Building a data culture with datafluencers

0:01 Chris McClellan: So welcome to Team DataFam Tableau User Group meeting number 85. This TUG aims to record all the in-person and unrecorded presentations to give them a wider audience.

0:12 Um, I don't mind where you've presented before. I don't care if you've never presented before.

0:17 Um, we'll find a slot. Let me know. My email is team.DataFam@Gmail.com, and we'll find something that fits you and me, and hopefully everyone else.

0:28 But today we've got a repeat from TC '26, Fi and Sarah, I think everyone knows Fi and Sarah, but officially Fi Crocker and Sarah Burnett are talking about building a data culture with datafluencers.

0:42 Um, they're the experts, so I'll hand it over to you guys and you can take it from here.

0:47 Fi Crocker: He did so good at saying datafluencer. I'm proud.

0:50 Chris McClellan: It was practicing it for weeks.

0:51 Sarah Burnett: I'm probably going to fuck it up all the way through now.

0:54 Fi Crocker: All the way through.

0:55 Sarah Burnett: All the way through.

0:59 Okay, let's get into it.

1:02 So we've spent decades inside some of the world's largest organizations, and what we've found as the single biggest problem i- it's not bad data, it isn't even bad analysis, and it's not even incompetent leaders. Although sometimes-

1:20 Fi Crocker: Sometimes I wonder.

1:24 Sarah Burnett: It's brilliant work that disappears, and today with building a data cultural datafluences, we're gonna fix that.

1:33 Fi Crocker: So I'm Fi, and that's Sarah, and we are co-founders of DubDubData, uh, Tableau partner and consultancy. We're both Tableau ambassadors, and between us we've spent decades doing exactly what you data professionals do. We build dashboards, we run analysis, and we've also led digital transformations on some of the world's largest organizations. And the projects that we've worked on have delivered more than $100 million in Australian dollars of ROI, and we mi-…

2:07 We know what makes data work, and we're gonna share it with you today.

2:11 Sarah Burnett: So we're gonna cover these three things. One, why your work is invisible. You know, the work's great, but the story is completely missing. Two, how to fix it and why it's on you and not your manager.

2:25 And then three, the tools to do it now. So a framework, a format, a channel, and the only thing in the way after this is you.

2:37 And as a special bonus, if you stick around till the end, we'll share access to our free training course on everything that we're covering today and a lot more in more detail.

2:49 So pretty exciting.

2:51 Fi Crocker: So let's crack on and explore why your work is invisible.

2:57 Sarah Burnett: Hands up if this sounds familiar: you built the dashboard, the training's delivered, the stakeholders told you they love it, and six months later there's no adoption, nothing's shifted.

3:11 Yeah?

3:12 Fi Crocker: Yeah. Thanks Andy.

3:15 Thanks Anne.

3:17 Sarah Burnett: It's not bad luck. So what we find is, it's the gap between the delivery and the adoption, and most data people weren't taught how to close this gap.

3:30 Fi Crocker: So why do you think that great wor- great data work goes unseen?

3:34 Well, it comes down to these three things.

3:37 Take a moment, read them, and think about which ones are missing for you.

3:45 If you fix the ones that are missing, everything will change.

3:52 Sarah Burnett: So now you know why, let's talk about how.

3:58 Fi Crocker: So who fixes this?

4:00 It's you, the data fluencer.

4:03 Not your manager or your senior leader.

4:06 You know your manager is across 100 different things.

4:10 Meanwhile, your senior leader's in the boardroom justifying data investment.

4:16 I can guarantee you they do want to celebrate your work, but only if you make it easy, and the datafluencer, they make it easy. They share the win, they tell the story. They make their work visible, and not because it's their job title, it's because it's their behavior.

4:35 They help the leaders to amplify.

4:39 Sorry about the scary, uh, picture. Uh, we, we have tormented a few people, uh, with it as well.

4:49 Sarah Burnett: Be careful what you ask AI to do.

