Tableau Prep 2026.1 features, Snowflake In-Database, Hyper as a Service + New Connectors

0:00Okay, welcome back.

0:0126.

0:021 is coming round the corner, and here we have Tableau prep features for this release

0:07This is going to cover pretty much everything in the web version and in the desktop version as well.

0:13A secret little hint here, they're both actually exactly the same thing.

0:16The one on the desktop just has a web window container, that's why it runs on a technology called Electron.

0:22You can add actually hit control plus and control minus and make it behave exactly the same way as the browser version.

0:28So that's why this is just basically the same thing

0:30So the first thing is Tableau Prep spatial calculations and joints.

0:34This is huge.

0:35Tableau Prep is just quietly sneaking up to Altrix in a way, and I love Altrix.

0:39I really I l I love the capability in Altrix.

0:42But the one thing I love more than Altrex is the interface of Tableau Prep.

0:46I just think it's one of the most beautiful interfaces for working with data anywhere.

0:50And one of the biggest challenges has just been bringing feature parity with some of those power features that people really, really love in Nortrix.

0:57Spatial analytics is one of them.

0:59So being able to do spatial calculations and joins natively inside of the product is super good.

1:03The way they've done this is they've brought the functions, so the make point, make line, buffer, distance, area, intersects, length, and outline

1:10are all here.

1:11This dovetails really nicely with the new spatial capability where you can put all of these uh spatial formats into one column so you don't have to split them out.

1:20for each type in a different column.

1:22So points, lines, and polygons can all sit in the same column, which is which is a really really nice types to have here.

1:29So users now have the flexibility to configure spatial join between two geometry data types to generate location points and regions of interest in Tableau Prep as they have in Tableau Desktop.

1:39So this was already possible in desktop.

1:41Just bringing it to Tableau Prep.

1:42I love this.

1:43This is such a good little feature.

1:45Tableau prep in database processing.

1:47Again, another little Ultrick sort of uh, you know.

1:50a safe ground in database processing, really powerful capability.

1:53Yeah, we we got it for a different database previously.

1:57I can't remember if it was Databricks.

1:59Now we have it for Snowflake.

2:00So the two big hyperscalers

2:02Entering the game, improved efficiency for flows connected to large datasets in in database processing.

2:08Users can now choose to perform operations in their Snowflake database instead of in Tableau Prep.

2:13This will make it super super fast and very nice to use.

2:16Given the tablet prep can be a bit sluggish when you have really large datasets

2:20I'd really love to see this running on a snowflake instance with a massive warehouse running behind the scenes.

2:26That would be really nice.

2:27But then I've also got to say you gotta be careful because if this is doing this on your whole entire dateset

2:32You might burn through some credits.

2:34So I still think people are going to be cashing their data sets and I still think you're going to want to make sure the sampling is set up correctly.

2:41Sampling is a capability in Tableau Prep that if you don't know how to set it up properly can really mess you up.

2:46So highly encourage you pay attention to that.

2:48Okay, Tableau Prep.

2:49Hyper as a service.

2:50Now this is interesting.

2:51The process larger prep flows more efficiently with Hyper as a service.

2:55Tableau Prep will now separate the flow processor, Minerva, and Hyper into different pods, allowing services to be scaled and deployed independently.

3:03This will make it easier to isolate faults and allocate resources effectively, resulting in far fewer flow failures due to memory constraints.

3:12Hypers as a service is generally available in tabay prep and cloud.

3:17So this is interesting.

3:20I don't know what this actually means, but what I think is happening is that they're just making the architecture of Tableau Prep on Tableau Cloud

3:28specifically tablet prep conductor run a little bit better which means that when you run out of memory or there are memory challenges it's going to fail more gracefully and still complete the jobs

3:38And by separating it out the services of FlowPress of Minerva and Hyper into different pods, essentially putting them on different compute clusters.

3:47That means there's less chance of one cluster running out of memory more easily, which these are these two are probably going to be the biggest ones.

3:53Hyper is obviously your data

3:54And the flow processor is actually think of it as like the background of four Tableau Preps.

3:58So this is kind of nice.

3:59It's also good to have the actual code name for it.

4:02It's kind of nice.

4:02I never knew that was the name, so that's kind of

4:04Kind of cool.

4:05Okay, REST API connector, we've touched on this before.

4:07Google Look at connector, we've touched on this already, SRE connector, custom ialth for OneDrive and SharePoint Online in government cloud and OAuth Cloudera for Impala

4:16We've touched on all these three.

4:18They're available in the desktop.

4:19They're also available here in uh Tableau Prep, which kind of gives you a hint that all of these connectors are now starting to use the same underlying code.

4:26So if we get something for desktop

4:28It looks like we're going to be getting it for prep at the same time.

4:30So this is really good part of the workflow.

4:33Parity between the two.

4:34So that's everything new in Tableau Prep 261.

4:38In the next video, we're going to check out

4:40Uh Tableau Pulse, yeah, that's the next one.

4:43Thanks for watching.