How to Append Queries in Power BI

Combining data from different tables or files is a fundamental task in any analysis, and Power BI offers powerful ways to do it without writing a single line of code. Appending queries is like stacking datasets on top of each other to create one master table. This guide will walk you through exactly how to append queries in Power BI, explaining when to use it and how to avoid common mistakes along the way.

What Exactly Is Appending Queries?

Appending is the process of taking two or more tables and adding the rows from one table to the bottom of another. Think of it like a deck of cards. If you have a stack of red cards (Table 1) and a stack of black cards (Table 2), appending them means placing the black cards underneath the red cards to create one single, taller deck. The number of rows increases, but the number of columns stays the same (assuming the tables have a similar structure).

This is extremely useful when your data is split across multiple files or tabs but shares the same format. A perfect example is monthly sales data. You might get a separate CSV file for January, another for February, and one for March. Instead of analyzing them separately, you can append them to create a single table with all first-quarter sales.

Append vs. Merge: What's the Difference?

It's easy to get append and merge mixed up, but they serve very different purposes. Always remember:

• Append = Stacking (More Rows): You add rows from one table to another. The resulting table is taller.
• Merge = Joining (More Columns): You add columns from one table to another based on a common matching column (like a customer ID or order number). The resulting table is wider.

If you have Q1 sales data and Q2 sales data, you would append them to get a table for the first half of the year. If you have a sales data table and a separate customer details table, you would merge them to add customer information (like name and address) to each sale.

Preparing Your Files for Appending

For the append operation to work smoothly, your queries need to have a consistent structure. This doesn't mean they have to be identical, but the closer they are, the less cleanup you'll have to do. The most important rule is that the column headers must match.

Power BI matches columns based on their header names, not their position. For example, if Table A's first column is "Sale Date" and Table B's first column is "Order Date," Power BI will see them as two separate columns in the final appended table. One will be filled with data from Table A and nulls from Table B, and the other will have the reverse.

Before appending, a quick check of your column headers can save you a lot of headaches:

• Consistency is Key: Ensure a column named "Revenue" in one table is also named "Revenue" in all others, not "Rev" or "Sales."
• Mind the Case: Power Query is case-sensitive by default. "Product ID" is different from "Product Id." Make sure the capitalization is identical across all tables.
• Check Data Types: It's also good practice for matching columns to have the same data type (e.g., both "Revenue" columns are set as Decimal Number). Power BI is smart about this, but consistent formatting makes for cleaner results.

A Step-by-Step Guide to Appending Queries in Power Query

All append operations happen in the Power Query Editor, Power BI's data transformation engine. Let's walk through the process using a common scenario: combining regional sales data from North America, Europe, and Asia into a single global sales report.

Step 1: Get Your Data into Power BI

First, you need to load your tables into Power BI. Each file or table will become a separate query.

1. Navigate to the Home tab in Power BI Desktop and click Get Data.
2. Select your source (e.g., Excel workbook, CSV, etc.) and connect to an individual data file (e.g., "NA_Sales.csv").
3. A navigator preview will appear. Click Transform Data to open the Power Query Editor. Do not click Load yet.
4. Once in the Power Query Editor, repeat the process. Click New Source in the Home tab of the Power Query ribbon, select your next file ("EU_Sales.csv"), and bring it in. Repeat for all your files ("Asia_Sales.csv").

Now, you should see three separate queries listed in the Queries pane on the left: NA_Sales, EU_Sales, and Asia_Sales.

Step 2: Choose Your Append Method

You have two ways to append data, each useful in different situations. You can find them under the Home tab in the "Combine" section of the Power Query ribbon.

Let's make sure you've selected one of the queries (e.g., NA_Sales) to make the option available.

• Append Queries: This is an "inline" operation. It adds the rows from another query directly into the currently selected query. In our example, if we have the NA_Sales query selected and use this option to append EU_Sales, the NA_Sales query itself will be modified to include the European data. This is good for simple transformations where you don't need to keep the original tables separate in your final data model.
• Append Queries as New: This creates an entirely new query that contains the combined data from the appended tables. Your original queries (NA_Sales, EU_Sales, etc.) remain untouched. This is the recommended best practice because it preserves the original tables, which can be useful for debugging and keeping your data transformation steps clean and organized.

For our example, we'll use Append Queries as New to create a fresh Global_Sales table.

