How to Join Two Excel Files in Tableau

Bringing two separate Excel files together in Tableau feels like it should be simple, but it can quickly become confusing with talk of joins, relationships, and data types. This guide cuts through the noise and gives you a clear, step-by-step process for combining your Excel data. We'll walk through how to connect your files, choose the right type of join, and troubleshoot common issues along the way.

Before You Begin: Prepare Your Excel Files for Success

A few minutes of prep work in Excel can save you a ton of headaches in Tableau. Before you even open Tableau, take a look at your spreadsheets. A successful join depends on clean, organized data, especially the column you plan to use to connect the two files.

1. Standardize Your "Join Key" Column

To join two files, Tableau needs a common reference point - a column that exists in both spreadsheets. This is often called a primary key or a join key. This could be an "Order ID," "Customer ID," "Email Address," or any piece of data that uniquely identifies a row and is present in both your files.

• Consistent Naming: For Tableau to automatically recognize the connection, it’s best if this key column has the exact same name in both Excel files (e.g., "Order ID" in File A and "Order ID" in File B). If they're named differently (e.g., "Order Number" and "OrderID"), that's okay - you can manually tell Tableau which columns to join on later.
• Consistent Data Formatting: This is a big one. Check that the data within your key column is formatted identically. "TX-1001" is not the same as "1001". If one file stores an ID as a number and the other stores it as text, the join will fail. Pick one format (text is usually safest for IDs) and apply it to both columns in Excel.

2. Clean Your Messy Data

Dirty data leads to messy visualizations. Look out for these common issues:

• Extra Spaces: Use Excel's TRIM function to remove leading or trailing spaces from your join key column. A space at the end of "jane.doe@email.com" will prevent it from matching with "jane.doe@email.com".
• Mixed Data Types: Ensure columns you plan to use for calculations are consistently numeric, and dates are formatted as dates across both files. If a "Sales" column has a few cells with "N/A" text in them, Tableau will read the entire column as text, preventing you from doing any math on it.
• Clear Headers: Make sure row 1 in each sheet contains clear, simple headers. Avoid merged cells or extra title text above your headers.

Connecting and Joining Two Excel Files in Tableau: A Step-by-Step Guide

Once your Excel files are prepped, it's time to bring them into Tableau. Follow these steps carefully to build your combined data source.

Step 1: Connect to Your First Excel File

When you open Tableau Desktop, you'll see a "Connect" pane on the left.

1. Under "To a File," select Microsoft Excel.
2. Navigate to your first Excel file and click Open.
3. You’ll now be on the Data Source page. You'll see the sheets from your workbook listed on the left. Drag the sheet you want to use onto the canvas area that says, "Drag tables here."

You should now see a preview of your data from the first Excel sheet.

Step 2: Add the Second Excel File

This is the magic step for bringing in the second file. Look at the "Connections" area in the top-left of the Data Source page.

1. Click the Add button (it looks like a cylinder with a plus sign).
2. Again, select Microsoft Excel and choose your second file.

You will now see the sheets from both Excel workbooks listed in the left pane. You've successfully added both files to the same Tableau data source.

Step 3: Create the Join

Now it's time to connect the data from your two files.

1. Drag the relevant sheet from your second Excel workbook onto the canvas, next to the first one.
2. Tableau is pretty smart. If your join key columns have the same name, it will likely create an automatic join for you, represented by a line (often called a "noodle") connecting the two tables and a Venn diagram icon.
3. Click on the Venn diagram icon (the join operator). This opens the Join configuration window where you can fine-tune the connection.
4. In this window, verify that Tableau has correctly identified the join key column from each file. If it guessed wrong or if your column names were different, you can select the correct columns from the dropdown menus under "Data Source."

Choosing the Right Join Type

In the Join configuration window, you’ll see four circles: Inner, Left, Right, and Full Outer. The one you choose determines which records are included in your final dataset. This is the most important decision you'll make in this process.

Let's use a common example:

• File 1 (Left Table): A Sales sheet with columns like OrderID, Product, and Amount.
• File 2 (Right Table): A Customer sheet with columns like OrderID, CustomerName, and Region.

Our join key is OrderID.

Inner Join

An Inner Join only returns rows where the OrderID exists in both the Sales table and the Customer table. If an order in your sales file doesn't have a matching customer entry, it will be excluded. If a customer exists but hasn't made an order, they'll be excluded, too.

Use this when: You only want to analyze the clean, complete data that has a match in both files.

Left Join

A Left Join returns all the rows from the left table (Sales) and only the matching rows from the right table (Customer). If an OrderID from the Sales table has no match in the Customer table, it will still appear in your data, but the columns from the customer table (CustomerName, Region) will be null (empty).

Use this when: You want to see every sale, regardless of whether you have complete customer information for it. This is one of the most common join types.

Right Join

A Right Join is the opposite. It returns all the rows from the right table (Customer) and only the matching rows from the left table (Sales). If a customer hasn't yet made a purchase recorded in the Sales file, they will still appear, but the columns from the sales table (Product, Amount) will be null.

Use this when: You need a complete list of all your customers and want to see which ones have or haven't made a purchase.

Full Outer Join

A Full Outer Join returns every row from both tables. If there's a match, the data is combined. If a sales record has no matching customer, it will be included. If a customer has no matching sales record, they will be included too. Nulls will appear wherever data is missing from one side.

Use this when: You need to see a complete inventory of everything from both files in one place, even the unmatched records.

Common Problems & Troubleshooting Tips

Even with careful prep, you might run into a few snags. Here’s how to fix the most common issues.

• Data Duplication: If you join a file where your key appears once (e.g., a list of customers) to a file where it can appear multiple times (e.g., a list of orders), you may see data from the first file repeated. This is normal behavior! Customer A will be listed for every single order they placed. It's not an error, but something to be aware of when you are calculating totals or counts.
• Poor Performance: Joining live Excel files can be slow, especially if they are large. After setting up your join, go to the upper-right corner of the Data Source page and switch your connection from "Live" to "Extract." This creates a hyper-optimized .hyper file that stores the data locally, making your dashboard interactions much faster.
• Mismatched Data Types Error: If Tableau gives you an error about data types, it means your join key is formatted as a number in one file and text in the other. You can fix this directly in Tableau. In the grid view on the Data Source page, click the icon at the top of the column (e.g., # for numbers, Abc for text) and change the data type to match the other file.

Final Thoughts

Joining two Excel files is a fundamental skill in Tableau that opens up a new world of analysis. By carefully preparing your files, connecting them methodically on the Data Source page, and selecting the correct join type, you can create a single, unified dataset that tells a much richer story than either file could alone.

Creating these kinds of multi-source views is exactly why we built Graphed. Instead of manually navigating connection settings and join clauses, you can simply connect your data sources - like Google Sheets, Excel, or analytics platforms - and then use plain English to describe the report you need. We handle the complexity of joining and visualizing the data in the background, allowing you to ask questions like, "Show me my sales revenue by customer region from my sales and customer files," and get a live, interactive dashboard in seconds.