Become a Data Factory Developer Using Microsoft Fabric.

Get started with Data Factory in Microsoft Fabric by building practical data pipelines.

Microsoft Fabric brings together data integration, data engineering, data warehousing, analytics, and business intelligence in a unified platform. Data Factory in Microsoft Fabric provides capabilities for connecting, moving, and transforming data across different data sources.

In this beginner-friendly course, we focus specifically on Data Pipelines in Microsoft Fabric Data Factory.

Rather than trying to cover every feature available in Data Factory, this course takes a focused, hands-on approach. You will build a practical data ingestion solution that moves files from Azure Data Lake Storage Gen2 (ADLS Gen2) into a Microsoft Fabric Lakehouse.

What will you learn?

We start by setting up the resources required for our project. You will create the necessary Azure resources and storage services and then move into Microsoft Fabric to create a Workspace and Lakehouse.

Once the environment is ready, you will create your first Microsoft Fabric Data Pipeline.

We begin with a simple use case: copying a single file from Azure Data Lake Storage into the Fabric Lakehouse. You will configure the source and destination, execute the pipeline, and validate the output.

After understanding the basic Copy activity, we gradually make the pipeline more dynamic.

You will use the Get Metadata activity to retrieve information about files available in Azure Data Lake Storage. This allows our pipeline to discover files rather than depending entirely on manually specified file names.

Next, you will work with the ForEach activity to iterate through multiple files. You will learn how ForEach can be combined with other pipeline activities to process files dynamically.

We will then introduce the Filter activity to identify only the files that are relevant to our ingestion process.

Finally, we bring these concepts together to build a pipeline that can discover, filter, iterate through, and copy multiple relevant files from ADLS into Microsoft Fabric.

During this course, you will work with:

• Microsoft Fabric Data Pipelines

• Fabric Workspace

• Microsoft Fabric Lakehouse

• Azure Data Lake Storage Gen2

• Copy Data activity

• Get Metadata activity

• ForEach activity

• Filter activity

• Pipeline expressions and dynamic file processing

Who is this course for?

This course is designed for beginners who want to start working with Data Factory and Data Pipelines in Microsoft Fabric.

It can also be useful for Azure Data Factory learners and data professionals who want an introduction to building pipeline-based ingestion solutions in the Microsoft Fabric environment.

You do not need advanced Microsoft Fabric knowledge to get started. The course follows a practical, step-by-step approach and focuses on understanding the core pipeline concepts through a simple project.

What will you be able to do after the course?

By the end of the course, you should have a practical understanding of how Data Pipelines work within Microsoft Fabric Data Factory.

You will know how to create a pipeline, connect to Azure Data Lake Storage, copy data into a Fabric Lakehouse, retrieve file metadata, iterate through multiple files, filter files, and combine these activities into a more dynamic ingestion workflow.

This course is intended as an introduction to Microsoft Fabric Data Pipelines, providing a foundation that you can build upon as you explore more advanced Microsoft Fabric Data Factory and data engineering capabilities.

Disclaimer

This is an independent educational course and is not affiliated with, endorsed by, or sponsored by Microsoft. Microsoft, Azure, Microsoft Fabric, Azure Data Factory, and other Microsoft product names are trademarks of their respective owners.

Microsoft Fabric and Azure are continuously evolving cloud platforms. Features, user interfaces, service availability, pricing, trial options, and configurations may change after the course is published. Some demonstrations require access to Microsoft Azure and Microsoft Fabric, and the use of cloud resources may result in charges depending on your subscription and usage. Always review the latest official Microsoft documentation and pricing information when creating or using cloud resources.

AI tools were used as supporting tools during the creation of this course, including assistance with content preparation, research, language improvement, and the development of selected learning materials. The course structure, technical demonstrations, explanations, hands-on activities, and final content were reviewed and prepared by the instructor.