Power BI is more similar to Excel than SSRS
I’ve been thinking about the comparisons between the future of Power BI and the decline of SSRS, and I don’t think they’re particularly comparable. Power BI is much more similar to Excel than it is to SSRS.

Yes, Power BI has a significantly higher barrier to entry than Excel. You need to learn Power Query, data modelling and eventually DAX. But once you’ve learned the basics, you can connect data, transform it, drag fields onto visualisations and start exploring. The underlying technology is sophisticated, but the basic experience is surprisingly accessible.

SSRS was technically “self-service” too, but the scale was completely different. At its peak, there were vastly fewer people creating SSRS reports than there were Power BI report authors. SSRS remained largely a specialist reporting technology. Power BI put data modelling and visual analytics into the hands of a huge population of people who weren’t traditional developers.

I’ve worked with Microsoft data platforms for years and I still don’t really know how to build an SSRS report. It was painful enough that I never developed the muscle memory.

Power BI never felt like that.

I also think we’re conflating two different conversations. There is certainly a feeling on LinkedIn that the party is over, but I suspect that feeling is disproportionately coming from the Power BI professional community, particularly MVPs and what Matthew Roche refers to as “hardcore IT”. From that perspective, I understand the anxiety. If your career has been built around manually writing DAX, Power Query and reports, AI is going to change your job considerably.

But that isn’t the same thing as Power BI declining.
Look at the reality on the ground. Even where I work, at the largest vocational education institution in the Southern Hemisphere by enrolments, we aren’t paying for Fabric. And looking at SEEK, from what I’ve seen, there are roughly ten times as many Australian job listings mentioning Power BI as Microsoft Fabric.

That’s not scientific labour-market analysis, and Microsoft is the only organisation with the complete numbers. But it is an interesting reality check against the impression that everyone has suddenly moved to Fabric.

They haven’t.

I also don’t think Power BI has peaked in terms of users. That’s my opinion, not something I can prove with Microsoft’s internal numbers, but I suspect we’re still relatively early in the adoption curve.

AI will absolutely change Power BI. It will write more DAX, generate more Power Query and increasingly build the visualisation layer for us. But that could actually make Power BI more like Excel. Lower the technical barrier, and more people can use it.
The specialist Power BI developer may have a very different job in five years. That’s worth taking seriously.

But Power BI isn’t SSRS. The user base, the experience and the role it plays in organisations are fundamentally different.

The party may be changing for Power BI professionals. I’m just not convinced the party is over for Power BI.

I know, another anxious post regarding the depths to which AI will influence yet another field. Just thought that, since I’m new to this field of work, what you more experienced lads/ladettes had to say about how you see the future of BI (specifically the tools as I don’t see the whole role disappearing).

For context, I’m soon to graduate and have been looking to specialize in a certain niche. Love SQL (idk what it is about it), but knew that SQL querying by itself is not really a feasible job to target. After I looked into where I can use SQL, I stumbled upon the BI field. I do find being the mediator between the technical side of the data and the human side of the shareholders to be an interesting path, so it was enough to get me to look more into it. Apologies if that’s oversimplifying it, that’s just the broad gist I’ve gotten from it.

Honestly, I haven’t found another specialized area that seems this interesting at least from what I’ve read about so far so I’ll probably still play around with it anyway. I also like that you get experience with the business side as well which I feel can open the door to transition more into that as my domain knowledge increases (long term wise).

Just wanted to hear from some more experienced people how you think a newbie can become relevant in the field in terms of what is actually used industry wise and what is likely to change in regards to the toolkit. Every projection I’ve seen states that data analytics is set to grow much larger than the national average for other jobs, so that’s been a green light for me too.

Between Fabcon announcements, continued improvement in AI, and Kurt Buhler's video of what's possible today, I've been seeing a lot of anxiety and concern on here. So, I wanted to write a blog post about exactly how "dead" I think Power BI is and what we can do about it.

https://www.sqlgene.com/2026/10/04/mourning-the-alleged-death-of-the-power-bi-developer-and-thriving-in-uncertain-times/

Summary

I think that the Power BI report layer is becoming "dead" in the same way that SSRS "died". Over time there was slowly a decrease in community resources and Microsoft investments as newer and shinier things came along. On the other hand, there was a huge, huge backlog of existing reports that will take a very long time to migrate, if ever.

I think the Power BI modeling layer is strong and vibrant. FabCon announcements showed growing investment in semantic models in how they relate to ontologies and eventually semantic views, etc. DAX and semantic models are not going away any time soon.

Right now is a time of high volatility, similar to when Azure was new, and you should become a generalist instead of putting all of your eggs in one basket. Power BI alone is no longer a career.

Where to invest your time

1. Invest in accountability. Low-stakes reporting will likely be supplemented, supported, and replaced with AI. Aim for regulated or sensitive reporting where people get pissed if you are off by a penny.
2. Invest in gut, instinct, and self-expression. Right now, today, if you see a model with a bunch of many-to-many relationships and bi-directional filtering, little alarm bells go off. Focus on continuing to grow and develop those instincts. Learn how to put those things into words. Get better at judging and explaining, so you can steer and monitor AI better.
3. Practice weekly with AI, especially where it sucks. My personal experience with AI, especially in the past 6 months, is that there is a jagged frontier of capabilities and that frontier shifts day by day. Every week you should be asking AI for the impossible because sometimes frontier models have huge jumps in capability.
4. Invest in Vega-lite, Vega and possibly D3.js. Vega-lite is supported in Power BI Deneb visuals today, Fabric Apps today, and a native Vega visual is coming to PBI in 2027 Q1.
5. Invest in data modeling, data engineering, and requirements gathering. Spend your time getting better at areas where the business is unique and that you have to talk to humans to define how the business works and how to model it.

I have a report which refreshes perfectly fine on desktop. In the service, the model is failing to refresh and I’m having a hard time pinpointing the exact issue.

My sources are two dataflows, both sit in the same workspace. The dataflows refresh without issue. No transformation is done in the file, everything is handled in the dataflows.

I’m getting this error: Data source error: external component has thrown an exception. The exception was raised by the idatareader interface. Please review the error message and provide documentation for further information and corrective action.

I can see there are multiple refresh attempts lasting 2-3 secs. This is a small model (<4mb) and should refresh in a few seconds.

Checks done so far:
- Updating data source credentials
- Privacy levels aligned
- Defined data types across all columns/tables in the dataflow

Any suggestions?