How Do You Consolidate Inquiries in Power BI?

Bringing all your data together in one place is the first step to unlocking powerful insights, but having it scattered across different tables or files can feel like trying to assemble a puzzle with pieces from different boxes. In Power BI, consolidating your queries is the answer. This article will show you exactly how to combine different data sources into a single, clean, and analysis-ready table using the core functions of Power Query.

Why Consolidate Queries in the First Place?

Before jumping into the "how," let's quickly cover the "why." Consolidating your data isn't just a tidying-up exercise, it's a strategic move that fundamentally improves your reports. When you bring your data together, you achieve several key benefits:

• A Single Source of Truth: Instead of building visuals from five different sales tables (one for each region, for example), you can create one master table. This reduces errors, ensures consistency, and makes your data model simpler to manage.
• Comprehensive Analysis: True insights often come from connecting the dots between different datasets. By consolidating, you can analyze things you couldn't before. For instance, you could merge your marketing campaign data with your sales data to calculate an accurate return on ad spend (ROAS) for each campaign.
• Improved Report Performance: A lean, well-structured data model with fewer tables generally performs better than a complex model with numerous relationships. Consolidating queries can reduce the complexity, leading to faster-loading reports and visuals.
• Simplified DAX Calculations: Writing DAX measures becomes much more straightforward when all your relevant data is in one table. You won't have to write complex formulas to navigate multiple relationships just to complete a simple sum.

The Two Main Ways to Combine Data: Append vs. Merge

Power BI's Power Query Editor gives you two primary methods for consolidating data: Append and Merge. Understanding the difference between them is crucial because they solve different types of problems.

Append Queries: Stacking Data

Think of Append as stacking tables on top of one another. When you append queries, you are adding the rows from one table to the end of another. The key requirement is that the tables should have similar, if not identical, column structures.

Use Append when:

• You have monthly or quarterly sales data in separate files (e.g., Sales_January.csv, Sales_February.csv).
• You want to combine transaction data from different stores or regions, where each has its own file but uses the same columns (Date, Product ID, Quantity, Revenue).
• You're combining logs or event data from different periods into one master log.

The result of an append operation is a single table with the same number of columns but more rows - the sum of the rows from the original tables.

Merge Queries: Joining Data Side-by-Side

Think of Merge as adding new columns to a table by looking up information from another table. It's similar to a VLOOKUP in Excel but far more powerful. To merge two tables, you need at least one common column (often called a key) to link them, like a ProductID or CustomerID.

Use Merge when:

• You have a Sales table with a ProductID but need to add product information like Product Name, Category, and Price from a separate Products table.
• You have a list of Orders with a CustomerID and you want to pull in customer details like Name, City, and Segment from your Customers table.
• You're enriching your website traffic data with details from your CRM to see which leads came from specific marketing channels.

The result of a merge operation is one wider table that contains columns from both of the original tables.

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

Let's walk through a common scenario: you have sales data for three different months in three separate tables (Jan_Sales, Feb_Sales, Mar_Sales) and you want to combine them into one comprehensive Q1_Sales table.

1. Open the Power Query Editor: From the main Power BI Desktop window, click on the Transform data button in the Home ribbon. This will launch the Power Query Editor where all the data shaping magic happens. Your three tables should be visible in the Queries pane on the left.
2. Locate Append Queries: In the Power Query Editor, go to the Home tab. In the "Combine" section, you'll see a button for Append Queries. Click the small dropdown arrow on this button.
3. Choose "Append Queries as New": You have two options: "Append Queries" (which adds rows to your currently selected table) and "Append Queries as New" (which creates a brand-new, combined query). It's almost always better to choose Append Queries as New. This leaves your original source tables untouched, making it much easier to troubleshoot if something goes wrong.
4. Select the Tables to Append: A dialog box will appear. Since you have more than two tables, select the Three or more tables option. You can now select Jan_Sales, Feb_Sales, and Mar_Sales from the "Available tables" list and click Add >> to move them to the "Tables to append" list.
5. Confirm and Review: Click OK. A new query will be created, probably named something like Append1. You can right-click this query and rename it to something descriptive, like Q1 Sales. Now, look at the data. Power Query matches the columns by name. If the column names were consistent across all three files, your data should look perfectly stacked. Check the total number of rows to make sure it equals the sum of rows from the original tables.