4:52 Fi Crocker: Yeah.

4:55 Sarah Burnett: So what does a datafluencer actually need? We believe it's these five things.

5:01 First, a delivered piece of work with a result that's worth sharing. You've probably already got that already, we'd hope.

5:10 Second is manager sign off on both the initial channel set up and then every story that goes out. It's important to really bring them along for the ride and get their buy-in. So we don't want to blindside- side them here. Third, a channel to share it, one that's public, discoverable and set up properly. This is the foundation of how you become seen, heard and promoted.

5:37 Fourth is a story framework with a variety of ways to share to keep your audience engaged. And fifth, people to amplify.

5:48 Leaders and stakeholders to promote the success. You do the work and they carry the story further.

5:56 Get these five things in place and nothing is standing in your way

6:02 Fi Crocker: So now you know how to make it visible, here are the tools to do it this week

6:07 Sarah Burnett: Datafluencers follow an easy framework to share and engage with people. They measure impact, tell stories, post collateral, build engaged channels, and support leaders to amplify work so they are seen, heard, and promoted.

6:28 Today we'll talk you through the seven-part data story arc in detail with an example on how to build and grow a winning channel and how to get support from leaders to amplify.

6:44 Fi Crocker: But before we get into fresh… f- the framework I want you to meet Fresh Mart. It's a fictional wholesale food chain with a very real problem. Kirk owns operations at Fresh Mart where waste is consistently over target and he doesn't know why. The dashboard exists, the data's there, and his team are capable, and still nothing is shifting.

7:08 He comes to me, I'm Fi, the supply chain analyst, and Kirk shares why he's getting pressure from above.

7:17 He needs a way to reduce the waste so that it's closer to target and he meets his KPIs.

7:24 To kick off the job our reviewed our order model end data quality, and thankfully everything was okay.

7:32 They had the data, so why wasn't anything changing?

7:36 I shifted to observation.

7:38 How were the store managers using the data? And that's when I discovered the problem.

7:44 You'll learn more soon.

7:47 Sarah Burnett: A key part of people understanding the value of data is hitting the mark with a story.

7:54 Every data story arc has seven parts. Let's explore the framework and then we'll walk you through how we leverage this for Fresh Mart.

8:04 One, the hook. Your biggest most striking result.

8:08 Its only job is to make someone stop and think.

8:13 Two, the problem. What was broken? What wasn't working?

8:17 Set the tension because if there's no problem there's no story.

8:23 Three, the insight. The turning point, the thing that reframed everything. This is your aha moment.

8:33 Four, the solution.

8:35 One change, one decision.

8:38 Resist the urge to list everything. The simpler it sounds, the more impressive it is.

8:45 Five, I knew I shouldn't have counted these.

8:49 Fi Crocker: . There isn't five.

8:52 Sarah Burnett: The result before and after, the proof. Don't cushion the numbers just let them land.

9:00 Six, the learning, the transferrable line, the thing that someone reads and sends to their own team.

9:09 And then seven, the call to action.

9:13 One clear door to walk through. Give people one thing to do next.

9:19 Fi Crocker: So that's a lot to take in but let me bring this to life with the Fresh Mart example. What you see here is what we call a carousel that has small images to catch peoples attention on your Slack or Teams Channel and get them engaged.

9:35 Our hook, 2.4 tons of fresh produce saved from waste.

9:41 One quarter, one dashboard change, no new tooling, no model rebuild.

9:46 This is what stops the scroll on your internal channels.

9:52 The problem, while the dashboard was accurate and waste was still climbing all the data was there; sell-through rates, forecast variance, safety buffer levels, even regional breakdowns yet we were still above target, well above target at 6.3% versus 5%.

10:12 Here's where things get interesting, the insight.

10:15 Everyone was right partially. Store manages were ordering responsibly, the model was slightly over buffering, but what was discovered with the store managers th- was that they needed the same data but a different view, and they needed it upfront not tucked away over multiple tabs.

