How to Make a Map in Tableau

Transforming rows of location data into an insightful map is one of the most effective ways to tell a data story. Instead of just seeing which state has the highest sales in a spreadsheet, you can instantly spot regional trends, pinpoint clusters of activity, and bring your geographic data to life. This guide will walk you through exactly how to create, customize, and troubleshoot maps in Tableau.

Why Use Maps in Your Dashboards?

Maps do more than just make your dashboard look nice. They provide geographic context that simple bar charts or tables can't. When you plot your data on a map, you unlock a different level of analysis, allowing you to answer questions like:

• Which sales territories are underperforming or exceeding targets?
• Where are our website visitors concentrated?
• Are support ticket volumes higher in certain urban areas?
• How does shipping performance vary by region or country?

By visualizing data geographically, patterns that were hidden in plain sight within your spreadsheets can become immediately obvious. A map might reveal a surprising cluster of low engagement in a specific region or a high-performing corridor of markets that you can investigate further.

Prepping Your Data for Mapping in Tableau

Before you can start building, Tableau needs to understand your geographic data. A clean and properly formatted dataset is the foundation of any good map. Fortunately, Tableau is smart enough to handle most common location types automatically.

Understanding Geographic Roles

Tableau recognizes common geographic data fields and assigns them a "Geographic Role." This tells Tableau that a column of data contains things like cities, states, or zip codes, not just random text. When you connect your data, Tableau automatically scans your field names and assigns roles to common ones like:

• Country
• State / Province
• City
• County
• ZIP Code / Postcode
• Airport

You can see if a field has been assigned a geographic role by looking for a small globe icon next to it in the Data pane on the left side of your screen. If Tableau missed one, you can assign it manually by right-clicking the field, selecting Geographic Role, and choosing the correct option from the list.

When to Use Latitude and Longitude

For most analyses at the country, state, or city level, Tableau's built-in geocoding is all you need. However, if you need to map highly specific locations - like individual store addresses, sensor locations, or specific coordinates for a logistics analysis - you'll need to provide latitude and longitude values yourself. Your data should have two separate columns, one for latitude and one for longitude. Tableau will recognize these and use them to plot points with precision.

A Few Data Prep Tips:

• Standardize spellings: Ensure consistency. For example, use "United States" or "USA" throughout your dataset, but not both.
• Avoid extra characters: Remove any commas, periods, or other characters from your location fields that aren't part of the name itself.
• Check for ambiguity: If you're mapping cities, including State and Country fields can help Tableau differentiate between places with the same name, like Springfield, Illinois, and Springfield, Massachusetts.

Creating Your First Map: A Step-by-Step Guide

Let's build a simple but powerful map that a marketing or sales team might use: showing sales performance by state. For this example, we'll use Tableau's sample "Superstore" dataset that comes included with the software.

Step 1: Connect to Your Data Source

Open Tableau and in the "Connect" pane, select your data source. Since we're using the sample data, click on Tableau's Saved Data Sources and choose Sample - Superstore. This will load the dataset and take you to the main worksheet view.

Step 2: Assign a Geographic Role (If Needed)

In the Data pane on the left, you'll see your dimensions and measures. Scroll down to the location fields like City, Country/Region, State, and Postal Code. Tableau is pretty good at this, so you should see the small globe icon next to each of them automatically. If State didn't have a globe, you would right-click it, go to Geographic Role, and select State/Province.

Step 3: Generate the Basic Map

This is often the easiest part. Simply find your main geographic field - in this case, State - and double-click it.

When you do this, Tableau automatically does two things:

1. It adds Latitude (generated) and Longitude (generated) fields to the Rows and Columns shelves. These are the coordinates Tableau creates for each state.
2. It creates a map view, placing a dot on each state present in your data.

You have a map! It's basic, but it's a start. Now let's make it tell a story.

Step 4: Add Your Business Data to the Map

Your map currently shows where your data is located but doesn't tell you anything about performance. Let's change that by using a measure, like Sales.

From the Data pane, find the Sales measure and drag it onto the Color card in the Marks pane. Instantly, your map will change. The dots will be colored based on the sum of sales for each state, with a legend appearing on the right to show you what the colors mean. States with higher sales will be a darker shade.