Pro Tip: For appending to work perfectly, your column names must match exactly. product_id is different from ProductID. If column names are inconsistent, Power Query will create separate columns for each, leaving you with lots of null values. Rename columns to be consistent across all tables before you append them.

Step-by-Step Guide: How to Merge Queries in Power BI

Now for a merging scenario. Let's say you have a table with your sales data (Sales_Data) that includes a ProductID. You also have a separate product lookup table (Product_Lookup) that lists every ProductID along with its ProductName and Category. You want to bring the product name and category into your main sales table.

1. Open the Power Query Editor: Just as before, click Transform data to open the Power Query Editor. Make sure both your Sales_Data and Product_Lookup queries are loaded.
2. Locate Merge Queries: Select your Sales_Data query (this is considered the primary or "left" table). On the Home tab, click the dropdown next to Merge Queries. Once again, select Merge Queries as New to create a new, combined query without modifying your originals.
3. Configure the Merge Operation: The Merge dialog box will open.
4. Choose the Join Kind: The "Join Kind" dropdown determines how the tables are merged. The default, Left Outer, is the most common. It means: "Keep all rows from the first table (Sales_Data), and bring in any matching information from the second table (Product_Lookup)." This is exactly what we want.
5. Expand the New Column: Click OK. You'll see your new, merged query. At the far right, there will be a new column named after the lookup table (Product_Lookup) with [Table] in each cell. This column holds all the data from the lookup table that matched each row. To see the data, click the expand icon (two arrows pointing in opposite directions) in the column header.
6. Select the Columns to Add: A dropdown list of all the columns from your Product_Lookup table will appear. You don't need to bring in ProductID again, as you already have it. Deselect ProductID and check the boxes for ProductName and Category. It's also a good idea to uncheck "Use original column name as prefix" to keep your column names clean (e.g., Category instead of Product_Lookup.Category). Click OK.

You did it! Your new table now contains two new columns, ProductName and Category, with the information pulled correctly from your lookup table for every sale.

Best Practices for Consolidating Data

To avoid headaches down the line, keep these tips in mind when consolidating your queries:

• Disable Load for Source Queries: After you create your new consolidated query (e.g., Q1 Sales), you no longer need the original, separate queries (Jan_Sales, Feb_Sales, etc.) to be loaded into your Power BI report model. In the Queries pane, right-click on each source query and uncheck Enable load. The data is still available in Power Query for refresh, but it won't clutter up your data model.
• Be Mindful of Data Types: Ensure that corresponding columns have the same data type before you combine them. Combining a text column with a number column can lead to errors.
• Start with Clean Data: "Garbage in, garbage out" applies here. Remove duplicate rows, filter out unnecessary data, and handle errors in your source queries before you append or merge them. This keeps your consolidation steps clean and easy to follow.
• Rename Your Steps: The "Applied Steps" pane on the right tracks everything you do. Double-click on a step to rename it to something more descriptive (e.g., "Merged with Product Details" instead of just "Merged Queries"). This makes your workflow much easier for others (or your future self) to understand.

Final Thoughts

Consolidating data is a fundamental skill in Power BI that elevates your reports from simple charts to a dynamic and interconnected analytical tool. By mastering Append for stacking data with the same structure and Merge for enriching your data with new columns, you can create a clean, centralized, and powerful data model ready for deep analysis.

While Power Query is essential for this kind of detailed data shaping inside Power BI, sometimes the task is consolidating data from entirely different platforms before it even gets there. Stitching together data from Google Analytics, Facebook Ads, Shopify, and Salesforce can feel like a full-time job. At Graphed, we automate that process entirely. We have one-click integrations to connect your marketing and sales sources, creating a unified view of your performance instantly. This allows you to simply ask questions in plain English, like "Show me a dashboard comparing my ad spend vs. revenue by campaign," and get a live, interactive dashboard built for you in seconds.