Saint Louis Tableau User Group 28 Sep 2026

0:01 Shawn Moore: So thanks everyone for joining us for our quarterly St. Louis Tableau User Group meeting.

0:07 This is the first, our first meetup right after Dreamforce, and there are some really exciting things listed on Dreamforce.

0:16 And we have Steve Brown here from, uh, Tableau, uh, Salesforce.

0:21 He's basically giving us our own private Dreamforce presentation. So thanks, Steve.

0:25 Steven Brown: Exactly.

0:25 Shawn Moore: Appreciate that. Yeah, so let me– I want to just go over one thing. I wanna, again, thanks everyone for attending. Thanks everyone for being a member of the St. Louis Tableau User Group.

0:36 You all are one of fifty thousand Tableau User Group members, and this is a number that we actually crossed this year.

0:43 Uh, fifty thousand, that's a big number. That's all across the world.

0:47 And so take a look at this link. Look at joining the Slack channel. We have a huge, huge Tableau, uh, community where these are all people that you can chat with, talk to, and learn from. And not only do we have the St. Louis Tableau User Group, we have other user groups such as the Higher Education User Group.

1:07 Any gr- if you could think of it, there's probably a user group from, for, I mean, for that, uh, information. So take a look at this website, look at the different communities, and just let's network and get to know people. So we're here to hear Steve talk. He's gonna give us, uh, like I said, our own personal Dreamforce presentation, and I'm gonna turn it over to you, Steve.

1:28 I'm gonna stop sharing.

1:29 Steven Brown: Awesome.

1:29 Shawn Moore: And you can take it from there.

1:31 Steven Brown: Fantastic. Well, thank you all so much for leaning in and, uh, donating your lunch hour, uh, to this. Uh, really appreciate that.

1:42 Um, and, uh, hopefully we'll, we'll make it worth your while. Uh, so my name is Steve Brown. I've been, uh, here at Tableau Salesforce for the past almost eleven years. Um, I did have the pleasure of going to Dreamforce this year.

2:00 Uh, hopefully, um, some of you or maybe some of the folks from your, from your companies or from the St. Louis TUG there have been, uh, able to, to kinda lean in and, and absorb some of that material. But I wanna bring you some of those messages, especially from the keynote, uh, bring that to you directly. I've been on this journey, as I said, about eleven years through data, AI, and analytics.

2:25 And the amount of innovation that we saw at this year's Dreamforce, particularly from Tableau, is just inspiring. Uh, hopefully you have been inspired and, uh, if you weren't able to catch some of the highlights from Dreamforce, I will highlight them for you here today.

2:45 I will go ahead and walk through some of the themes from Dreamforce, and we'll open it up to, to Q&A as well.

2:54 So I'm based, uh, here in the DC area. I'm in Old Town Alexandria, for those of you that, that know it. Um, but love, love St. Louis. Um, and I'm wearing today this shirt is, uh, I'm a fan of cycling, professional cycling. Um, I don't know if there's any other fans out there, but this was from ten, eleven years ago when the Cycling World Championships were hosted in Richmond, Virginia.

3:20 It's a massive event worldwide, not so big here in the States.

3:24 But the cycling championships this year were just yesterday, and an American, Brandon McNulty, won that for the first time. Um, well, I shouldn't say hi-his first time, but uh, it's the first time an American had won in like four decades. So, um, anyway, kinda cool.

3:43 Uh, so thank you again for, for being here. This, uh, Dreamforce, uh, Tableau Conference, this innovation, it's all about you. It's all about the innovation that we've heard from you in the, uh, in the, the DataFam and bringing that innovation to you. And really, hopefully you're seeing that, like, a lot of that innovation is coming to core Tableau, to server, to cloud, and leveraging the work that you've been doing for the past couple of decades, right?

4:20 For over twenty years, it's been folks, it's been you, it's been folks like yourselves, these DataFam members within the community, within the companies as change agents in the company, harnessing this power to see and understand and act on data.

4:36 And along this past couple of decades, as you've been building your workbooks, building your data sources, your PDSs, you've been building a trusted foundation. Like, in those data assets is a ton of metadata. It's a ton of metrics. It's a ton of, uh, meanings and descriptions and connections between data elements and data sources.

5:00 And that is the foundation that we have based a lot of the most recent innovation, uh, that we have announced at Dreamforce and are bringing to market, um, either already or right around the corner, uh, to you. You're also the experts in world-class analytics, um, and the visualizations, the insights, the actions, and we've been able to package up tho- that, uh, capability as well, embed it in the product so that no matter what surface that somebody's doing on, uh, analytics on these days, they get those best practices, uh, that you've been working on for the past, uh, twenty years.

