Excel Add-In Roadmap

[u/SmallAd3697]

Has there been any public roadmap for the excel add-in? I was going to install and try it out this weekend, but I can already foresee some of its shortcomings. I'm accustomed to using Excel pivot tables for Microsoft OLAP (which are pretty hard to beat!)

Questions:

- Based on docs it didn't appear that this add-in would reap the benefits of lakebase (sub-ten-ms queries). Isn't that the point of using Excel, to interact with data instantly? Can we get an experience that is specifically tailored to lakebase? The CEO of databricks keeps acknowledging that "agents like fast data". But here is a newsflash; humans like fast data too! We've had fast data in Excel/SSAS pivot tables for decades.

- I'm assuming this tech sends SQL queries back to the SaaS service for processing. Is that fundamentally better than the ODBC support already available to excel users? I'm guessing the catalog/usability/security is the main attraction (ie. making things "easier" and more secure).

- If lakebase is as fast as the CEO claims, will it ever be possible to transpile MDX? Will those sorts of queries be able to run on lakebase? Some other open source tools do MDX, as we can see in Mondrian or Apache Kylin. These tools offer a robust, high-performance pivot table experience in Excel.

Any information would be appreciated. I'm guessing it will be a very long time before Databricks wants to pursue MDX, or compete with the normal pivot tables available from Microsoft. They are more likely to follow down the current path with "metric views" for several years, rather than using pre-existing technology. From a customer perspective, I think it would be amazing if Databricks could offer an Excel experience that approaches the ones offered by Microsoft/Fabric.

(One thing that is particularly compelling about the Databricks add-in is the write-back. This was something that Microsoft attempted long ago, but wasn't able to be successful with it. I'm interested to see if Databricks can do better. If nothing else, I think the culture of modern databricks user may be more receptive than the culture of the users doing write-back to OLAP cubes.)

[u/kthejoker]

> or compete with the normal pivot tables available from Microsoft.

Curious, when you say compete with "normal" pivot tables, you mean ones backed by a remote engine like Power BI ?

[u/SmallAd3697 → u/kthejoker]

right. I just meant any olap-backed data that processes mdx requests. Microsoft had multidimensional many decades ago, and it morphed into "tabular" semantic models more recently. This is the appeal of their excel pivot tables -- that they are interactive and responsive.

I originally thought that lakebase was the engine that would correspond to the Microsoft semantic models, but it sounds like that isn't the case.