How to Create a Report from Dataflow in Power BI

Building reports in Power BI is one thing, but building them efficiently is another game entirely. It’s easy to get stuck in a cycle of connecting to the same data sources, applying the same cleaning steps, and tweaking the same column names for every single new report you create. This repetition is not only tedious but also a recipe for inconsistency. That’s where Power BI Dataflows come in, offering a smarter way to manage your data preparation. This article will show you exactly how to create a Dataflow from scratch, connect it to Power BI Desktop, and start building reports on a clean, reusable foundation.

What Are Power BI Dataflows, and Why Should You Bother?

Think of a Power BI Dataflow as a master recipe for your data. Instead of digging out all the individual ingredients and measuring them every time you want to make a cake (build a report), you create a perfectly measured, pre-mixed batch of all the dry ingredients upfront. When you're ready to bake, you just grab your "cake mix," add the wet ingredients (your report visuals), and you're good to go. The prep work is already done.

Technically, a Dataflow is a collection of tables created and managed inside the Power BI Service (the online version). It uses Power Query to connect, clean, transform, and shape your data one time, right in the cloud. Once your Dataflow is created, you and your team can connect to it from multiple Power BI reports, Excel files, or other applications, ensuring everyone is working from the same source of truth.

Leveraging Dataflows offers several clear advantages:

• Reusability: This is the headline benefit. Define your connection and data transformations for your core datasets - like monthly sales, advertising spend, or website traffic - once. Then, reuse that clean data across dozens of reports without ever repeating the prep work.
• Consistency: When everyone on your team connects to the same Dataflow, they're using the exact same definition for metrics and dimensions. No more meetings where one person's "Total Revenue" report shows a different number than someone else's.
• Separation of Duties: Dataflows allow you to separate the task of data preparation from report creation. Data-savvy team members can focus on building robust, clean Dataflows, while marketers and analysts can focus on building beautiful, insightful reports in Power BI Desktop without getting bogged down in data cleaning.
• Improved Performance: All the heavy lifting of data transformation happens in the Power BI cloud service, not on your computer. This can significantly speed up report authoring and data refreshes in Power BI Desktop, especially when dealing with large datasets.

Step-by-Step: Creating Your First Dataflow

Let's walk through creating a basic Dataflow. You'll need a Power BI Pro or Premium license to create and use Dataflows, as this feature lives within the Power BI Service.

For this example, we’ll create a Dataflow for some sample online sales data, preparing it for a sales performance report.

Step 1: Navigate to Your Workspace

First, log in to your account at app.powerbi.com. From the left-hand navigation pane, select the Workspace where you want to create your Dataflow. In your Workspace, click the + New button and then select Dataflow from the list.

Step 2: Add New Tables

You'll be prompted to choose how you want to create your Dataflow. Since we're starting from a new data source, click on the Add new tables card.

Step 3: Connect to a Data Source

This next screen should look very familiar if you've ever used Power Query. It presents you with a list of all available data sources. You can connect to databases, SharePoint files, Salesforce, and much more. For simplicity, we’ll use an Excel file hosted online that contains sample sales information.

Choose Excel workbook as your data source. You'll be prompted to provide a file path or URL. We'll use a URL to connect to the sample data source.

Step 4: Clean and Transform Your Data with Power Query Online

Once connected, you’ll find yourself in the Power Query Online editor - which is the heart of the Dataflow process. This environment is nearly identical to the Power Query editor in Power BI Desktop.

Here’s where you apply your "master recipe" of data transformations. Let's perform a few common cleaning steps on our sample sales data:

• Remove Unnecessary Columns: Our sample data has a column called "Row ID" that we don't need for analysis. Right-click its header and select Remove.
• Change Data Types: Power Query is pretty good at guessing data types, but it's always worth double-checking. For instance, make sure your "OrderDate" column is set to the Date type and that "TotalSales" is a Decimal Number. You can change this by clicking the icon in the column header.
• Split Columns: Let's say we have a "ProductID" column that combines a category and a number, like "TECH-1001." We can split this into two separate columns. Select the column, go to the Transform tab in the ribbon, and use Split Column > By Delimiter (using the "–" hyphen as the delimiter).
• Rename Columns: Finally, give your columns clear, friendly names. Rename "ProductID.1" to "Category" and "ProductID.2" to "SKU." Rename "TotalSales" to "Revenue." Clean names make report building much easier later on.

As you apply these steps, they are all recorded in the "Applied Steps" pane on the right, just like in Desktop.

Step 5: Save Your Dataflow

Once you are happy with your transformations, click the blue Save & close button at the bottom right. Power BI will ask you to name your Dataflow. Use a descriptive name that tells you what's inside, something like "Global Sales Data - Q1 2024".

After saving, Power BI will validate your new Dataflow. You can also configure a scheduled refresh, which is highly recommended. You can tell your Dataflow to refresh automatically every morning, ensuring any report connected to it always has the latest data without manual intervention.

Connecting Power BI Desktop to Your Dataflow

Great, we’ve built our Dataflow in the cloud! Now let’s see how an analyst would actually use it in a report.

Step 1: Open Power BI Desktop and Get Data

Open a new, blank Power BI Desktop file. In the Home ribbon, click Get Data. From the dropdown list, select Power BI dataflows. (You may need to click "More..." and search for it if it's not immediately visible).

You’ll be asked to sign in to your Power BI account if you aren't already.

Step 2: Select Your Dataflow

A navigator window will appear, listing all the Workspaces in your Power BI organization that you have access to. Expand the Workspace where you saved your Dataflow.

You’ll see the "Global Sales Data - Q1 2024" Dataflow we created. Expand it one more time to see the tables inside. Select the tables you need for your report and click Load.

You might notice the "Transform Data" button is either grayed out or has limited functionality. This is intentional! The transformation logic lives in the cloud Dataflow, not in your local report file. Your Power BI report is simply becoming a consumer of that pre-prepped data.

Building Your Report - Welcome to Easy Mode

With your data loaded from the Dataflow, you're now ready to build visualizations. If you look at the Data pane on the far right of your screen, you'll see your tables. All the columns have the clean, friendly names we gave them. All the data types are correct. The transformations are already applied. No further cleaning is required.

You can now start building visuals instantly:

• Drag the "Revenue" field onto the canvas and turn it into a Card visual to see the grand total.
• Create a Bar Chart showing "Revenue" by "Category" to quickly identify your top-performing product lines.
• Use a Line Chart to plot "Revenue" against the "OrderDate" column to visualize sales trends over time.

The experience is fast and smooth because all the heavy lifting was done once in the Dataflow. Any time a teammate needs to build another report with this same sales data, they just repeat the two simple connection steps and get straight to building great visualizations.

Final Thoughts

Power BI Dataflows provide a central, reusable data preparation layer that saves you from redundant work and promotes data consistency. By separating the logic of data transformation from the art of report building, you create a far more organized, scalable, and efficient analytics workflow for yourself and your team.

While mastering tools like Power BI Dataflows is a powerful skill, it requires a significant investment in learning and setup. We built Graphed because we wanted to eliminate that steep learning curve and the tedious, manual work involved in business intelligence. Instead of wrangling data connections and building transformation pipelines, our platform allows you to connect sources like Google Analytics, Shopify, or Salesforce in just a few clicks. From there, you just use plain English to build the dashboards you need in seconds. Our AI handles the data prep and visualization automatically, turning hours of report building into a simple conversation and letting you get straight to the insights that matter.