5:39 And then probably most important and something that just doesn't go away is this idea of data culture, right? Like, the DataFam is so strong.

5:47 Um, it's so energizing going to events like Dreamforce, uh, especially Tableau Conference, and sharing these best practices with each other, um, and building that data culture in your organization. Look, we know it's not easy to wrangle the organization, whether your organization is small from just a few people to large and a few dozen, uh, thousands, tens of thousands of people, the challenge remains.

6:17 How do you build this data culture, data literacy across the organization? Well, you've been laying that foundation, and we want to help you accelerate that transformation in your organizations. That's what this year has been all about. And we want to empower you as members of the DataFam to really own these new capabilities to accelerate not just your own organization's transformation, but your own careers as well.

6:44 Because these are superpowers, and when you harness these superpowers, you can really do tremendous things, uh, for yourself.

6:52 So the mission has always been to see and understand data and to act on it, um, especially now attached to the, to the Salesforce footprint, and to do that at the speed of thought.

7:04 Now, traditionally, that's been in some Tableau surface, right, or Salesforce, uh, surface. But these days, those surfaces are multiplying. Now it's Claude, it's Slack, it's ChatGPT, it's Teams, and yes, it's still Tableau and Salesforce.

7:22 But we need to meet our users where they're at, where they work. We've talked for a long time about insights in the flow of work, but where that flow of work is happening is evolving, and evolving very quickly.

7:39 So this is all about unlocking the agentic analytics, uh, enterprise and doing that with speed and trust.

7:48 Probably a lot of you have seen in your organizations, and if you've been in analytics long enough, it kind of harkens back maybe to those days of, um, folks taking their, their data, maybe exporting it outside of the tools that you've created for them, and then people come to the meeting all with different versions of the truth.

8:08 And we see that kind of repeating itself, history repeating itself today with people maybe vibe coding their own dashboards or doing, uh, these kind of innovative things. And then you know what? They come to the, the, the meeting also with different versions of that truth because they haven't grounded it, uh, on that foundation of trust and governance.

8:30 So we want to be able to foster rapid innovation and, uh, development, but balance that with trust.

8:38 And this is the stack that does it. Um, from the bottom up, a data engine that is powered by Hyper, that extract engine that, uh, we've known and loved in Tableau for years now.

8:52 Something new on top of that, that we announced at, uh, Dreamforce is the Knowledge Engine, and this is all about increasing the accuracy of your conversational analytics. So I like to frame this up as context. It's all about context plus conversation.

9:11 We talk about context a lot in the, uh, area of AI, right? For AI agents having context. But context is really important for us, you know, for people, for humans.

9:23 And that context may come in the form of a Tableau dashboard, right, a viz, uh, maybe a Pulse metric. It may be a Slack alert or Teams alert.

9:33 But then we need to empower our users today in this age of agentics to then be able to have conversations with their data. So that context plus conversations. That context super important because humans, we have a cold start problem. You just give me a blinking cursor, and I have to build up my own context, right, uh, over time. That wastes my time.

9:55 It burns tokens. Um, so serve that up, push that context out to me, and then let me ask questions. But those conversations, those, that conversational analytics, it needs to be accurate, and that Knowledge Engine is all about driving that accuracy.

10:13 And the end goal of all of this is then to make decisions and take action. Um, and so you'll see embedded throughout this ability to go from insight then to action, whether that be in Salesforce, whether that be in Slack, whether that be through MCP out to other agents or harnessing the power of agents directly in your, uh, analytics workflow.

10:38 Every layer that you're seeing here is open, and especially there at the top, where talk about headless analytics, right? The concept of the head being where are your users actually working? As I mentioned, typically, that's been in desktop. It's been in Tableau Cloud, right? It's been in Pulse. It's been somewhere in the Tableau platform. But now through this, uh, protocol, MCP, Model Context Protocol, we're able to open that up to all the different surfaces, uh, that users are using these days.

11:12 You see some of the, the examples, uh, up there.

11:16 So that's what headless means. You can benefit from all of the power and flexibility and governance and security and trust and scalability that you've known and loved through Tableau Server, Cloud, the entire portfolio next, um, and then expose that, uh, through any surface conversationally.

11:35 And so the playbook, we've worked hard on thinking through how to, to frame this for you and your organizations.