To add another layer of detail, drag the Profit measure onto the Size card. Now, not only will the dots be colored by sales, but their size will be determined by profit. A large, dark blue dot means a state has high sales and high profit, while a small, light blue dot represents a less successful one.

Exploring Different Types of Tableau Maps

The symbol map we just created is great, but Tableau offers several other types. You can switch between them using the dropdown menu on the Marks card.

Filled Maps (Choropleth Maps)

Instead of plotting a single point, a filled map shades the entire geographic area (like the state boundary) according to your measure. This can be more visually impactful for showing regional comparisons.

When to use it: Perfect for displaying ratios or rates like population density, election results, or percent-of-total sales.

How to create one: With your basic map open, simply click the Marks dropdown menu where it probably says "Automatic" and select Map (not Symbol Map).

Density Maps (Heatmaps)

Density maps are excellent when you have lots of data points that are close together and overlapping. Instead of trying to show thousands of individual dots, a density map visualizes the concentration of points as warm or cool "hotspots."

When to use it: Analyzing clusters of events, like crime incidents in a city, bike-share pickups, or customer locations in a dense urban area.

How to create one: Change the Mark type from "Automatic" to Density. You can then adjust the color and intensity to best highlight the patterns.

Customizing and Enhancing Your Map

A good map isn't just accurate, it's also clear and easy to understand. Tableau gives you plenty of options to refine the look and feel.

Improve the Tooltip

The tooltip is the box that appears when you hover over a mark on your map. By default, it shows the fields you've used. You can make it much more useful by dragging other measures or dimensions onto the Tooltip card.

For example, you could drag Category and Sales to the tooltip. Now, when you hover over a state, you'll see a breakdown of sales by category for that specific state, adding a layer of detail without cluttering the map itself.

Adjust Colors and Sizing

Don't just stick with the default blue. Click the Color card and select Edit Colors. Here, you can choose from dozens of color palettes. A red-green diverging palette is great for showing profit (positive) and loss (negative), while a sequential orange-blue palette might be good for revenue.

Similarly, you can click the Size card to adjust how Tableau scales the circles in your symbol map to prevent them from becoming too large or too small.

Use Map Layers

Tableau's base maps are highly detailed. You can customize them by going to the top menu and clicking Map > Map Layers. This opens a panel where you can turn various layers on or off, such as:

• Streets and Highways
• Place Names
• County Borders
• Demographic data (for US maps, Tableau includes layers for population, income, and age)

This allows you to add extra context to your data - for instance, overlaying household income data to see if it correlates with your customer locations.

Common Problems and How to Fix Them

Sometimes your map doesn't quite work on the first try. Here are two of the most common issues and how to resolve them.

Dealing with "Unknown" Locations

Occasionally, you'll see a small gray indicator in the bottom-right corner of your map that says something like "12 unknown." This means Tableau couldn't recognize one or more of your locations.

How to fix it: Click on the indicator. A menu will pop up, giving you options to Edit Locations. This typically happens because of a typo (e.g., "Tennesssee" instead of "Tennessee") or an ambiguous name (Tableau doesn't know which "Hamilton" you mean without knowing the country or state). In the Edit Locations menu, you can match your unrecognized values to Tableau's known locations and fix the issue.

Data is Too Scattered or Too Vague

If your geographic data is very specific (like street addresses) but you haven't provided latitude and longitude coordinates, Tableau won’t be able to plot the map. It knows countries, states, and major cities, but its built-in geocoding doesn't go down to the address level. In this case, you'll need to add latitude/longitude columns to your data source.

Final Thoughts

Tableau makes it remarkably simple to get started with geospatial analysis, turning rows of data into rich, intuitive maps. By correctly preparing your data and choosing the right map type - whether it's a filled map for state-level data or a symbol map for specific points - you can uncover regional insights that will drive better business decisions.

For teams drowning in data across a dozen platforms, the learning curve and manual setup process for tools like Tableau can feel like a major roadblock. At Graphed, we remove that friction entirely. You can connect your marketing and sales data sources like Google Analytics, Shopify, and Salesforce in seconds. Instead of navigating menus and dragging fields, you just describe what you want to see - "Show me a map of USA sales by state for last quarter" - and our AI data analyst builds the dashboard for you in real time.