What is Power Map in Power BI?

If you're trying to plot sales by state or visualize customer addresses on an interactive map, you might have heard of a tool called Power Map. This article will walk you through exactly what it is, its evolution from Excel to Power BI, and how you can create powerful map visualizations in Power BI today using its modern, built-in tools.

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What Ever Happened to Power Map?

First, let’s clear up a common point of confusion. "Power Map" was originally an Excel add-in that allowed you to create interactive, 3D globes and maps from your spreadsheet data. It was an amazing tool for its time and eventually got renamed to "3D Maps," becoming a standard feature within Excel.

So, where is Power Map in Power BI? The short answer is: it doesn't exist as a separate feature with that name. Instead, Power BI integrates the core functionality of geographic data visualization directly into its report builder with several different "visuals" that are more powerful and flexible than the original Excel tool.

When people search for "Power Map in Power BI," they're really looking for how to create these geographic charts. Let's cover the main types of map visuals available in Power BI and how you can use them.

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Meet the Core Map Visuals in Power BI

Power BI offers a few different ways to plot your location-based data. The two most common and useful built-in visuals are the 'Map' and the 'Filled Map.' Each serves a slightly different purpose.

1. The Basic Map Visual (Bubble Maps)

The standard Map visual plots your data as circles, or "bubbles," on specific geographic points. The size of the bubble can represent a numerical value, making it easy to see where your biggest customers, largest sales, or most active locations are.

Use this when: You want to show data for specific points like cities, postal codes, or exact street addresses.

How to Create a Bubble Map in Power BI

Let's walk through an example. Imagine you have some basic sales data for stores in different US cities.

Your data might look something like this:

Store, City, State, Sales
Store A, Los Angeles, CA, 120000
Store B, Phoenix, AZ, 85000
Store C, Seattle, WA, 110000
Store D, Denver, CO, 95000
Store E, Austin, TX, 105000

Here’s how to turn that data into a bubble map.

• Step 1: Prepare Your Location Data. Before you start, make sure Power BI can understand your locations. The best way is to have separate columns for different geographic levels like Country, State, City, and Postal Code. For ultimate accuracy, use latitude and longitude columns. Power BI's geocoding engine (Bing Maps) is smart, but being specific helps avoid errors.
• Step 2: Add the Map Visual to Your Report. In Power BI Desktop, look at the Visualizations pane on the right. Find the icon that looks like a small globe and click it to add a blank map to your report canvas.
• Step 3: Move Fields into the 'Location' Well. In the Fields pane, find your location data. Drag your 'City' and 'State' columns into the 'Location' field in the Visualizations pane. Power BI will read the data and start plotting points on the map.
• Step 4: Use a Measure to Size Your Bubbles. Right now, all the bubbles are the same size. To make the map insightful, drag your 'Sales' field into the 'Bubble size' well. The bubbles will instantly resize based on their sales value - larger bubbles mean higher sales.
• Step 5: Format Your Map. Click the paintbrush icon in the Visualizations pane to open the Format visual options. Here you can tweak everything:

In just a few clicks, you now have an interactive bubble map that clearly shows where your highest-performing stores are located.

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2. The Filled Map Visual (Choropleth Maps)

Unlike a bubble map that shows points, a Filled Map colors entire regions, like countries, states, counties, or zip codes. The intensity of the color represents a value. This is also known as a choropleth map.

Use this when: You want to show how a metric varies across regions and compare them, like sales per state or population density per country.

How to Create a Filled Map in Power BI

Let's use a similar dataset, but this time it's aggregated by state.

State, Profit, Region
California, 76000, West
Washington, 45000, West
Arizona, 21000, West
Illinois, 55000, Midwest
Texas, 68000, South

Here's how to visualize this in a filled map.

• Step 1: Check Your Regional Data. Make sure your data contains a column with well-defined geographic regions. Full state names ('California') or standard two-letter abbreviations ('CA') work best.
• Step 2: Add the Filled Map Visual. In the Visualizations pane, click the icon that looks like a shaded map to add a Filled Map visual to the canvas.
• Step 3: Drag the Region into the 'Location' Well. Take your 'State' field and drop it into the 'Location' area in the Visualizations pane. Power BI will identify the states and outline them on the map.
• Step 4: Control Color Saturation With a Measure. The map isn't very useful yet. To add meaning, drag your 'Profit' field into the 'Color saturation' well. The states will now be shaded based on their profit values. By default, higher values get a darker shade of a single color.
• Step 5: Customize the Colors and Tooltips. In the Format visual section:

Want More Power? Try ArcGIS Maps for Power BI

If the built-in map options aren't quite enough, Power BI has a certified visual for ArcGIS Maps, developed by Esri, the world leader in geographic information systems (GIS). This visual brings a new level of geospatial analytics to your reports.

With ArcGIS, a free version of which is included in Power BI, you can:

• Use Better Basemaps: Access a library of high-quality basemaps, including satellite imagery, topographic maps, and street maps.
• Add Demographic Layers: Overlay your data with valuable demographic information, like average income, population density, or age, for a specific region.
• Perform Geospatial Analysis: Use tools to create drive-time zones (e.g., "show me all customers within a 10-minute drive of our new store") or find hotspots.

To use it, simply select the ArcGIS Maps for Power BI visual from the Visualizations pane and start dragging your location data in. While it has a slightly higher learning curve, it opens up a far wider range of possibilities for geographic analysis.

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Best Practices for Creating Good Map Visuals

Building a map is easy, but building a good map takes a little thought. Here are a few tips to make your geographic visualizations clear and insightful.

• Clean Your Location Data. Geographic data is notoriously messy. A typo like "Arizna" instead of "Arizona" can cause that data point to go missing. Before you build, scan your location columns for misspellings, abbreviations, and inconsistencies.
• Use Latitude and Longitude When You Can. For pinpoint accuracy with bubble maps, nothing beats latitude and longitude. Place names can sometimes be ambiguous (think Paris, Texas vs. Paris, France), but coordinates are always unique.
• Avoid Clutter. Too many bubbles on a map becomes an unreadable mess. If you have thousands of data points, consider using filters or summarizing your data by a larger region (like state or postal code) to keep the visual clean and focused.
• Think About Color and Size. Your use of color and size should be intuitive. A big bubble should always mean "more" of something important (sales, customers). With filled maps, use a color palette that makes sense for your data - a diverging red-to-green palette is great for showing profit and loss.

Final Thoughts

While the specific "Power Map" feature from Excel isn't in Power BI, its spirit lives on. Power BI's built-in map visuals are robust, user-friendly tools that empower you to turn your rows of location data into insightful, interactive maps that reveal geographic trends and patterns.

Setting up maps in Power BI is a fantastic way to begin visualizing your data. As your needs grow, you'll start pulling in marketing and sales data from other sources like Google Analytics, Shopify, or Salesforce, and connecting everything manually can become a job in itself. At Graphed, we handle that friction by letting you connect all of your data sources in one place and build custom dashboards just by asking questions in plain English. No more hours spent wrangling data, just fast and clear insights.