11:43 There's three, uh, key pillars. So empower everyone to be a builder. This idea of a builder, you all have been builders for a long time, uh, now, particularly on the Tableau platform. You've been change agents in your, uh, organizations. But now the idea of builder is expanding, uh, across the organization. So we want to empower everyone to be a builder, not necessarily having to, to code, um, a- Or for that matter, even be in the VizQL interface that we, uh, know and love.

12:14 So expanding that sphere of capability even, uh, broader.

12:20 And then have… Second pillar is have intelligence come to you. So the idea of proactive notifications that bring those insights to you. You can have an army of agents working on your behalf, looking for outliers in your business, bring them to you where you can act on them, and then all of this built on a trusted foundation.

12:39 So empowering everyone to be a builder. So something we announced at Dreamforce this year is Tableau Studio.

12:48 So there are hundreds of thousands, I don't know the exact number, maybe millions of, uh, installations of, of Tableau Desktop, uh, worldwide, right? This is that original, uh, interfa- VizQL interface that just, you know, captured the, the hearts and minds of, of, uh, folks, and especially the DataFam, using this to build visualizations over the past couple of decades.

13:13 So there's a big footprint, uh, there. The idea of Tableau Studio is to take… It's a, it's a reimagined Tableau Desktop experience with AI at the center. So imagine being able to click on the little sparkle logo up in the upper left and go from a pills on shelves interface that we've known and loved for the past two decades to now just a prompt that looks like Claude or ChatGPT, and you can simply type and build, uh, the assets, run the queries, build the assets, uh, analytics, vizes, um, and then be able to share them.

13:52 And you're doing all of that on top of this trusted foundation, the trusted governed, uh, data sources that you've al-already created, the PDSes, and all of that, um, then you… It's not only secure, but you can scale it, share these assets, uh, across the company, and you're doing that with, uh, with natural language. And they have pre-built skills for doing the things that you and the DataFam do on a daily, uh, basis.

14:19 So super exciting reimagined, um, experience.

14:24 The, the, um, keynote itself is available on Salesforce Plus, the streaming, uh, video platform, where you can see a demo of Studio brought to life.

14:36 So I encourage you to go, uh, see that.

14:40 So that experience on, uh, looks like what you see on the left here. So good evening, Brock. So there we're in Tableau. We're in Tableau Desktop, now Tableau Studio, um, on, uh, on our local machine. And you can see, simply describe your task or ask your question.

15:00 And so that's the video that you would see walking through, um, exactly the capabilities there in Tableau Studio. On the right is an interface that maybe some of you are pretty familiar with. It's, uh, Claude from Anthropic. They look really similar, right? So it's this idea of just having, uh, a prompt where you can type in exactly, uh, what you're looking for.

15:24 And so on the right-hand side with that Claude experience, so the idea here with Tableau Data Apps is what I talked about earlier is fostering this innovation, this, as we've come to know it, vibe coding, right? Being able to jump into Claude, vibe code a dashboard through Tableau Data Apps. You can then bring those vibe-coded assets and attach them to your governed, trusted foundation in Tableau.

15:55 So it's literally publishing that to Tableau. So building your assets, and then again, via this MCP capability, publish those assets into Tableau. So when you're ready to scale, to share, to secure those assets that your organization's building, you can use Tableau Data Apps and this idea of publishing to Tableau to do that.

16:19 So it's this great balance between letting the organization run fast and yourselves run fast with vibe coding in your favorite platform, and then be able to… I like to think about it as planting, right? That you might, uh, do with your, with your crops. Put that in fertile so-soil, right? That being your Tableau, uh, trusted foundation to secure and scale and share that.

16:44 So super exciting, uh, capability there with Tableau, uh, Data Apps.

16:49 And the whole idea is to be able to bring innovation, um, and, and foster development in any of these surfaces, Tableau, Claude, Salesforce, Slack, ChatGPT, Teams, and publish that down to leverage all of the new capability, uh, the, the trusted foundation that you built for a couple decades, plus the new capability that we announced, like the Knowledge Engine, the Decision, uh, Engine as well.

17:19 So the second pillar, uh, of the playbook is having intelligence come to you. And so the idea here is proactive, uh, intelligence.

17:30 Now, look, again, those that have been in, uh, the analytics space, um, for a while have seen different takes on this, and this is a truly innovative way to bring this intelligence, uh, to your users wherever, whichever surface they might be in. 'Cause it's not just saying, "Hey, I'm interested in, uh, when this metric goes, you know, out of bounds," um, although that's certainly a, a capability here.

