Chris Webb wrote a great post today “Power BI Roadmap Announcements In the Dynamics 365 Spring ’18 Release Notes” citing the many exciting new features coming to Power BI in the next few months and highlighting the huge momentum behind Power BI. I want to bring your attention to a couple of them:
- Incremental data refresh: Organizations can use incremental data refresh to scale datasets to even larger sizes. With incremental data refresh, users can load only new or changed data. When creating a dataset in the Power BI Desktop, a user configures a refresh table for each table in the model that is to load incrementally, and then publishes it to a Power BI Premium workspace. Thereafter, each scheduled refresh loads only new or changed data.
- Query acceleration for large datasets (Public Preview): Users can create DirectQuery models over any size data in sources, such as Spark and Azure SQL Data Warehouse, and then accelerate common queries by building in-memory aggregations over some of the data. Common queries use the aggregated cache to return results in a fraction of a second instead of directly querying the source. Users can create datasets of massive size and still provide interactive querying.
Why is this important? Because important professional features have crossed the Analysis Services-Power BI line and now business users can build large-scale models using Power BI Desktop. In fact, it looks like “in-memory aggregations” would come first to Power BI as we don’t have them in Analysis Services (yet). Now, I’m not a big proponent of business users building “massive” models (such datasets should be centralized and sanctioned by professionals) but apparently there is a good case for it. In fact, in my “Why Business Like Yours Choose Power BI Over Sisense” blog, I mentioned that SiSense uses this as a competitive advantage. At that time, the maximum Power BI dataset size was 1 GB. If you wanted to build larger models, you had to use Analysis Services, which has a separate price tag, and requires Visual Studio for development. Not to mention that you have to migrate your models from Power BI Desktop to Analysis Services (supported in AAS but not officially supported with on-premises SSAS) and learn new skills.
A lot has changed since. Notably, Power BI Premium raised the maximum dataset size to 10 GB and it’s likely that this limit would be raised further. While I’m not ready to embrace Power BI Desktop for organizational semantic models yet, soon Power BI Premium users will have the option to use a business-user friendly tool (Power BI Desktop) for implementing larger semantic models. And, of course, another important motivation to take this path is reducing licensing cost.
“While I’m not ready to embrace Power BI Desktop for organizational semantic models yet…”
Well, you better get ready to embrace it Teo because we are bringing the full power of professional semantic modeling to the Desktop!
We are committed to making the Desktop a no-compromise Pro BI development environment that will scale to the largest and most complex models. And this summer you will see the first big installment.
We have also fully committed to providing through Power BI Premium the best Analysis Services system you can find anywhere: Scaleable to new limits, fully programmable, with unique features found nowhere else, and with total and seamless integration with the rest of the Power BI stack.
Well, Amir did advise that folks should start learning DAX a decade ago so I guess its now time to figure out how to do professional semantic modeling since it’ll be arriving in the Desktop shortly 🙂
Thanks Amir! I’ll be following this closely. As you know I’m somewhat skeptical about changing paradigms. By biggest concern is speed of development. I need to need to see how Power BI Desktop will perform given that even SSDT can’t perform with more complicated schema. In addition, I’d like know what AS features will make the cut, especially:
Perspectives
Partitions
Actions
Source control integration
Ability to interchangeably use VS and Power BI Desktop and reverse engineer Power BI-hosted AS models to both formats. So, I’ve started with VS and want to move to Power BI Desktop, can I do it? And vice versa.
Open Power BI AS management endpoint (using SSMS, Profiler, AMO)
Out of curiosity, what do you think developers will gain by modeling in Power BI Desktop for organizational semantic models?
Teo,
I am think there is already a broad consensus that the Power BI Desktop is a more productive BI development environment for BI project than SSDT. Most Pros will admit (with a little whisper) that they already do most of their development there.
The challenge of the Desktop is dealing with high scale models (hundreds of tables) and advanced features that are simply missing as you outlined.
We are committed to fixing both. Make the Desktop appropriate for large scale Tabular semantic model development and add the missing advanced modeling features.
When we are done (and we move pretty you know), we believe will not want or need to use SSDT/VS anymore.
Hi Amir,
Thanks for clarifying. I’m excited about letting customers deploy semantic models to Power BI and thus saving cost. I’m not so sure that “there is a broad consensus that PBID is a more productive IDE”. Historically, we’ve seen how community tools, such as BIDS Helper and DAX Editor, have filled in gaps in the Microsoft-provided design tools. This works for VS because it’s extensible. Power BI Desktop is not, which is another thing I’d like to add to my wish list. Ideally, I’d like to see Microsoft supporting both Power BI Desktop and SSDT to design semantic models deployed to both Power BI, AAS, and SSAS. Let’s give modelers the choice of which tool they prefer. This is conceptually similar to SSRS Report Designer and Report Builder.
Thanks for listening!
Hi Amir! I totally agree with you. I would much rather develop models in Power BI Desktop than SSDT/VS, it is a much more responsive UI and of course it is being enhanced more often! Lets achieve parity though, that is what forces me to use SSDT/VS!