10:34 The gap was visibility and not performance.

10:40 So our solution was to reframe the first tab of the dashboard from how did we perform to what becomes waste if nothing changes.

10:49 The first thing that managers now see is the projected surplus volume dollar impact and days to expiry of the fresh food. The result, waste dropped from 6.3% to 5.1%, in six weeks, and that was a $672,000 US Dollar annual cost.

11:12 The learning, the data was always there, but what changed was how we framed the decision and we made peoples actions easy.

11:20 And the call to action, get your win.

11:25 This makes the reader on the channel feel like they could get results too. If your dashboards are accurate but nothing is changing reach out.

11:36 That's bringing people back into your team, back into the journey with the seven-part data story arc.

11:43 And don't forget, this is all covered in detail in our free training course, even that Canva template.

11:51 Sarah Burnett: So you've got your story, now where does it live?

11:54 This is it in practice, a public channel, a Data Wins Carousel built to stop the scroll.

12:02 But the post is only part of it, the culture is what makes it compound

12:09 Fi Crocker: And I know this because building strategy and data culture used to be my job. At JLL, I built a Teams channel that became the highest subscribed technology channel in the entire organization.

12:21 Second only to the all-hands channel and that one was compulsory for people to belong to. We had over 700 people in our channel, and it was a team of only 150 people, so you do the maths.

12:34 We invited people in, uh, and added them, but as the momen- momentum grew, people actually joined through discovery, and the best moments were when people outside of the sta- team stopped lurking and started talking. They got involved. They celebrated wins, and they elevated people. That doesn't happen by accident. It's happening because you build a place that people actually want to be.

13:00 You open the doors to your teams channel or your Slack channel, and you make it public.

13:06 You have a strategy with ways of working. You invite your own team to start with, and the leaders, and then stakeholders, but it's not a one and done. You have to keep nurturing that channel and keep, keep up with the invites as the stakeholder base grows and your work grows as well. Make sure you s- do little things like saying hi when people join, and celebrating everyone's wins.

13:32 This channel is the foundation, but the culture is what fills it.

13:38 Sarah Burnett: Amplification is the part most people skip, and that's the real… where the real impact happens.

13:46 If you post but you don't stop there, you make it effortless for your manager to amplify. A caption written, a message sent, one click. They commit, they tag, and they take it higher.

14:00 Then you prompt them to nudge a senior leader. A comment on a thread, a mention in an all hands. However they show up, it compounds. And don't forget the person who asked for the work in the first place. They add a lot of credibility with the reinforcement because they've lived the result.

14:21 Fi Crocker: Now we started today with the truth.

14:23 The best day to work on this call or watching this video will never been seen, and not because it isn't good enough, but it's because nobody told the story.

14:38 Nobody told the story, but now you will.

14:41 You have a seven-part data story arc that turns any result into something worth sharing, a channel that outlives the project, and an amplification stack that takes your story all the way to the top.

14:53 And from today, the right people will know your name, and that's what seen, heard, and promoted actually means.

15:04 Sarah Burnett: We've touched on some key concepts today, and there's so much more to go deeper on which is why we've built a course, The Datafluencer Toolkit, and it goes end to end on everything a datafluencer does. The seven-part data story arc, the channel, the amplification stack, and everything in between. It's free, and there's no catch, and it's pretty easy to get through.

15:27 So if you get your phones out and take a photo of the slide and register for The Data Fluencer Toolkit, and you can also subscribe to our Undubbed podcast where we keep the conversation going. And connect with us both on LinkedIn while you're here. We'd love to hear how your story lands.

15:45 Fi Crocker: Stop waiting to be noticed, and start making it impossible to be ignored.

15:53 Sarah Burnett: That's a wrap. Yay.

15:55 Fi Crocker: Thanks for coming on the TUG today. Uh, we're open for questions. Andy, did you wanna ask your question? It might be easier.