17:56 But you're actually spinning up one or more agents, AI agents, that are working in the background on your behalf, looking for trends in the metrics that are of interest to you, and then surfacing, uh, those insights to you in the flow of work, right? Again, on any surface where you can see that insight, ask questions to drill in deeper, and then take action to, uh, to correct or, or amplify any of those insights that you've received.

18:27 So a seamless way for you to kind of harness the power of AI, allow your users to harness the power of AI to be working there in the background twenty-four/seven, looking for either anomalies or interesting trends or out of bounds, uh, in the, uh, in their analytics, and then bring that, uh, to the front.

18:50 So really interesting capability, uh, there. And it's this proactive intelligence loop that the agents are doing in the background to take what you are actually, uh, looking for or the work that you're… the workflow that you're in and your, your day-to-day jobs to be done, observe, analyze, reason, and then notify you via your surface, recommend next best actions and be able to actually execute those.

19:18 So really exciting, uh, there. And then finally, Tableau Knowledge. So I mentioned this capability of, uh, needing to be super accurate in your conversational analytics, and that's what Tableau Knowledge is all about. So if we look at that stack, you know, it starts at the bottom with our data layer. So as always, Tableau is the Switzerland of data, connect to any data sources that are out there.

19:46 Then on top of that is a semantic model. And that semantic model, think of it as connecting the business terms that somebody might use when asking a question to the underlying tables and fields that exist, uh, in these various data sources. So that's, that's semantics.

20:04 And if you take an LLM and point it directly at your data, you'll tend to get about thirty percent, uh, accuracy. That's what we've seen internally here at Salesforce and Tableau. It's also what Anthropic, uh, has seen. They published a blog where they pointed Claude directly at, uh, their data sources and saw in the twenties, uh, accuracy.

20:27 When you put a semantic layer on top of that, you can get up into like the seventies percent, uh, accuracy, so much better. But to really build your trust and to drive adoption, you really need to get into kind of that ninety-plus percent accuracy, and that's what knowledge is all about.

20:46 Knowledge is super exciting because it's about making connections between the entities that exist in your data. And this starts with Tableau Cloud and Server and that metadata that I was talking about earlier. So those PDSs that you've created, those metrics, data sources that you've connected together, all the work that you've been doing in data prep, all of that is metadata that can now– that is now used to build the knowledge graph that sits on top of the semantic layer.

21:16 So all of these interconnections. And then that graph, it learns over time. It builds new node, adds new nodes based on the actual queries that are flowing through the knowledge graph.

21:31 And Tableau Knowledge itself, so there's kind of two concepts here. There's the knowledge graph behind the scenes. That's this entity, um, that exists. You see a, a image of it there. For instance, uh, if it were in Salesforce, you've got Sales Cloud and the various connections there.

21:49 Um, so it takes your initial PDSs to build that, uh, that initial copy, and then as that, the actual SQL is being generated and that graph is being used, then it learns over time. Tableau Knowledge allows human-in-the-loop maintenance of that knowledge graph. So that's the interface that we're actually seeing, is that graph that was created from your PDSs.

22:15 And that Tableau Knowledge also has an agent right alongside. So this is, you know, probably a member of the DataFam, right? Maybe a data steward type of persona that can then use an AI agent to inspect the health of the graph and to improve that over time.

22:35 And so this is key. This knowledge layer is key then to getting into that kinda ninety, uh, percent-plus, uh, level of accuracy.

22:45 So super exciting there. So what ha- then happens throughout the whole stack is, let's say you're working in Claude. Well, an, a user might ty-type a analytic question in Claude via Tableau MCP that comes through knowledge and semantics, hits your data, and returns those governed, accurate, trusted numbers then to Claude to continue the conversation with your users.

23:12 And through each layer of that stack, um, is Tableau value at every layer, right? Starting from the bottom with the data foundation, again, that Switzerland of data being able to tie into, into a-any data source, uh, across, uh, the company and bring those data sources together here at the app layer, if you will, and analytics.

23:35 Hyper acceleration with that Hyper engine, uh, that's powered Tableau as- uh, extracts for years. So this fast real-time access, uh, to data at the speed of thought, powered by Hyper. Now, knowledge and semantics on top of that to drive conversational accuracy in our, uh, conversational analytics, and then bring that out to any of the surfaces via that Model Context Protocol, MCP, which I understand you've been able to get, uh, a bit hands-on, um, maybe previously, and I think there's gonna be a future TUG around that as well.

24:12 So getting hands-on with these tools, and literally tools, tools within MCP that you have access to, uh, is very exciting, and there's new tools that are coming out, um, uh, over the coming weeks and months, uh, from Tableau as well.

