Introduction
The past two months have brought a wave of exciting updates to Microsoft Fabric, each aimed at simplifying workflows and empowering both technical and business users. From powerful new data transformation tools like the Eventstream SQL Operator and Materialized Lake Views, to smoother integration of Azure Data Factory pipelines, Fabric continues to evolve into a more unified and low-friction platform. Added to this are previews in notebooks, Copilot enhancements, and org-level improvements that make data more accessible, collaborative, and actionable across teams.
Notebooks integration with variable libraries (Preview)
Fabric Notebooks now includes Variable Libraries in preview, a feature designed for centralized configuration management. Instead of hardcoding values such as paths or parameters, users can store these variables in a single location, improving flexibility and reusability across teams and projects.
The feature introduces functions like getLibrary(), which allow users to dynamically reference variables (e.g., Lakehouse names) in their code, so switching between dev, test, and production environments becomes seamless. This not only makes deployments smoother but also ensures consistency by maintaining a single source of truth for configurations.
Our element 61 perspective: Variable libraries is a smart step toward cleaner, more maintainable code, especially in collaborative or multi-environment projects where hardcoded values often create friction. Variable libraries definitely streamline deployments.
Notebook: T-SQL and Python code against SQL DW (Preview)
Starting this month, Microsoft Fabric is rolling out a public preview of the T-SQL magic command in Python notebooks. This lets you run T-SQL directly in a Python environment—with full syntax support—so you can execute DDL/DML on Fabric Datawarehouse or SQL Database, or run read-only queries on Lakehouse SQL endpoints. The results can even be converted into pandas DataFrames for further Python analysis, all in the same notebook.
To use this feature, simply set the notebook’s language to Python and start a cell with %%tsql to execute T-SQL commands.
Our element61 perspective: This feature bridges SQL and Python, making it easier to combine traditional data management with advanced analytics. It’s a practical way for data engineers and scientists to work together more smoothly, using the best of both worlds.
Materialized Lake Views
This feature makes it much easier to build and manage data in a Lakehouse. Instead of manually orchestrating pipelines, users can create SQL-based views on raw or staged data that are automatically kept up to date by the system. The feature also offers clear data lineage maps, real-time monitoring, quick issue detection, and data quality tracking with alerts when problems arise. Built on improved Spark SQL, it helps data teams create reliable, scalable data layers without the heavy operational workload.
Our element61 perspective: Materialized Lake Views is a step forward in simplifying data engineering, cutting down the manual work that usually comes with managing data pipelines in a Lakehouse. The built-in automation and monitoring make it easier to keep data reliable and scalable without adding extra overhead. However, some features like API support and incremental refreshes are still missing from Materialized Lake Views. Let’s see if Microsoft addresses these gaps in the coming months.
Eventstream SQL Operator
In its pursuit of a low-code solution, Fabric has introduced no-code data transformation options for real-time processing. This includes filter, managed fields, aggregate, group by, join, union, and expand.
In addition, SQL Operator is now available in Fabric Eventstream. This solution boosts transformation capabilities by letting users apply custom rules with familiar SQL syntax, making it easier to handle complex processing in one central place. The built-in editor makes it easy to write and test queries in real time, with IntelliSense and auto-complete speeding up the process. Once the logic is ready, the transformed data can be sent to any Real-Time Intelligence destination. To enable this feature, go to Transform events button and select SQL operator.
Our element61 perspective: With these two new features, Fabric makes Real-time intelligence features more accessible. It is a smart move from Fabric, balancing no-code options for quick transformations with the flexibility of SQL for more advanced needs.
Azure Data Factory item in Microsoft Fabric (Generally Available)
Microsoft Fabric now lets you bring your existing Azure Data Factory (ADF) pipelines into Fabric without rebuilding them, thanks to the general availability of the ADF Mounting feature. You can now mount pipelines from Git-enabled ADF factories or directly from the ADF interface, making it quick and easy to manage your data pipelines inside Fabric workspaces.
Our element61 perspective: Having the ability to mount pipelines directly from Git or the ADF interface simplifies workflow management and speeds up integration with Fabric. This new feature is definitely a big time-saver, making it much easier to manage existing ADF pipelines without starting from scratch.
Organizational themes
Power BI now offers Organizational Themes (in preview) to help companies keep their reports visually consistent and on-brand. Admins can upload, manage, and share custom themes—like color schemes and fonts—through the Admin Portal, making them available to all report creators in both Power BI Desktop and the Power BI Service. These themes are disabled by default but can be enabled by admins, who can also set a preferred theme for AI-generated reports (via Copilot). This ensures that even automated reports match the company’s style from the start. Report creators can still choose a different theme if needed. Plus, the sleek theme previously reserved for Copilot is now accessible to everyone. Only admins can manage these themes, while users simply select from the approved options in the theme gallery.
Our element61 perspective: With this feature, it is now possible to keep all your reports—whether you build them manually or with AI—looking consistent and on-brand without any extra work. Managing themes centrally in the Admin Portal makes collaboration easier, ensures everyone follows company standards, and it even has the option to use Copilot’s clean default theme for any project.
It’s a simple yet powerful way to keep your workflows smooth while ensuring every report looks polished and professional, regardless of who puts it together.
Power BI Enhanced Report Format (PBIR) Update
Power BI’s PBIR file format is now out of preview and fully supported. It fixes earlier limitations, so you can now:
- Deploy reports using Fabric deployment pipelines
- Save copies of reports directly in the service
- Track report usage metrics
- Use Power BI’s REST APIs for full integration
With the addition of the Power BI Project (PBIP) format—also called "developer mode"—teams can finally work with proper version control, automation, and collaboration, making report development a lot smoother. No more manual workarounds.
Our element61 perspective: This PBIR update, along with the PBIP format, is a step further in treating Power BI reports like code—enabling version control, automated deployments, and smoother team collaboration. No need for clunky workarounds anymore. For anyone who cares about efficiency and scalability, it’s a change that turns Power BI into a proper developer tool, not just a reporting platform.
Use Copilot on reports in org apps (Preview)
After the release of Copilot directly in the reports and semantic models in May, Fabric released a Copilot pane in the org apps. This tool can help users to navigate through the report better and dig deeper in a user-friendly manner.
Our element61 perspective: The Copilot pane in Fabric’s org apps transforms the user experience by making data exploration feel as natural as asking a colleague for help—no need to hunt through menus or understand underlying models. For business users, it’s a game-changer: faster insights, less friction, and a more engaging way to interact with reports, as long as the responses stay sharp and context-aware. The risk? Over-reliance on AI could mask gaps in data literacy if users skip learning the basics.
Final thoughts
These releases show Microsoft’s clear direction: making Fabric a one-stop, user-friendly platform for both low-code exploration and advanced data engineering. It’s a promising step toward giving organizations the flexibility to innovate faster while keeping operations simpler and more connected.
If you are keen to learn more about Microsoft Fabric, do reach out via the element61 contact form.