16:03 Andy Holt: Sure, yeah. No worries. Um, thanks for fitting me in Sarah, really great. Um, I just was wondering, you know, what have you both learnt about how to implement these ideas in the consultancy, consultancy space rather than in-house?'Cause I guess it kind of differs. I'm just interested in your pro- um, your thoughts on that.

16:20 Sarah Burnett: So are you meaning, like, within your consultancy?

16:23 Andy Holt: No, no. I think in terms of when you're working with clients.

16:27 Fi Crocker: For us it depends on the size of the client obviously. So we… Sometimes we work with tiny clients that have just got a couple of Tableau licenses, uh, and so they're working more with their board and trying to get board papers out. Um, so it's really about choose- choosing the right audience. Uh, other clients that are much larger, you know, got a footprint of 1,500 plus, we start to introduce as we're developing the things that are important for adoption such as change management et cetera.

16:59 And so this channel is part of what we would say is a great change program.

17:04 Uh, and so you know, making sure that we're bringing in champions to start with, um, building up that culture, talking about beta programs, and then introducing this as a… We, we give them access. You know, we've got this course on how to, how to build your own, um, data culture and make sure that you're, um, promoting the success of your data teams.

17:30 I think anyone that's working in data right now would agree with there's a lot of roles that are being lost out in the data land at the moment, and I feel like it's because we don't do a great job of promoting, um, what we actually do. So it's about coaching and nurturing people through that, and having a free course is a good way to go. I mean, your clients are welcome to use the free course as well.

17:53 Like, it's all o-… It's totally open. You can use it. You can download the con- you know, the content and everything. It's fine.

18:00 Sarah Burnett: Yeah. And I'll just say additional to that Andy, you know, when we've built them internally in large organizations, they've kinda been our babies, and we've been able to nurture them and grow them and, and you know, have, have certain, um, you know, stakeholders prompted and things like that. When you're building it for a client, when you're not there, you know, it's someone else's responsibility, so it's really about going the extra mile and getting the right people in that are going to grow it when you're not around

18:30 Andy Holt: Great. Thank you. That's really helpful

18:32 Sarah Burnett: Uh, any other questions for us?

18:37 Chris McClellan: I think that's sometimes a challenge, isn't it? Being a consultant is trying to actually instill into the employees or the company that they're, they're the data champion if you like.

18:48 You know, even though the dashboard might have been built for them, but it's important for them to champion the dashboard internally.

18:53 Sarah Burnett: Mm.

18:55 Fi Crocker: Yeah, for sure.

18:57 Um, but you know I, I really do believe it's a, a great way to protect your own position in an organization. And I, I know it feels uncomfortable to promote yourself and to promote the work that you're doing. The good thing about the course is it, it's got all of the prompts, everything that you need to do to help you to build this really quickly.

19:20 It's not like it's gonna take you a long time. Um, but you can choose your LLM of choice and just use it as a c- as a sparring partner to build the data story out, get everything ready so it's much, much faster for you to get through once you've got the right sort of frameworks in place. And things like our Canva template you can put into your own brand.

19:41 Um, and you can do that all free of charge. You don't need a paid Canva account to do that as well. Um, so trying to do these things in a way that it looks pretty, um, that it makes sense, and that it's easy for you to do.

19:55 Uh, the, the leaders I find are so time poor that it's really difficult for them to go in and really sell what you've done, and promote it, and promote the, the return on investment. But if you've done the legwork behind it, they'll see you as a champion 'cause anything that you do makes them look… Th- you know, any great things that you do makes them look good as well as part of their team and, and it just, you know, it, it builds momentum.

20:26 Sarah Burnett: Yeah. And you never really know who's out there listening as well. If… Particularly if you make the channel quite open. You know, y- quite often in big organizations you're working in silos and, you know, if your team's on the chopping block or whatever's happening, there might be another department that's really interested in your skillset, and this is a way of sharing it.

20:47 Fi Crocker: Yeah.