24:31 And so, uh, just walking through, uh, in talking about Tableau Knowledge, like this is the, the, the Tableau user group, so I wanna be, uh, transparent and let you know it's kind of a phased, um, phased release of activating Tableau Knowledge. So in its first phase, it's gonna take advantage of your Tableau assets that exist in Server and Cloud. So those PDSs, those metric definitions, all that metadata that you have in Tableau will be used to jumpstart that knowledge graph.

25:02 That's going to learn over time, uh, in server and cloud. And then in phase two, now you can start taking Tableau knowledge and putting it directly against, uh, other data sources. So in phase one, you can always ingest those data sources into Tableau, that becomes your Tableau metadata that exists in phase one. In phase two, Tableau knowledge going directly against those data sources like Snowflake, Databricks, uh, Google BigQuery and others.

25:30 And then in phase three and out- uh, lying years, being able to bring in semantic contacts and unstructured data from other tools to layer into the knowledge graph, that may contain things like business, uh, rules that you have. Maybe it's, uh… Maybe you're in finance and you have, uh, compensation, you know, analytics that you're doing, and you can layer in your sales compensation documents, um, into the knowledge graph, and that serves as, uh, as additional unstructured data that gets turned into, uh, insights that the knowledge graph can then use to generate the most accurate SQL.

26:10 So that phase three is all about being able to pull that data, not just from uploaded PDFs that you can do in phase one, but actually tapping into these sources of unstructured data across your organization. Again, to build that knowledge graph.

26:24 You of course can do today querying those data sources, but specifically to build that knowledge graph and that metadata, uh, around the data. That's what I'm talking about in phase three there.

26:37 So that's the playbook. Empower everyone to be a builder with Tableau Studio, the reimagined desktop, Tableau data apps, vibe coding anywhere, and planting that or publishing that in Tableau. Have intelligence come to you with proactive intelligence, and then that trusted foundation that, of accuracy and governance and trust in, uh, in Tableau knowledge.

27:02 And this is working. Um, this is working with customers of all sizes in all industries.

27:10 Um, and we are super excited, uh, to, to bring this to you, bring it to you in phases. A lot of this innovation, uh, is new, but you can see from some of the dates throughout the presentation, it is either here or right around the corner for you to take advantage of.

27:29 So with that, um, that's the end of what I prepared. Um, I've got a couple things I could, uh, show or open it up to questions.

27:41 Um, I'll kind of let Shawn maybe, uh, let you drive at this point.

27:47 Shawn Moore: Okay. So le- let's open it up to questions. Um, let me know if you can see the Q&A box. You can type your question there, and either Steve can read it off, I'll read it off. Or I can, uh-

28:00 Steven Brown: I see the chat.

28:01 Shawn Moore: Okay, you see it? Okay.

28:02 Steven Brown: Yeah.

28:03 Shawn Moore: So-

28:03 Steven Brown: And I see this first question about the agentic analytics features available in Tableau Pub- uh, Public. Um, and that is a great question that I do not know the answer to about what's going to be, uh, available when. So let me, uh, take that as an action item, and I can get back to the group, uh, on that.

28:27 Shawn Moore: Okay. Thanks Raj Rajesh for the question there.

28:31 Uh, do we have any more questions out there?

28:35 And, and if you're comfortable talking, I'll make you a presenter or you can type it.

28:39 I have some questions, Steve, but

28:44 But I, I might, uh, I want to give folks, other folks the ques- chance to ask the questions.

28:51 Steven Brown: Or what do people think? Is this, uh, is it exciting? Is it stuff that you can see being useful in your organization?

28:59 Um,

29:03 because this is, this is all innovation for you. These are requests that have come from the community, and they're for the community.

29:10 Shawn Moore: Yeah. One more question just came in from Jeff.

29:13 Steven Brown: Yeah.

29:14 Is this for active data analysts or for all? Uh, does it take away from a data analyst job?

29:20 I think there's never been a more exciting time to be in analytics. Um, so these, these are tools both for you and for end users. So when I, um, if we look across, you know, sort of this most recent innovation, take something like, like Tableau Knowledge, right? Tableau Knowledge is all about building that foundation of, um, of, of trust and, and scale for your analytics users in your organization.

29:50 So Tableau Knowledge is going to take advantage of your core skill sets around metrics in Tableau, data sources, vizs, um, all of that capability that you've been, uh, uh, the, the drivers of for the past couple of decades.

