How to Append Tables in Power BI

Combining data from different sources is a daily reality for anyone working in business intelligence. You might have monthly sales data in separate tables or marketing performance reports from different platforms. To get the full picture, you need to bring that scattered information together. This is where appending tables in Power BI becomes your go-to move. This article will walk you through exactly how to append tables in Power BI, why you'd want to, and how to deal with the common issues that pop up along the way.

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So, What Exactly Is Appending in Power BI?

Appending is the process of stacking data from two or more tables to create one single, large table. Think of it like taking a stack of pages from one report and placing it directly on top of a stack of pages from another report. You end up with one big report that contains all the pages. In data terms, you are adding rows from one table to the end of another.

The key requirement for a clean append operation is that the tables should share a similar structure. This means the column headers should be the same, or at least very similar. For example, if you have sales data for each month of the first quarter in three separate tables (January_Sales, February_Sales, March_Sales), you can append them to create a single 'Q1_Sales' table.

January_Sales Table:

• Order ID, Product, Amount
• 101, Widget A, $50
• 102, Widget B, $75

February_Sales Table:

• Order ID, Product, Amount
• 103, Widget C, $100
• 104, Widget A, $50

After appending you get:

Q1_Sales Table:

• Order ID, Product, Amount
• 101, Widget A, $50
• 102, Widget B, $75
• 103, Widget C, $100
• 104, Widget A, $50

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Append vs. Merge: What's the Difference?

People often confuse appending with merging. While appending stacks data vertically (adding rows), merging stitches data together horizontally (adding columns). A merge is similar to doing a VLOOKUP in Excel, where you pull in new columns from another table based on a matching key or identifier.

• Append: Use when you have tables with the same columns but different rows of data (e.g., combining monthly reports).
• Merge: Use when you have tables with different information about the same items, and you want to combine it based on a common column (e.g., adding product details to a sales table using a 'SKU' column).

Step-by-Step Guide: How to Append Tables in Power BI

The magic of appending happens inside Power BI's powerful Power Query Editor. This is where you'll shape and transform your data before it even hits your report dashboard.

Step 1: Open the Power Query Editor

First, you need to get into the Power Query Editor. From the main Power BI Desktop window, go to the Home tab on the ribbon and click the Transform data button. This will launch a new window for the Power Query Editor, which is your workshop for all data wrangling.

Step 2: Locate the Append Queries Function

Once you're in the Power Query Editor, make sure you're on the Home tab. In the "Combine" group of the ribbon, you'll see a button labeled Append Queries. This is where you'll start the process.

Step 3: Choose Your Append Method

When you click the dropdown arrow on the 'Append Queries' button, you get two choices:

• Append Queries: This option takes a second table and appends its rows to the table you currently have selected. It modifies your original query.
• Append Queries as New: This option combines two or more tables into a brand new query, leaving your original source tables untouched.

As a best practice, you should almost always choose Append Queries as New. This preserves your original data tables should you need to reference them later, and it makes your data transformation steps easier to troubleshoot. Let's proceed with this option.

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Step 4: Select the Tables to Append

After clicking 'Append Queries as New', a dialog box will appear. Here you decide which tables you want to stack together.

For Two Tables:

The default view is for combining two tables.

1. Keep the 'Two tables' radio button selected.
2. Select your first table from the 'Primary table' dropdown.
3. Select the table you want to append from the 'Table to append to the primary table' dropdown.
4. Click OK.

For Three or More Tables:

If you need to combine more than two tables (like our monthly sales data), it's just as simple.

1. Select the 'Three or more tables' radio button.
2. A list of 'Available tables' will appear on the left.
3. Select the tables you want to append one by one and click the Add >> button to move them to the 'Tables to append' list on the right.
4. Review your list on the right and click OK.

Step 5: Review and Rename Your New Table

Power Query will instantly create a new table, likely with a default name like Append1. You'll see that the row count is the sum of the rows from the tables you selected. Your first action should be to give this new query a meaningful name in the Query Settings pane on the right. Let's call it "Q1_Sales."

Step 6: Handle Mismatched Columns (Crucially Important!)

This is where things can get a little messy if your initial tables weren't identical. Power Query appends data based on the column headers.

• If the column names match exactly, the data will stack perfectly.
• If a column name from one table doesn't exist in the other, Power Query will create a new column in the appended table. The rows from the table that didn't have that column will simply show null values.

For example, if one table had a column named 'Region' and another had 'Territory', your final table would have both a 'Region' column and a 'Territory' column, each filled with nulls for half the data. Not ideal!

The fix is simple but vital: ensure your column names are consistent before you append. The easiest way to do this is to go back to the original source queries (before the append step) and rename the columns to be identical. Just double-click a column header in Power Query and type the new name.

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Step 7: Close & Apply

Once you're happy with your appended table, click the Close & Apply button in the top-left corner of the Power Query Editor. This will load your new, unified table into your Power BI data model, ready for you to build visualizations.

Pro Tip: Disable Load for Original Tables

Since you now have a comprehensive table (e.g., "Q1_Sales"), you probably don't need the individual source tables (January_Sales, February_Sales, etc.) in your final Power BI report. Loading them just uses unnecessary memory and can slow down your report. To fix this, right-click on each source query in Power Query and uncheck Enable load. They will still be available for refresh in Power Query, but won't be loaded into your main data model.

Common Scenarios for Appending Data

Appending might seem straightforward, but its applications are incredibly broad. Here are a few places where you'll find it indispensable.

• Consolidating Periodic Data: The most classic example. Combining daily, weekly, or monthly reports (sales, web traffic, performance metrics) into a quarterly or annual dataset.
• Unifying Data from Different Platforms: Imagine you have ad performance exports from Facebook Ads and Google Ads. While the column names might differ slightly (e.g., 'Cost' vs. 'Spend', 'Impressions' vs. 'Impr.'), you can rename them to match in Power Query and then append them to create a single 'All_Ad_Performance' table.
• Joining Archived Data with Current Data: Often, historical data is stored in separate files or database tables. You can easily append your archived data with your current active data to do a complete longitudinal analysis.
• Collating Data from Multiple Regions or Departments: If your company has different branches, you can append sales data from North, South, East, and West to get a comprehensive view of company-wide performance.

Final Thoughts

Appending queries is a fundamental skill in Power BI that allows you to take scattered, segmented data and consolidate it into a single source of truth for your dashboards and reports. By using the 'Append Queries as New' function in the Power Query Editor, you can easily stack related tables on top of one another, clearing the way for powerful, holistic analysis.

While Power BI's append feature is fantastic for combining datasets you've already managed to import, we know the real bottleneck is often just getting that data into one place to begin with. We built Graphed to streamline that entire process, automatically connecting to dozens of marketing and sales sources like Google Analytics, Shopify, Salesforce, and Facebook Ads. Instead of manually exporting files, cleaning them, and then appending, you can just ask a question like, "Show a combined chart of my total ad spend vs. revenue across all platforms for this quarter," and we instantly build the unified report for you, keeping it updated in real-time.