20:48 Chris McClellan: Yeah, definitely. Stopping the scroll as you said as well. Just getting people to actually stop and focus even for a little bit of time just to see.

20:57 Fi Crocker: Yeah.

20:58 Chris McClellan: Any more questions at all?

21:01 No? That's okay because then-

21:02 Sarah Burnett: Is everyone kind of doing an element of this, like in their roles actively?

21:09 Ann Stolzman: I was when we were a Tableau house. Um, now that we're a Databricks house it's, uh, that culture seems to have died off a little bit.

21:19 Um, because you've got more people, uh, who are using things like Genie and AI to try and build dashboards, and they're kinda siloing it instead of sharing it.

21:32 So-

21:33 Sarah Burnett: Hmm

21:33 Ann Stolzman: … I, I am trying to get people to come back to the analyst because some of the stuff that is being built isn't being built on trusted sources, isn't being built, uh, correctly, let's put it that way. Um, th- it, it's AI slop. Um, and, and I'm trying to get people to get back into that environment of having those trusted channels and having those discussions again.

22:04 Chris McClellan: Yeah. More, more of a data culture type fit as well maybe.

22:08 Ann Stolzman: Yeah. I mean we're, we're very data centric at Rivian. It's just a matter of trying to get people back into that everybody is talking about the same thing instead of seven different people have built variations of their own dashboards on quote unquote "the same data".

22:27 Chris McClellan: Mm-hmm.

22:28 Ann Stolzman: And they're all different, and they may not necessarily be accurate.

22:33 Chris McClellan: It's always a challenge.

22:33 Sarah Burnett: And I wonder if in that model it's, it's kind of harder maybe to share because it might spark more debates than, um, credit.

22:43 Ann Stolzman: Both are true.

22:48 Byron Walton: I hope you can hear me. Th- this is Byron Walton, uh, Cincinnati. Yeah. We're working on a l- literacy project right now and really… A- and I work for the University of Cincinnati.

23:01 Um, and we're really trying to paint a picture of why we need more of a governance body when it comes to data, uh, because we do have a lot of rogue, uh, dashboards as I call them.

23:21 Um, I'm not gonna call them Temu dashboards. I'm just gonna say, you know, they are where they are, right? Now so, so we're trying to get to a point where we can get it more centralized, um, with our eyes on them so that we can, um, be able to test for validity and, uh, so, so that's where, so, so that's where we are. And so that's why today, and I, I feel th- this is very helpful to be able to paint the picture, not re- necessarily solving our problem, but to be able to paint a picture just with facts and stating this is why we need to go in this direction.

24:01 Fi Crocker: Yeah. I think, um, it's a really interesting point in time that we have at the moment with the proliferation of AI and the ability for people to do and build or go rogue, uh, with their Temu dashboards. Uh, but I belie- m- m- it's my belief that at some point things are gonna come crashing down because there's gonna be some really poor decisions that are made.

24:27 And they may, may be on a really grand scale. It may be in a bank, you know, that impacts a lot of people's finan- financial wellbeing or, you know. It, it will certainly be in a space That is on such a grand scale that people will sit up and take notice. So I, I agree, Byron, I think it's really important to have a set of standardized dashboards, but I also am of the opinion that I like people to be able to self-serve as well and to do the analysis.

24:59 But whatever is driving our organization, whether that's a university or a school or, um, or a technology company, you know, you want to have the governed dashboards creating the conversation around, you know, are we meeting our sales targets? We, we need to have the same, uh, calculation for conversion, for weighted pipeline. Everyone… You know, we can't have someone weighting their pipeline with a, a different waiting value or metric because it just suits their needs at a point in time.

25:31 So it's absolutely important to have some centralization.

25:36 Ann Stolzman: Sure. Thank you.

25:38 Chris McClellan: For sure. If there's no more questions, we'll move on.

25:41 Fi Crocker: Sounds good.

25:42 Ann Stolzman: Thank you.

25:43 Fi Crocker: Thanks everyone.