30:06 And now you're able to add this new layer on top of that in Tableau Knowledge. So your knowledge of PDSs and these connections is going to empower you straight away. If I go over here, in fact, um, here I am in Tableau Cloud. You can see right here on left-hand side, Tableau Knowledge is just built right into this Tableau, uh, cloud or, um, or server experience.

30:36 So when I click on Tableau Knowledge, now you have access to all of that graph, uh, capability. So if I come in here to manage graphs, I've got a, a graph right here.

30:48 When you first sit down and you're the data analyst and data steward, now you're going to see in the same way you might have seen in Prep Builder, you know, making all these connections. Now, this knowledge graph will have been built from PDSs across your organization with all of these connections between these nodes, um, and the- This is going to be something that you're gonna be very much in the loop of.

31:15 So your skill set becomes expanded. This is now you on, you know, with, with superpowers to be able to enable accurate conversational, uh, experiences for your users. And you're gonna use AI yourself alongside your day job, right? To actually take a look at the graph and check the graph health and suggest improvements. So you're gonna be able to do this job even faster and more accurate with the help of AI right alongside you that's taking a look at, all right, how are my connections to the different, uh, data sources, uh, doing?

31:57 What are actionable improvements?

31:59 Missing field descriptions. You know, let's be honest, I bet a bunch of you out there have missing field descriptions metadata in your data sources. Well, now in this world of AI, where now we have AI agents coming in and looking at these graphs to see, okay, what data do I have access to and what can I do with it, those descriptions become really important.

32:21 And so you can evaluate where you're missing descriptions and being able to fill those descriptions in.

32:28 And you can come in here and add business preferences. Um, so business rules that exist in your organization to inform the AI to drive more accurate conversations.

32:41 So you can see how a tool like this now becomes a complement to everything that you're familiar with in Tableau in order to drive this, uh, this accuracy for analytics.

32:52 On the other end of the spectrum, though, you're trying to make it super easy for your end users to be able to, yes, ask their own questions via conversational analytics. So that's that context plus conversation that I was talking about earlier. That context with, driven by dashboards and vizs and, and in the flow of work. And then, yeah, allow your users to ask their own questions.

33:17 And when you do this right, you as the DataFam, the power of analytics just gets amplified, and you can do more across your organization and drive the kinds of experiences that probably you're being asked to drive, uh, from the top. I know when I work with a lot of, uh, companies. I'll sh- I'll show you one, one more thing along these lines. Um, so here I am in Claude Desktop, and I bet a lot of you see in your own, uh, in your organizations these days an experience like this.

33:53 "Hey, I'm prepping for a board meeting tomorrow. Um, I need a dashboard in the next 15 minutes. Here are the latest CSV files that I just, you know, uh, exported. Um, can you build me this dashboard?" And I'm gonna show you here, uh, in a moment what this looks like, but I'm also gonna put in a, a second prompt here, which is I'm gonna come up here and add in, uh…

34:22 Well, let's see.

34:28 I did not have my Tableau connector in here.

34:34 Anyway, um, I'll go back to, uh, back to here. So when, with that first prompt about asking to, uh, to build a dashboard, which I'm sure you're seeing in your organizations now, Claude goes through and says, "Yeah, I'll build you a dashboard, and it's gonna be this beautiful, interactive, you know, React, uh, dashboard that's got all the numbers." The issue is these numbers are wrong, right?

35:00 And you as the DataFam, your job is more important than not ever to make sure these numbers are trusted. Because when we do this prompt, this second prompt of, hey, now that you have Tableau MCP, this is you in the loop.

35:15 Now compare the numbers that you just did through that vibe-coded dashboard to now what you can do with this MCP connection.

35:24 And if I scroll down to kind of the punchline, it says, "Hey, guess what? Your forecast commit is wrong for every region.

35:31 EMEA is overstated by a ton," right? The, the data is not accurate.

35:37 This is more than ever what your job is now is to make sure these numbers are accurate regardless of what surface your users are coming in through.

35:47 Shawn Moore: Yeah. A-and Steve, I, I wanna add something to it. Um, I think you said it, you said it perfectly. This is our assistant that can save us some time and get us started, right? Because as analysts, we still need to do some data storytelling, right? We know the context of what's being built. We know the audience.

36:09 We know what to focus on, what to focus the audience's attention on when building these dashboards, right?

36:15 But what the AI can do, you know, once we get those things in order, AI can allow those users to dig down deeper and a-ask those questions of their data, right?

36:25 Um, and it can al-

36:27 Steven Brown: Yeah.

