Welcome back to a brand new episode of the Fabric Threads podcast! In July, Microsoft Fabric announced countless updates to the platform that will directly impact efficiency and security.

So much of this has been implemented as a result of direct end-user feedback, so keep reading to see if anything you’ve requested from Fabric before has finally come to fruition.

Enhanced Row-Level Security Editor in Power BI Desktop

One of the standout features this month is the enhanced Row-Level Security (RLS) editor in Power BI Desktop.

This update is a game changer for organizations that need to enforce data security at the most granular level, or row level, inside of Power BI semantic models. What this allows you to do is to define specific users or groups within your organization that view only certain subsets of data. Ultimately, this helps to protect sensitive information.

The legacy RLS interface relied heavily on writing DAX code to filter data based on who was logged into the semantic model, whether they were viewing data through a visualization or through a specific report built on top of that semantic model. While this ensured security, it wasn’t the most user-friendly interface.

This RLS update helps maintain these security standards while offering a much more easy to use, graphical interface. Now, Power BI developers and administrators can build security rules visually, creating what-if scenarios without needing to write extensive DAX code.

This still requires some setup, since you have to configure these security rules on every semantic model you’re developing. But this little bit of upfront work more than pays off when you consider how easy it is compared to the code-heavy solution before.

Time Travel in Fabric Warehouse

After months in public preview, time travel in Fabric Warehouse is now generally available. This makes it possible to go back in time (hence, the Back to the Future-esque name), and query historical data within your Fabric warehouses, giving you a crucial safety net for data integrity.

The main problem this Fabric feature addresses is the risk of data loss or unintentional changes during your daily operations. Whether records are modified, deleted, or added, time travel lets you go back and review up to 30 days of historical data.

Let’s say, you realize you accidentally deleted something. Time travel makes it easy to revert to the previous state and avoid any issues. Or let’s say you’re experiencing some problems and aren’t quite sure what the issue is. You can easily use time travel to look at a full record of what’s been removed, added, or modified to identify any changes that may be having an impact.

There is a common misconception we’re hearing that this feature needs a lot of resources to go back and query these historical records. However, this is not the case. Microsoft developed time travel specifically to enhance and be implemented within your data environment, so performance shouldn’t be negatively impacted.

However, it’s important to note the 30-day limitation. This feature may fall short for organizations requiring a longer look-back period. But for most users— data engineers, analysts, and administrators—this will be extremely valuable in ensuring data quality and data integrity within the Fabric environment.

Public Preview of Lakehouse Schemas

Managing a large number of tables in your data lakehouse quickly becomes chaotic. That’s why Microsoft Fabric has introduced lakehouse schemas to add an organizational method on top of your tables. It essentially acts like a map to help you best move through your lakehouse.

With lakehouse schemas, you can group your tables into a more structured format. Group tables based on business unit, department, data source, or any other relevant logical grouping that suits your organization’s specific needs. This method not only makes your lakehouse easier to navigate, but also helps enhance collaboration and efficiency across teams.

Until now, you could have anywhere from 20 to over 100 tables within your lakehouse with no clear organizational structure. This got very messy very quickly, especially if you had multiple people or separate teams trying to navigate the data.

The fact that you can now group these tables with a clear organizational structure makes it infinitely easier for the data engineers and lakehouse administrators creating tables within lakehouse environments.

Edit JSON Code for Data Pipelines

For users who prefer working with code, the ability to edit JSON code directly within data pipelines is a welcome change. JSON, a text-based format for storing and transmitting data, is now editable within Fabric’s data pipeline environment.

Before this update, users were limited to modifying pipelines through the graphical interface in Data Factory. Now, with access to the backend JSON code, users have more granular control over their data pipeline transformations. This gives users flexibility in choosing between a graphic interface and coding, depending on their skill set and project requirements.

Just to be clear, though, JSON is not replacing the graphical interface. The Fabric team designed these to complement each other, giving users the best of both worlds by providing both an easy-to-use and a more advanced solution.

On-Premise Support for Fast Copy

This is arguably the most impactful Fabric update of the month.

Thanks to on-premise support for Fast Copy, organizations can now copy massive amounts of on-premise data directly into their Fabric environment. Even if you’re dealing with terabytes of data in an on-prem environment, ingesting all data into your Fabric cloud environment will happen in a matter of minutes.

Many organizations are still fully on-premise, so this capability makes it quick and efficient to transition to a cloud environment.

On-premise support for Fast Copy isn’t just helpful for large enterprises. We’re seeing many small and medium-sized businesses expressing interest in moving into a more Fabric-based environment, so this update benefits them, too. The time and cost savings are significant regardless of organization size.

Efficiency, Security, and User Experience at the Forefront

This round of Fabric updates reflects a clear focus on enhancing efficiency, security, and user experience.

Every month, we see many steps taken to make Fabric data environments more robust and easier to manage—we love sharing these exciting updates with you here in our monthly Fabric Threads discussions.

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And, if you’re ready to dig deeper into Fabric’s capabilities and create meaningful change in your organization’s data processes, reach out to our team.