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Deploy and Use Azure Data Factory with Power BI: A Simple Guide

  • aferencz21
  • Oct 24
  • 2 min read

If you are new to Microsoft Cloud and wondering how to make your data dance between Azure Data Factory and Power BI, you are in the right place. Think of Azure Data Factory as the choreographer and Power BI as the stage where your data performs. No complicated moves required.


What You Need Before You Start

  • An active Azure subscription

  • A Power BI account

  • Basic understanding of what data is (if you are still thinking “Excel but bigger,” you are on track)



Step 1: Create Your Data Factory

  1. Sign in to the https://portal.azure.com.

  2. Search for Data Factory and select Create.

  3. Fill in the basics: subscription, resource group, region, and name.

  4. Hit Review and Create.

  5. Wait for deployment to finish. This is the cloud equivalent of brewing coffee, fast but still needs a moment.


Step 2: Build a Pipeline

Pipelines in Azure Data Factory are like assembly lines for your data.

  1. Open your Data Factory resource and select Author & Monitor.

  2. Use the Copy Data tool to bring data from your source (SQL, Blob Storage, or even SaaS apps).

  3. Configure your source and destination. For beginners, start with Azure SQL Database or Azure Data Lake.

  4. Validate and publish the pipeline.


For a full walkthrough, see Data Factory Tutorials.


Step 3: Transform Data with Data Flows

If your data needs a makeover before hitting Power BI, use Mapping Data Flows.

  • Go to Author > Data Flows.

  • Add transformations like join, filter, or aggregate.

  • Save and debug to make sure your data looks sharp.


Step 4: Connect to Power BI

Now for the fun part, visualizing your data.

  1. Open Power BI Desktop.

  2. Select Get Data > Azure > Azure Data Lake Storage or Azure SQL Database (depending on where your pipeline landed the data).

  3. Load the data and start creating reports.

  4. Publish to Power BI Service for sharing and collaboration.


For integration tips, check Azure and Power BI.


Step 5: Automate Refresh

Use Azure Data Factory to trigger Power BI dataset refreshes. This ensures your reports stay fresh without manual effort.

  • Configure a Web activity in your pipeline to call the Power BI REST API.

  • Authenticate using a service principal.



Why This Matters

Combining Azure Data Factory and Power BI gives you:

  • Scalable data integration

  • Real-time insights

  • A single source of truth for your analytics


And yes, it makes you look like a data superhero without wearing a cape.


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