36:27 Shawn Moore: It can help us get started. So the data storytelling part, like when, when Steve showed that dashboard where he had to question the numbers and validate the numbers, as a analyst, we still need to look at that dashboard and say, "Is this the right context? Is this the, what the audience want to see?" Because there's, there's certain things that go into when we build a dashboard, right?

36:50 Upper management might not want to see the same thing as the analyst. There are things that we want to stress. Sometimes the dashboard has a point that we want to get out and prove, right?

37:00 And those things, to me, in my opinion, come from us as the analyst.

37:06 And as we explore that data, right, it allows us to ask better questions of AI and spit out a, a dashboard that can save us time.

37:15 Steven Brown: Exactly right.

37:16 Shawn Moore: Yep. So.

37:18 All right. So Tammy did that. Oh, you said thank you. Hopefully that answered your question.

37:22 Steven Brown: Yeah. Thanks for the question.

37:24 Yeah.

37:24 Shawn Moore: Yeah. Uh, any other questions out there?

37:30 So see, if I wanted to find out more information, I saw on very first slide you mentioned data culture. Where can I go to find, read up on this stuff, and maybe just learn-

37:41 Steven Brown: Yeah

37:41 Shawn Moore: … more about it, take it back to my organization? I think data culture for me is a big part of it too, 'cause we're getting our, our audience, our, our business folks, getting them acclimated also to a new way of doing things. Just like-

37:55 Steven Brown: Yeah

37:55 Shawn Moore: … the new way of us to do things, right?

37:59 Steven Brown: Yeah.

38:00 So I think, you know, two steps there. Uh, first is understand these new capabilities and-

38:05 Shawn Moore: Okay

38:05 Steven Brown: … what we've announced. We, this is a, this is a lot of innovation. A lot of innovation coming-

38:09 Shawn Moore: Yes, it is

38:09 Steven Brown: … very fast, right? I mean, um, it's, it's incredible to see, but it's al- it can be a lot to get your, get your arms around. Good thing is this is incremental, uh, innovation, right? This is building on that foundation of trust, uh, that you've already built. But, uh, on Salesforce+ uh, that I mentioned, that, uh, streaming platform, you can just search for, uh, Tableau keynote, Dreamforce '26 Tableau keynote, um, on Salesforce+ and that will give you access not just to that keynote, but there are several sessions up there on Salesforce+ that are, uh, digging in, uh, even deeper.

38:48 Um, then the other part is about really, you know, driving this home in your organization with best practices, building the data culture, right? You know, how the, the innovation is wonderful, how to actually make it have impact in your organization is, is kind of the, the next step. Um, and that, uh, you know, for that, what I, uh, suggest, there's great resources, um, out there on Tableau's website, you know, in terms of, uh, the, the process to go through.

39:21 Um, and some of that is, uh, now accelerated with, uh, this latest innovation that we've, uh, added. But probably the, the best thing is coming to, um, to sessions like this and like the next one, and I think the previous one too, where you're actually getting hands-on to sort of demystify this so you understand these new capabilities and how you're going to be able to put it in the hands of your users.

39:48 Um, you need this, this innovation, this idea, for instance, of vibe coding dashboards, like it's happening. It's happening in your organizations, I'm sure it's happening around you. So you need to be up to speed on this innovation, uh, to know how to connect this innovation to what your users are already starting to do. And these themes around being able to trust it and govern it.

40:14 I mean, it's the same themes we've been talking about for a while, but now these tools kind of take a different shape. So I think your familiarity with the capabilities themselves will then let you, um, uh, uh, you know, figure out, work out the best way to actually layer this into your organization. And we can, I can follow up, uh, Shawn, with you with resources that you can get out to this group as well.

40:40 Shawn Moore: Okay. That'd be really helpful. Yep. And, and, uh, something else I noticed, this innovation is coming to Tableau Server as well as Tableau Cloud.

40:50 Steven Brown: That's right.

40:50 Shawn Moore: Which is great.

40:52 Steven Brown: Yes.

40:52 Shawn Moore: It's really great, right?

40:53 Steven Brown: Yeah.

40:53 Shawn Moore: And we, we can't stress that enough.

40:55 Steven Brown: Yeah.

40:55 Shawn Moore: That investment is still happening in Tableau Server.

40:58 Steven Brown: Yeah. And it, and it's coming there first. Um-

41:01 Shawn Moore: Yes

41:02 Steven Brown: … and it's, which, which is exciting, uh, for all of us, you know, that have been on this journey for a while. And that's because of all of this rich foundation that al- already exists there, right? So that's why server and cloud is really that, that firm foundation. And of course, the innovation, uh, comes to Tableau Next, uh, and the Salesforce world as well.