25:44 Chris McClellan: That's okay.

25:44 Fi Crocker: Appreciate you joining us.

25:46 Chris McClellan: That's okay. It's not over yet.

25:48 Fi Crocker: Yeah, I know.

25:48 Chris McClellan: We've got a, we've got a pop-up, pop-up contact details for Fi, and a whole heap of links for DubDub. Uh, the same for Sarah, but you've got their links before. Here's some other links as well.

26:01 All the same thing, just to get in contact with them and talk if you need to after the presentation.

26:06 And just a final part of the survey. So the link's been in the chat for a while. I'll… I was gonna start the counter. I don't know. I will start the counter, it doesn't matter. Um, but scan the QR code or use the link in the chat. If you wanna be really old school, is like type in the whole URL with the code as well.

26:26 But, um, a lot of people have entered that before. Uh, and also while we're looking at the link in the chat, there's the one for the data badge as well.

26:35 So you can actually create your data badge rather than waiting for the whole three minutes to count down. I'm just gonna jump across quickly and look at the survey so far. 10 responses, so that's pretty good.

26:47 And look at the data badges as well.

26:50 So we've had a few people with data badges. That's good. And it's just, um, you know, as I said, it's just interesting to see on the data badge side, we've just got these questions, um, what you've actually done with the TUG.

27:04 And we'll go through the quiz as well. So there's a few more, um, respondents to the quiz, but I'll go through the quiz slowly because people might have time to actually submit questions and go through from there. So first question is usually where do you live? So a range of people as we saw today.

27:20 Um, but we've got New Zealand, Australia, various parts of the US.

27:26 I don't see a London there, so I'll just put my hand out for Sophie that she's in London, and also on the quiz, and also in the meeting as well.

27:35 Uh, what industry do you work in? Just to prove that, um, Tableau can be used in a lot of different industries. So cont- consulting is a standout for today.

27:44 Um, and a variety, uh, over that as well. Someone's had any/all industry, so that's pretty good. That's probably consulting as well.

27:54 And how many years have you been using Tableau?

27:57 This always skews differently. So we've got a few people who have been using Tableau for only zero to two years today, which is fine, and, you know, everyone was in that group at some point in time. It's just that you filter down after a while, obviously.

28:11 And the quiz style questions for today is: Which of the following is a key aspect of data literacy? Everyone got that right, or everyone who answered it got it right.

28:23 Um, which of the following is a key aspect of data-driven culture?

28:27 Again, all these questions are AI generated. The answers are AI generated. Um, a lack of collaboration might be the right answer in your situation as well.

28:36 Uh, what's the primary goal of a data governance program? To ensure data quality and security. Cool.

28:44 And what is the purpose of a data catalog? To provide a pro- to provide a centralized repository of data assets.

28:53 But everyone's getting these questions right. I need to make them a bit harder.

28:57 And, and what is the following is a common challenge in building a data culture? A lack of data. Yes, I would actually mark that as being a good answer as well.

29:06 But, but in this instance, resistance to change was the correct answer. But, but yeah, lack of data for sure.

29:12 I was looking for an all of the above.

29:15 Ann Stolzman: Yeah.

29:15 Chris McClellan: Yeah. It's hard, it's hard to do all of the above, but yeah. I should- You did, um…

29:20 Yeah, they're– These questions or the, the answers this time were much better in terms of, uh… It was a little more obvious which one was correct, I think. Yep. So it's better.

29:33 Though maybe having multiple that are close can lead to, to some discussion.

29:39 Makes it harder. So. I al- also had to prompt the AI a few times to actually get the questions right, because the first batch of questions, like I always generate 10 questions to get like five good ones, and the first 10 it was, it was just absolute rubbish. And it's like I, I just…

29:56 It was impossible to ask someone that question because it just, the answer didn't, didn't make sense at all.

30:01 So again, it's prompting the AI properly to get the result that you want when you're trying to get to a certain result. You should have fed it the Data Fluencer Toolkit training content.

