In a recent full course by Pragmatic Works, instructors Mitchell Pearson, Manuel Canana, and Zayn dive into the world of Microsoft Fabric and how Power BI developers can use it more effectively. With the number of features Fabric offers, it’s easy to feel overwhelmed. This course breaks down what you need to know and how to get started in a way that’s practical, clear, and actionable.
What Is Microsoft Fabric and Why Should Power BI Users Care?
- Microsoft Fabric is a unified platform that supports various roles—engineers, scientists, and analysts—with an integrated data ecosystem.
- OneLake is a single, organization-wide data lake that simplifies governance and access across teams.
- Lakehouses sit on top of OneLake, allowing developers to organize and access curated data for specific use cases or departments.
Key Concepts Introduced
- Creating a Lakehouse:
- Step-by-step guidance on building a lakehouse from scratch or using existing files.
- Use of shortcuts to connect to curated data from Azure Data Lake Storage Gen2 or other internal lakehouses.
- How to add tables from CSVs and convert them into usable data models.
- Building a Semantic Model:
- Explanation of semantic models in Fabric, which mirror Power BI Desktop models.
- How to define relationships and write DAX calculations.
- Introduction to Direct Lake mode—a key feature enabling high-performance, live reporting without refreshes.
- Using Dataflow Gen2:
- Dataflow Gen2 is essentially Power Query in Fabric.
- Allows more flexibility in shaping, transforming, and loading data into lakehouses.
- Zayn demonstrates building a “Customer” table, adding new columns like Full Name and Age Group using point-and-click logic.
Hands-On Demos: From CSV to Dashboard
The course features detailed, guided demos showing how to:
- Create a workspace and lakehouse in Fabric
- Import curated sales and dimension tables through shortcuts
- Convert raw CSV files into delta parquet tables
- Build a semantic model and define relationships using the online editor
- Connect to the semantic model in Power BI Desktop using Direct Lake mode
Advanced Customization with Power Query and Dataflow Gen2
Zayn takes the course further by enhancing the customer data with:
- Data type conversions
- Merged columns to create Full Name
- Calculated columns like Customer Age and Age Breakdown using conditional logic
- Scheduled refreshes and failure notifications
Integrating Power BI Desktop and Fabric
Manuel wraps up the course by demonstrating how changes in Fabric—like updated customer tables—can be reflected directly in Power BI Desktop without re-importing. He emphasizes the power of using Direct Lake mode:
- Import Mode offers great performance but requires refreshes
- Direct Query allows real-time data access but can be slower
- Direct Lake combines the best of both—no refresh required, high-speed access
Final Takeaway
This course is a strong entry point for Power BI developers stepping into Microsoft Fabric. It stays grounded in tools they already know—Power Query, Power BI Desktop—and shows how those skills translate into Fabric’s more scalable, enterprise-friendly features. With clear walkthroughs and relatable use cases, this is more than a tech demo; it’s a real-world primer for the future of Power BI development.
Don't forget to check out the Pragmatic Works' on-demand learning platform for more insightful content and training sessions on Fabric and other Microsoft applications. Be sure to subscribe to the Pragmatic Works YouTube channel to stay up-to-date on the latest tips and tricks.