41:24 But, um, yeah, like the first out of the gates is server and cloud.

41:29 Shawn Moore: Yes. Yeah.

41:31 And, um, oh, Tableau Studio, a reimagined Tableau Desktop.

41:36 Steven Brown: Yes. Exactly.

41:38 Shawn Moore: That was good news. I can't wait to see it.

41:39 Steven Brown: And, and it's, it's, um, this kind of experience, it's really, you know, when you get hands-on with it, you'll just love it because you can be in your familiar desktop experience. That's gonna get kind of a, a look and feel, uh, refresh. You know, just a kind of a more modern, uh, look and feel, but it's gonna be the same pills and shelves and, and experience that you've had, had with p- sheets and, uh, and, uh, you know, workbooks.

42:07 And, but then you'll click on that sparkle in the upper left and it just, the whole experience will transform into, and simplify into just a text box, and you'll just type in your request and be able to build from there. And you can go back and forth between the two. You'll see this in the, if you do have a chance to look at the, the keynote demo, you'll see an authoring experience in Tableau Studio.

42:31 Uh, and then there's a, now I, now I want to edit it, and you click on that, and the interface just switches to that familiar VizQL interface with, uh, with drag and drop. Um, so you don't sacrifice anything, you just accelerate.

42:46 Shawn Moore: Cool. Thank you. So does anyone else have any questions?

42:52 All right. So I think Steve did mention it. So we are planning our next Tableau user group. It's gonna be in November, the beginning of November. We have not sent the invite out yet. It's gonna be a hands-on lab working with Tableau MCP and, uh, Tableau Cloud and, and some other things, right?

43:15 Uh, and it's gonna be hands-on, it's gonna be live. It's, it's gonna be around this same time. It's gonna be a lunch and learn here in St. Louis, and we're gonna try to do, uh, a virtual- A virtual event too. We're gonna do a hybrid approach. So please keep a lookout for the invite. Either we'll get it out this week or early next week, and I'm looking forward, we are looking forward to seeing everyone as we continue this journey and, and learning and working with this, uh, new technology.

43:45 All this, not new technology, but a better way to say it.

43:49 Steven Brown: And you-

43:49 Shawn Moore: As we move forward on this journey

43:51 Steven Brown: … and you're innovating in how you're bringing it to the TUG.

43:53 Shawn Moore: Yes.

43:54 Steven Brown: I love it. Um-

43:54 Shawn Moore: Exactly.

43:55 Steven Brown: It's great with the, the hybrid model.

43:58 Shawn Moore: So Steve, can you do me a- I wanna give some swag away.

44:03 A couple gift certificates, um, to the Tableau store.

44:07 And I think I've seen a couple of people we've already given them to. You wanna pick a couple names, and, and, uh, we'll go from there. And if, if you've received one already, I'll let Steve know. I don't know the best way to do it, so.

44:24 Steven Brown: Well, uh, I don't know, Tamala, she asked a question. How about Raj and Tamala for asking the questions? If they haven't received one already.

44:33 Shawn Moore: Oh. T- Tamala did.

44:35 Steven Brown: Oh.

44:36 Shawn Moore: Raj, if you don't mind, you can shoot me an email and I'll get you, uh, a certificate. I mean, a Tableau store gift certificate.

44:45 Um-

44:45 Steven Brown: And then, uh, I'll just go with the order that I see. How about Brianna Johnson?

44:53 Shawn Moore: Oh, she received one too. Sorry, Brianna.

44:55 Steven Brown: Then next is, uh, Stephanie Hunt.

44:58 Shawn Moore: Stephanie Hunt. Okay. All right. So Stephanie and Raj, if you guys can shoot me an email.

45:04 SW, I'm gonna put my email address in here, swmoore1@Gmail.com, and I'll hook up with you guys and I'll send you, um, a Tableau gift certificate to the Tableau store.

45:22 Steven Brown: Awesome.

45:24 Shawn Moore: All right. So thanks, Steve. I really do appreciate it. Um, great c- a great conversation.

45:30 Thanks everyone again for attending, and we look forward to talking to you guys next time.

45:35 Steven Brown: Thank you all.

45:35 Shawn Moore: And all people, watch out for your email. All right. Thank you.

45:37 Steven Brown: And thank you, Shawn. Appreciate it.

45:39 Shawn Moore: You're welcome. Bye-bye.

45:40 Steven Brown: Bye.