30:13 Well, now I've got the link. I could send that through.

30:16 Yeah, this is the trick, is doing it without let- without knowing what the content's about, so that's why.

30:22 Um, so what do we want to see at this TUG in the future? Is the future of data viz interesting? More TC26 stuff, Tableau features, uh, just anything. Tableau journeys. Yes, I need to get onto that. There's a few people I can contact to do that.

30:37 And who should present at the TUG?

30:41 Because I'm just reading this as well, right? Mark R., um, everyone… Mark- Is that the same Mark?

30:47 And Neil Richards.

30:49 That just gives me s- a bit of leverage to go back to these guys, but asking Mark might be a little bit tricky. I'm not sure.

30:55 I'll see what happens.

30:57 Fi Crocker: Maybe for your hundredth.

30:58 Sarah Burnett: I know some Marks.

30:59 Chris McClellan: Sorry, what?

31:00 Sarah Burnett: Maybe for your hundredth.

31:02 Chris McClellan: Maybe for the hundredth. Yeah.

31:03 Sarah Burnett: Yeah.

31:03 Chris McClellan: Maybe he'll watch it. I don't know.

31:05 We'll see.

31:06 Fi Crocker: Screen share.

31:07 Chris McClellan: And, and who even put the other Mark there? W- are we talking about the same Mark? I'm not sure.

31:11 Sarah Burnett: Yes.

31:11 Fi Crocker: Yes.

31:12 Chris McClellan: Yes.

31:13 Sarah Burnett: Did… Was that you, Sarah?

31:14 Fi Crocker: No.

31:14 Sarah Burnett: 'Cause Mark R. was me.

31:18 Chris McClellan: It's like when someone goes Mark, look, everyone k- knows who Mark is. There's a million Marks. It's cool.

31:23 Sarah Burnett: .

31:23 Chris McClellan: It's fine. This is, this is just evidence that I can go back to him and say, "Look, people want to see you present so you should actually come and present," right?

31:31 Um, and then just going back to the badges for a minute. Oh, only s-… Oh, we've got more badges? No, we don't.

31:37 But anyway.

31:38 Jacob Rothemund: Think I need to refresh the page. Refresh, yeah. Refresh.

31:40 Fi Crocker: There probably is more.

31:41 Chris McClellan: I thought it just refreshed.

31:44 Oh, now there's more badges.

31:46 Jacob Rothemund: Although the bottom of his screen cuts off. I don't know.

31:50 Chris McClellan: I don't know. Michelle and Sophie-

31:51 Jacob Rothemund: Like the bottom of your browser's getting cut off

31:54 Chris McClellan: … Michelle and Sophie run Vizibly. Uh, we're doing it as more of a test. I don't know if, if either of you guys wanna cut in and, and talk about this a little bit.

32:03 Question without notice.

32:04 Michelle Maraj: Happy to share a little bit. Thank you guys so much. So Vizibly is a data badge generation website. So data badges are n- just another way to engage your audiences. So you know, it's great as either, like an icebreaker at the beginning of a call, way to close out at the end of a call just to see like people's receptions to what you presented on. But it's a way for, yeah, people in your audience to take a quick survey, get a badge, um, and share their experiences.

32:30 So with the badge really it is an image that's great for sharing on social media. So you can definitely, you know, get your image and then share it to LinkedIn or Instagram. It's got, "Hey, I attended this event. This is, um, what I learned," and things like that. So it's, like just another fun way to interact with data that we're testing out.

32:51 Chris McClellan: Pretty cool. And you can customize the questions and everything, so these questions were customized for us today as well, which is good.

32:58 Jacob Rothemund: If you, um, if you answer exactly the same as someone else does it end up, like having a times two or does a second badge of the same just appear or…?

33:07 Michelle Maraj: A second badge of the same would appear.

33:09 Jacob Rothemund: Cool.

