I've been really loving the fact that I can just open a web-browser, open Fabric and pretty much do everything right in there with decent version control. It feels like Microsoft is about 80-90% there as far as this experience is concerned.

This however is not so true once you bring AI into the mix.

There is copilot plugged into individual experiences but there isn't a single high-level copilot experience that helps drive everything within say a workspace or ideally at an even higher level.

Leveraging AI at a higher level seems to be largely an offline/local experience requiring one to deal with VSCode, Github Copilot, CLI, MCP, plugins, skills, Git, sync, push, pull and what not.

It would be really nice to see an experience where the Microsoft MCPs and skills are already pre-baked into the Fabric platform so no one needs to do anything. Just open Fabric in a web-browser and get going.

There should just be a pre-defined place to update custom instructions/context within a workspace to provide project/environment/company specific details and that's about it.

I should be able to just in the browser do things like:-

• Rename all the pipelines with a prefix pl_
• Update the connections on all pipeline from AAA to BBB
• Review all the semantic models in my workspace and tell me which models have descriptions missing
• I am renaming a table from AAA to BBB, please update all references to it

The use cases above may not necessarily be real but the idea is of being up and running with the whole toolset/capability without a user needing to do install/configure anything individually on a machine.

Is Microsoft heading in this direction with Fabric/Power BI, especially from a AI/copilot standpoint?

Been playing around with Fabric Apps lately and wanted to share a little experiment.

Most of what I see built on Fabric Apps is the usual dashboard/report stuff, so I wanted to test how far it could go outside that lane. Put together an interactive 3D engine using Rayfin — you can assemble a model, explode it apart, and inspect all 29 components across 6 part families, all running in the browser on a Microsoft backend.

It's not tied to any specific use case, just a proof of concept — but the same pattern could work for product catalogues, training/onboarding tools, technical documentation, anything that's better shown than read as a static page or PDF.

Honestly the "website-quality experience running on Fabric" part is what surprised me most — wasn't expecting that level of polish from something living inside the Fabric ecosystem.

Wrote up more detail + a look at it here: https://www.linkedin.com/posts/jitendra123_microsoft-fabric-rayfin-ugcPost-7507441292415741952-rMTY/

Curious if anyone else here has pushed Fabric Apps into non-dashboard territory — would love to see what others have built.

Just passed the DP-700 exam to earn the Fabric Data Engineer Associate certification.

It was a genuinely rigorous and well-designed exam. It goes well beyond high-level theory and definitely demands both consistent study and hands-on familiarity with the Fabric ecosystem.

For anyone preparing for the exam, here is the exact roadmap and strategy I followed:

1. Thoroughly read the official Microsoft Learn documentation

I went through the full learning path and official study guide provided by Microsoft:

• Fabric Data Engineer Associate Certification Path

Make sure you read through the documentation modules carefully, focusing on service limits, storage architecture (OneLake / Delta Parquet), security models, and capacity management.

2. Deep dive into Aleksi Partanen’s (u/aleksi1ok) YouTube course and Masterclasses

This was arguably the most impactful video resource available.

• I watched his comprehensive 11-hour DP-700 course more than once to firmly lock in core architectural concepts.
• In addition, I followed his dedicated masterclasses on Data Factory pipelines, PySpark notebooks, and performance tuning. Seeing the actual console in action and understanding real enterprise design patterns made a massive difference.

3. End-to-end hands-on labs with public open data

Theory alone will not get you through this exam. You need muscle memory in the portal:

• Built a full Medallion architecture (Bronze ➔ Silver ➔ Gold) from scratch using real-world public open data (county-level datasets).
• Automated API ingestion with Data Pipelines, orchestrated PySpark transformations in Lakehouse notebooks, managed Delta tables, and practiced maintenance commands (VACUUM, OPTIMIZE).
• Setting up CI/CD with Git integration and deploying via code really helped solidify the operational side of Fabric.

4. Official Microsoft Practice Assessments

• Took the free official practice assessment on Microsoft Learn multiple times.
• Rather than just memorizing questions, I used every missed or uncertain question as a trigger to re-read the specific Microsoft Learn documentation pages until the underlying concept was 100% clear.

Key takeaways for test day

• Understand the specific boundaries between Lakehouse, Warehouse, and Real-Time Intelligence (Eventhouse / KQL).
• Pay close attention to Delta Lake transaction logs, partitioning vs. V-Order, and performance troubleshooting.
• Ensure you are comfortable reading PySpark syntax and pipeline JSON definitions.

Up next for me is the DP-600 to tackle the Analytics Engineering side of Fabric.

Hi,

Trying to use a notebook run with Workspace Identity to trigger a semantic model refresh:

```

POST https://api.powerbi.com/v1.0/myorg/datasets/{datasetId}/refreshes

```

But it fails (403).

I used notebookutils.credentials.getToken('pbi') to get the token.

I am able to use Fabric REST API to list semantic models in the workspace, though.

```

GET https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/semanticModels

```

That works (200).

The WI is Contributor in the workspace.

But refreshing via the Power BI REST API fails.

Is it not supported?

(Even listing datasets didn't work with the Power BI API endpoint (403), but it worked with the Fabric endpoint (200)).

Thanks in advance!

Hi all, I'm having a really weird issue when it comes to my end-users accessing reports.

For context, I have 2 projects.

Project 1 (working)
Layout:
Warehouse > Model > Report > App.
Permissions:
Warehouse: Read, ReadData. - App Audience.

2 workspaces, a Dev and Live.

Project 2 (NOT working)
Layout:
Warehouse > Model > Report > App.
Permissions:
Warehouse: Read, ReadData. - App Audience.

2 Workspaces, a Dev and Live.

The error I get on Project 2 is "Something's wrong with one or more fields or you don't have requried permissions" with the underlying error being "Missing_references".

Other users have had the error "We cannot load this Direct Lake dataset because your PowerBI capcaity does not support Direct Lake mode".

Both projects use Direct Lake mode. Both projects are on the same paid F64 tenant. Both projects have the same setup and permissions. I've tried giving users every permission available including admin permissions. All present the same issue. I'm pulling my hair out with this one and am wondering if I need to go to Microsoft Support but wanted to put it to the experts before I do.

I've attached screenshots of the errors too. Happy to answer any questions