How to Connect Multiple Excel Sheets in Tableau

Chances are, your business data isn't living neatly in one single spreadsheet. In this tutorial, you'll learn exactly how to connect and combine multiple Excel sheets in Tableau, turning scattered numbers into a unified, actionable report. We'll walk through the best methods - Relationships, Joins, and Unions - so you can stop manually copying and pasting and finally get a complete view of your data.

First Things First: Why Combine Data in Tableau?

You might be tempted to do all your data prep directly in Excel, painstakingly merging sheets before you even open Tableau. While it seems straightforward, this approach is often time-consuming and prone to errors. Combining data directly within Tableau offers several key advantages:

• It's Repeatable and Dynamic: Once you set up the connection, you can simply refresh your data source in Tableau when your Excel files are updated. You won't have to repeat the manual merge process every week or month.
• It Maintains Data Integrity: Working with the original, separate sheets means you aren't altering your source data. This reduces the risk of copy-paste errors or accidentally deleting important information.
• It's More Powerful: Tableau’s data connection tools are built for complex data blending scenarios. Tools like Relationships and Joins give you much more flexibility than VLOOKUPs or manual consolidation in a spreadsheet.

Prep Your Excel Sheets for a Smooth Connection

Before you jump into Tableau, a little preparation goes a long way. Spending five minutes cleaning up your Excel files can save you an hour of troubleshooting later. Here are a few best practices:

• Use Clean Headers: Ensure the first row of each sheet contains clear, unique column headers. Avoid starting your data on row 2 or having titles above the header row.
• Remove Merged Cells: Merged cells are a visual formatting tool in Excel but can confuse Tableau’s data interpreter. Unmerge any cells within your data tables.
• Format Data as a Table: In Excel, select your data range and click Format as Table. This gives your data a defined structure that Tableau recognizes easily, and it automatically handles a consistent format for new rows you add later.
• Check Data Types: Make sure a column you plan to connect on (like "Customer ID" or "Date") is formatted consistently across all sheets. A "Customer ID" column formatted as a number in one sheet and text in another will cause connection problems.

Understanding Your Options: Relationships, Joins, and Unions

Tableau offers three primary ways to combine data from different sheets or files. Knowing which one to use depends on the structure of your data and what you want to achieve.

1. Relationships (The Recommended Method)

Relationships are Tableau’s newer, smarter, and more flexible way to combine tables. Think of them as a contract between two tables, not a permanent merge. You tell Tableau how two tables are related (e.g., the "Orders" sheet links to the "Customers" sheet via a "Customer ID" field), and Tableau only brings in data from the related table when it's needed for a specific visualization.

When to use Relationships: This should be your default choice. Use it when you have data in different tables with different levels of detail (e.g., a "Customers" table with one row per customer and an "Orders" table with multiple rows per customer).

Why they're great: They prevent data duplication and maintain the correct level of detail for each table, leading to more accurate aggregations like counts and averages. They are also much more performant with large datasets.

2. Joins (The classic, physical merge)

Joins create a new, fixed table by combining columns from two or more tables based on a shared field (a "key"). Unlike Relationships, a join physically merges the data into a single, wider table before any analysis begins. This can be powerful but also less flexible.

There are four main types of joins:

• Inner Join: Only returns rows where the key field exists in both tables. For example, if you join "Sales" and "Customer Info" on "Customer ID," you’ll only see sales data for customers who also appear in your customer info list.
• Left Join: Returns all rows from the left table and any matching rows from the right table. If a row from the left table has no match in the right table, the columns from the right table will show as NULL. This is useful for seeing all sales, even those without customer details.
• Right Join: The opposite of a left join. It returns all rows from the right table and any matching rows from the left table.
• Full Outer Join: Returns all rows from both tables. If there's no match for a row, the missing parts will be filled with NULL values. This helps you see every record from every table, matched up where possible.

When to use Joins: Use them when you are absolutely sure you need a single, wide, and flattened table for your analysis. This is sometimes necessary, but Relationships handle most use cases better.

3. Unions (For stacking similar data)

A union stacks rows of data on top of each other. Instead of adding more columns (like a join), a union adds more rows. This is incredibly useful when your data is split across multiple sheets or files but has the exact same column structure.

When to use Unions: The classic example is combining monthly data. If you have "January Sales," "February Sales," and "March Sales" in separate sheets, you can use a union to append them into a single "Q1 Sales" table.

