I’ve been doing a lot of building with both Claude Dashboarding and Fabric Apps. I wanted to find out which one I prefer and which one has the potential to be better. Here are my findings.
The creation process for dashboards is pretty much the same. Start by creating a design mock-up (preferably using Claude Design), define the requirements — including calculation logic, time intelligence, and data sources — and ask Claude to build the dashboard based on the mock-up and those requirements. Then fine-tune the dashboard to your liking.
The real difference, however, isn’t in the front end, but in the back end.
When Power BI took off around 10 years ago, we all started building dashboards at scale. It didn’t take long for us to realise that the real strength of a good dashboard lies in the back end: data quality, choosing the right data model, scalability, and maintainability.
Now we have Claude Dashboarding, and the output is impressive. But let’s not forget everything we’ve learned over the years.
A good dashboard is only as good as its back end.
The output may look the same, but what’s happening behind the scenes is different. And that’s where I believe Fabric Apps still have the edge.
Fabric Apps rely on a semantic model. Creating one takes time, but isn’t that exactly what we’ve learned over the years? That time isn’t wasted. It’s an investment in building a solid model, making the right decisions, challenging assumptions that turned out to be wrong, and gaining a deeper understanding of our data and the business itself.
Claude Dashboarding offers a different approach. It allows us to generate insights quickly, without necessarily having to build that same structured foundation first. And that’s valuable, too. It gives the business the insights it needs to keep moving while we work on a more robust, long-term solution.
I believe the two should go hand in hand.
Use Claude Dashboarding to deliver quick insights and help the business make decisions in the short term. Use Fabric Apps to build a robust, reliable, scalable, and maintainable solution for the long term.
Speed gives us insights. A solid data foundation makes those insights sustainable.