33:11 Michelle Maraj: Yeah. And so I mean it's kinda interesting to see here. You can see that most people have attended more than four, um-

33:17 Chris McClellan: Mm-hmm

33:18 Michelle Maraj: … D- DataFam TUGs which is really cool. So it kind of just helps you see, like how you relate to everybody else in the audience too.

33:27 Chris McClellan: I told you there was some people who had been to a lot of TUGs.

33:30 Especially this one. We've got the, we've got the regular crowd, and then we always have people that, that just jump in because it's a topic they're interested in as well.

33:38 Jacob Rothemund: I think Ian's beating me. Probably.

33:43 Chris McClellan: I need to pull the stats and check. I don't know.

33:45 Michelle Maraj: Oh, and I wanted to also quickly plug that if you are watching the recording we're leaving the, um, the data badge up for a little bit and so you can still fill it out and check the wall back, um, in a couple days and you could still see it.

33:59 Chris McClellan: And that'll change those badges as well, right? Because one of the questions was, "Is it live or recorded?" And you'll see the wall change with them.

34:07 Fi Crocker: That's cool. Um, I was wondering, uh, do you just go to Vizibly.live if you are interested in doing badges for something else? Or what's the story?

34:19 Michelle Maraj: Yes. And so if you are interested what you can do is as an event organizer you can create an account on Vizibly live, so that is the URL. It's Vizibly.live. Um, you can create an account and then from there you can either use a template or create your own badge from scratch and then you can, yeah, share the wall, share the link and use it for your own events.

34:37 Though we are running, um…

34:39 It, it is free right now in that we do have a free version, and so we're currently in the beta testing process, but, um, yeah, definitely let us know if you run any issues or have any questions about it and we're happy to chat.

34:50 Chris McClellan: Easy. Perfect.

34:51 Fi Crocker: Very cool.

34:52 Chris McClellan: An- and I think it worked well, so that's good. So if you want to submit questions for the survey as well you can do that on that link or that QR code. We're just full of QR codes at the moment. Um, I sort of prefer QR codes rather than writing links down all the time. Again, all this is in the recording.

35:09 But you can go back and actually submit questions for this TUG or just in the global pool of questions 'cause other TUGs might be using the system as well.

35:17 Um, if just something looks good. The questions need to be approved so you can't… You know, there is filtering in there. But, um-… if someone's got some questions put them in.

35:27 Yeah, I'm not game enough to just let it open flat out.

35:30 Fi Crocker: Fair enough.

35:31 Chris McClellan: And the next TUG meeting is Shaheel talking about, uh, dashboards and the Tableau API ecosystem, so another API techy type talk. But, uh, again, should be good. It's all up to him. Um, because of the time slot it's August 5 everywhere in the world, it just depends if you're in the USA it might be an early start. Uh, if you're in Australia and through to Europe it's a little bit more sensible time.

35:56 But again, be here live or watch the recording as well.

36:00 And speaking of recordings, everything that we do and whole heap of other online TUGs are on the YouTube channel at TeamDatafam or the Spotify or Apple podcasts.

36:10 Um, there's shorts on YouTube as well. I was talking to someone the other day, they didn't realize that we did shorts. But, uh, a whole heap of TUGs on there. Um, Data+ Women West Coast as well.

36:21 Um, tons of great content, and if you're not near a screen you can listen to the podcast and get a lot of detail about that as well.

36:30 But again, thanks Fi and Sarah for doing that. Was great to see that. You don't have to be at TC26. And I'm hoping a lot of people can benefit from that and download your training material as well.

36:44 Fi Crocker: Thank you.

36:45 Sarah Burnett: Thank you.

36:46 Chris McClellan: Awesome.

36:47 Thanks, guys.

36:48 Jacob Rothemund: Thanks, guys. See you later.

36:50 Bye.

36:50 Thank you all. Thank you.

36:51 Jacob Rothemund: Cheers. Bye.

36:52 Thanks, all. Take care.