Step-by-Step Guide: Connecting Your Excel Sheets in Tableau

Let's walk through a common business scenario. Imagine you have an Excel workbook with three tabs:

• Orders: Contains transaction data like Order ID, Order Date, Customer ID, and Amount.
• Customer Details: A list of customers with Customer ID, Customer Name, and Region.
• Returns: A list of returned orders with Order ID and Return Reason.

Our goal is to analyze sales by customer region and see which regions have the highest return rates.

Step 1: Connect to Your Excel File

1. Open Tableau Desktop.
2. Under the Connect pane on the left, click on Microsoft Excel.
3. Navigate to your saved Excel file and click Open.

Tableau will now show you the Data Source page, with a list of available sheets from your workbook in the left sidebar.

Step 2: Create a Relationship between Orders and Customer Details

Relationships are the default and easiest way to start.

1. Drag the Orders sheet into the canvas area that says "Drag tables here." This becomes your primary table.
2. Next, drag the Customer Details sheet onto the canvas. Tableau will automatically detect the common field, Customer ID, and create a “noodle” connecting the two tables.
3. Click the noodle to review the relationship details. Tableau is usually very good at identifying the correct fields automatically, but you can edit them here if needed.

You’ve just created a relationship! You now have a logical model where data from both sheets is connected but not yet physically merged.

Step 3: Join the Returns Data

Now we want to add the returns data. Returns are directly related to specific orders, so a join makes sense here to create a single table that shows every order and whether it was returned.

1. In the canvas, double-click on the Orders table box. This opens the "physical layer" where you can create joins. The view will now just show the "Orders" table.
2. Now, drag the Returns sheet onto the physical canvas. The Join configuration Venn diagram will appear.
3. By default, Tableau might guess an Inner Join. An Inner Join would only show you orders that were returned. We want to see all orders and identify which ones were returned.
4. Click the Venn diagram icon and select Left. Set the joining field to Order ID = Order ID.

Now you have a physically joined table of orders and associated returns. Close the physical layer by clicking the "X" in the top corner of the physical view. You'll return to the main canvas showing your [Orders + Returns] logical table connected to your Customer Details table.

Step 4: Combining Monthly Performance with a Union

Let's imagine a different scenario. Suppose you have separate files for each month's sales: Sales_Jan.xlsx, Sales_Feb.xlsx, Sales_Mar.xlsx. They all have the same columns.

1. Connect to your first Excel file, Sales_Jan.xlsx.
2. Drag the sheet containing the sales data to the canvas.
3. In the left sidebar, don't drag another sheet. Instead, click the New Union button.
4. A dialog box will open. You can manually drag the other sales sheets into this box. But there's a better way: click the Wildcard option.
5. Set it to search in the folder your files are in and use a pattern like Sales_*.xlsx to automatically grab all files that start with "Sales_" and union them.
6. Click OK. Tableau will append all the files into a single, tall table, even adding a handy File Path column so you can see which file each row came from.

Common Problems and How to Fix Them

Even with good prep, things can sometimes go sideways. Here are a couple of common issues:

• Issue: My join created a ton of NULLs! Cause: This usually happens with a Left or Right join where many keys in one table don't have a match in the other. It could also mean the connecting keys have different data types (e.g., number and text). Fix: Double-check that your joining field (Customer ID, etc.) is formatted identically across all sheets in Excel. In Tableau's Data Source page, check the data type icon (e.g., #, Abc) above each column name and ensure they match.
• Issue: The numbers in my charts seem wrong after joining. Cause: Joins can sometimes duplicate data. If one customer has five orders, joining the "Customers" table to the "Orders" table at the customer level might inflate metrics associated with the customer. Fix: This is a perfect reason to use Relationships instead of joins. Relationships keep the tables separate and analyze each at its own native level of detail, preventing this kind of unintended data duplication. Undo your join and try creating a relationship instead.

Final Thoughts

Combining data from multiple Excel sheets is a fundamental skill for building insightful dashboards in Tableau. By understanding how to use Relationships for flexibility, Joins for specific merges, and Unions for stacking similar data, you can build a comprehensive view of your business performance without the headache of manual spreadsheet wrangling.

We built Graphed because we believe getting answers from your data shouldn't be so difficult. Instead of learning the intricacies of joins and data models, our platform allows you to connect all your sources like Google Analytics, Shopify, and even spreadsheets, and then just ask questions in plain English. We turn hours of complex data prep into a quick conversation, so you can build real-time "cockpit" dashboards for your business in seconds, not days, and free up your time to focus on growth.