the dedicated "Heatmap" chart in Power BI can feel like a bit of a scavenger hunt because it's not a standalone visual. A heatmap is actually a formatting feature you can apply to other visuals to bring your data to life with color. This article will show you exactly where to find and how to create the two most common types of heatmaps: in a table or matrix and on a geographic map.

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What is a Heatmap in Power BI, Really?

Before jumping into the "how," let's clarify what a heatmap is. It's a data visualization technique that uses a color spectrum to represent the magnitude of individual values. Typically, you'll see a range from cool colors (like blue or green) for lower values to warm colors (like orange or red) for higher values. This makes it incredibly easy to spot trends, hotspots, and outliers at a glance without reading a single number.

In Power BI, this concept is applied in two primary ways:

• Tabular Heatmaps: This involves applying color gradients to the background of cells in a Table or Matrix visual. It's perfect for comparing performance across multiple categories, like seeing which products sold best in which regions.
• Geographic Heatmaps: This style displays the density or intensity of data points on a map. It's ideal for understanding geographic concentrations, such as where your customers are clustered or which areas generate the most support tickets.

Now, let's build both.

How to Create a Table Heatmap with the Matrix Visual

The most common way to create a heatmap is by using conditional formatting on a Matrix visual. It’s a powerful way to analyze performance across two different dimensions. Let's imagine we want to see our monthly sales performance for different product categories.

Step 1: Add a Matrix Visual to Your Report

First, drag a Matrix visual from the Visualizations pane onto your report canvas. This visual is perfect for our heatmap because it allows you to neatly organize data by rows and columns.

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Step 2: Add Your Data Fields

For this example, let's build a view of sales performance. In the Fields pane, find your data fields and drag them to the wells in the Visualizations pane:

• Drag ‘Product Category’ to the Rows well.
• Drag ‘Month’ to the Columns well.
• Drag ‘Total Sales’ to the Values well.

You’ll now have a standard matrix showing sales figures. It’s useful, but it takes effort to scan and compare the numbers. Here’s where the heatmap magic comes in.

Step 3: Find the Conditional Formatting Options

With the matrix visual selected, navigate to the Format your visual pane (the paintbrush icon). Look for the section called Cell elements and expand it.

Here, you'll see your data field (‘Total Sales’ in our case). You can apply conditional formatting options to it, such as Background color, Font color, Data bars, and Icons. For our heatmap, we care about the Background color.

Step 4: Configure the Heatmap Colors

Turn the toggle for Background color to On. Power BI will apply a default color gradient, but to make a proper heatmap, you’ll want to customize it. Click the fx button next to the toggle to open the advanced formatting window.

In this window, you have full control over the color logic:

• Format style: Make sure this is set to Gradient.
• What field should we base this on?: This should already be set to your value field, Sum of Total Sales.
• How should we format empty values?: You can choose a specific color for blanks or just leave them unformatted.
• Minimum: For the lowest values, choose a light, "cool" color. Click the color dropdown and pick a light blue, light gray, or green.
• Maximum: For the highest values, choose a dark, "warm" color. A deep red or vibrant orange works well.

Pro Tip: For even better insights, you can add a center color by clicking the "Add a middle color" checkbox. This creates a diverging color scale, which is great for highlighting values that stray from a midpoint or average. For example, you could have low values in blue, average values in white, and high values in red.

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Step 5: Apply and Refine

Click OK. Your matrix is now a heatmap! The cells with higher sales figures will stand out in warm colors, making it instantly clear which categories performed best in which months. You can easily spot seasonal trends or consistently underperforming categories.

You may also want to format the font color so text doesn't get lost on dark backgrounds. Go back to Cell elements and turn on the Font color option. You can set it up similarly, perhaps making the font white for high values (dark backgrounds) and black for low values (light backgrounds) for maximum readability.

How to Create a Geographic Heatmap

What if you want to see the geographic concentration of your data? Power BI's map visuals can be configured to show a heatmap layer, which is perfect for identifying hotspots.

Step 1: Choose a Map Visual

Start by adding an Azure Map visual to your canvas. While the standard Map visual also supports some heatmap functionality via bubble size/color, the Azure Map has a dedicated heatmap layer that offers more control and better performance.

Note: If you don't see the Azure Map in your Visualizations pane, your Power BI admin may have disabled it, or you might need to enable it in File > Options and settings > Options > Global > Security.

Step 2: Add Location and Data

Next, provide the map with your data. Let's say we want to visualize order density by location.

• Drag a location field like ‘City’ or 'Postal Code' to the Location well.
• You can leave the other wells empty, as the heatmap will be based on the density of data points by default. Alternatively, you can add a measure like ‘Order Count’ to the Size well to weight the map by a specific value.

Step 3: Enable the Heatmap Layer

With the Azure Map selected, open the Format your visual pane. Scroll down and expand the Heat map layer settings. Simply switch the toggle to On.

Instantly, your map will transform from showing individual points to displaying a colorful overlay representing the density of those points.

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Step 4: Customize the Heatmap Appearance

Inside the Heat map formatting options, you can fine-tune the visualization:

• Radius: This setting controls how far each data point's "heat" extends. A smaller radius is good for dense, specific areas, while a larger radius can help visualize broader regional trends.
• Opacity: Adjusts the transparency of the heatmap layer, allowing you to see the map underneath more clearly if needed.
• Color scale: Just like with the matrix visual, you can customize the gradient here. Define your colors for low, middle, and high intensity to match your report's theme or make the hotspots pop.
• Intensity Unit: You can choose whether the intensity is based on simple point density or weighted by a value from the Size field.

Alternative: Using Custom Visuals from AppSource

If the built-in conditional formatting or map layers don't meet your specific needs, the Power BI marketplace (AppSource) is filled with custom visuals built by third parties.

To access it, click the three dots (...) at the bottom of the Visualizations pane and select Get more visuals. From there, you can search for "heatmap." Some popular options include:

• Heatmap by MAQ Software: A highly customizable visual that functions much like the matrix heatmap but offers more control over labels and formatting.
• Calendar visual: Several calendar visuals on AppSource include built-in heatmap functionality. This is fantastic for visualizing daily activity levels, like daily website sessions or ticket volume, over an entire month or year.

Always review the publisher information and recent reviews before importing a custom visual into your report.

Final Thoughts

Power BI brilliantly integrates heatmap functionality not as a standalone visual, but as a powerful formatting option within core visuals like the Matrix and Azure Map. By mastering conditional formatting for tables and a few simple toggles on maps, you can quickly transform dense datasets into visually intuitive reports that reveal insights in an instant.

Manually creating reports and finding the right settings, even for something as common as a heatmap, still involves a lot of clicks and adjustments. Instead of working through different menus to set up your visuals, at Graphed we've created a far simpler process. You can just ask a question like, "create a heatmap of our Shopify sales by product type and state for last quarter," and we instantly build the correct visualization, live with your data. We streamline the entire reporting process from connecting data to getting answers, giving you back time to focus on strategy instead of report building.