Step 3: Appending Your Data

After clicking Append Queries as New, a dialog box will pop up. Your choice here depends on how many tables you're combining.

Appending Two Tables

If you're only combining two tables, the default view is what you'll use. It's straightforward:

1. Select the "Two tables" radio button.
2. Use the first dropdown menu to select your primary table (e.g., NA_Sales).
3. Use the second dropdown to select the table you want to append to it (e.g., EU_Sales).
4. Click OK.

Appending Three or More Tables

Since we have three regional sales tables, we need to use the second option.

1. Select the radio button for Three or more tables.
2. You'll see two boxes. The left box, "Available tables," lists all the queries in your model. The right box, "Tables to append," is where you will move the queries you want to combine.
3. Select NA_Sales from the left box and click Add >.
4. Do the same for EU_Sales and Asia_Sales. The order in which you add them determines the order of the rows in the final table, though this rarely matters for analysis.
5. Once all the tables you want to append are in the right-hand box, click OK.

Step 4: Check and Clean Your New Table

Power Query will execute the steps and create a new query, likely named "Append1" by default. The first thing you should do is rename it to something descriptive, like "Global_Sales."

Now, carefully inspect the appended table:

• Scroll Horizontally: Check for extra columns. If you had mismatched header names (e.g., "Region" and "Territory"), you'll now see both columns, with lots of null values. If this happens, you can go back to the original queries, rename the columns to match, and the change will automatically flow through to your appended table.
• Check Column Profiles: In the View tab, turn on the "Column quality" and "Column distribution" features. This gives you a quick snapshot of empty or erroring values in each column, helping you spot issues from the append.
• Confirm Row Count: For a quick sanity check, make sure the new table's row count matches the sum of the rows from your original tables.

Once you are happy with the combined data, click Close & Apply in the top-left corner to load your new, shiny Global_Sales table into the Power BI data model for visualization.

Pro Tips and Common Pitfalls to Avoid

Appending is usually straightforward, but a few subtle issues can trip you up. Here's how to handle them.

Handling Mismatched Column Headers

As mentioned, this is the #1 problem. If NA_Sales has a column named "Revenue" but EU_Sales has "Sales_Amount," your final table will have two separate columns. The fix is simple: Before the append step, go into the EU_Sales query and rename the "Sales_Amount" column to "Revenue." The changes will propagate, and your append result will be correctly combined into one column.

Maintaining Data Origin

After appending everything, how do you know which row came from which region? The source information is often lost. To prevent this, you can add a custom source column to each table before appending it.

1. Select the NA_Sales query.
2. Go to the Add Column tab and click Custom Column.
3. Name the new column "Region."
4. In the formula box, simply type in the region name in quotes: "North America".
5. Click OK.

Repeat this for the EU_Sales (adding a "Region" column with the value "Europe") and Asia_Sales (value "Asia") queries. Now, when you append them, the "Region" column will neatly identify the source of every single row, becoming an incredibly useful dimension for your reports and slicers.

Disabling the Load of Original Tables

Since we used "Append Queries as New," we now have our master table (Global_Sales) and the original component tables (NA_Sales, EU_Sales, Asia_Sales). You likely don't need to load the original tables into your Power BI data model, as they just take up memory. You still need them in Power Query, but you can prevent them from loading to the final model.

In the Power Query Editor's Queries pane, right-click on NA_Sales and uncheck Enable load. You'll see the query name become italicized. Do this for EU_Sales and Asia_Sales, too. Now, only your clean, appended Global_Sales table will be available for creating visuals once you click Close & Apply.

Final Thoughts

Appending queries in Power BI is a core data preparation skill that moves you beyond single-source reports. It allows you to transform fragmented data — like monthly reports, regional results, or exports from different campaigns — into a single, consolidated source of truth for clear and comprehensive analysis.

For many teams, the real bottleneck isn't the transformation but the repetitive, manual work of just connecting and pulling data from all the different platforms in the first place. With Graphed, we’ve built a solution to that exact headache. Instead of logging into a dozen apps and repeating steps in Power Query, you can connect your sources once, then just ask in plain English: "Combine my revenue from Shopify and sessions from Google Analytics into one dashboard." We handle a lot of this data stitching automatically, creating live dashboards so you can jump straight to insight without the setup struggle.