We're really excited to share some dashboard design tips for this year with you. I've got my colleague Robin here. We'll introduce her more in a little bit. But also just wanted to call out that this webinar is part of our monthly assist webinar series. There's a QR code on the screen. If you want to scan that, it'll get you registered for our February webinar. That topic is going to be a new feature review from the twenty one point four release of Tableau. So excited to share those tips with you. Feel free to scan that code and sign up right now. A couple of you had already asked, this webinar will be recorded. You'll get a follow-up email that's got a link to that. So if you need to step out for a minute, no worries, you can catch it, you can catch the recording later. You can also share it with anyone who didn't have a chance to attend live. On the right side of the screen, just a couple of things to help you, to make sure that you know about. If you're running into issues that you're getting stuck on in Tableau or Tableau Server, we've got an assist program that gives you access to our data professionals. So feel free to check that out, interworks dot com slash assist. It's just it'll just give you the peace of mind to know that there's someone available to help you if you get stuck and need some help. If you're looking to, add on to the user experience in tablet server, our Curator product works really well with it, and it offers some additional functionality and allows you to create a branded analytics experience. So it just takes your dashboards to the next level and make sure that your users are getting the most out of those great dashboards you've created. And then last of all, server care is just a managed service to help you take care of your Tableau server. If you need help, maintaining the health of that or, doing those upgrades, feel free to reach out to us. We'd be happy to help you with that as well. Along the bottom of your screen, you should see a couple of buttons. If you have questions throughout the presentation, drop them in the Q and A section. The chat can get pretty busy, so we wanna make sure we don't miss those questions. So if anything comes up along the way that you wanna know more about, feel free to put a question in the Q and A. The chat is great just for those general comments and chatter as well. Just a little bit more, about us. You'll see on the screen, just an overview of who we are and what we do. We are a global company. We've got, lots of people that can help out with any tech or data needs that you have. If you haven't visited our blog yet, feel free to check it out. We're sharing lots of great tips on there that might be helpful for you. And just a quick overview of what we do, I've got on the screen here all of the different practice areas that we have at Interworks. We do a little bit of everything when it comes to data, and often the people we work with at some point will say to us, oh, we didn't realize you did that too. So we just wanted to make it known there's lots of things that we can help you out with. If anything on the screen here jumps out at you as something that you would like to connect with us about, feel free to reach out. We'd love to talk more. So let's get into, a bit of our presentation today. I'm Keith, I'm an analytics consultant here in, the US. I've got my colleague Robin with me, she's based in the Netherlands, so special thank you to Robin. She should be kicking her feet up and watching Netflix, and instead, she's kicking it with her American Data fam. So thanks for joining us, Robin. Dustin is normally on the call, but unfortunately, he's sick this week, so he'll be back next month. He usually hosts these, so look forward to seeing him back here next month. So, again, thanks to everybody who joined. We're glad that you chose to spend part of your Friday with us, and we are excited to share some tips that we hope will help you create better dashboards in twenty twenty two. So Robin and I, as analytics consultants, spent a lot of our time last year either looking at or building dashboards. But as we reflected on the ones that were our favorite, the ones that seem particularly effective or impressive, we noticed a few themes. First, great dashboards are intuitive. They're easy for users to understand. They don't require much explanation at all. Great dashboards are also flexible. They allow users to approach data from multiple angles. They're versatile, and they're often multifaceted. And great dashboards are contextualized. They place specific values in context, and they help users maintain the big picture even as they dig into the details. So I'll confess that Robin and I probably spent the bulk of our prep time for this webinar trying to decide on that third word. It's a complicated, issue, but we're gonna share some examples of each of these to flesh out these ideas a little bit further. I think we saw all of these themes in some of the dashboards that inspired us last year, like this one. Now this is actually a website. I'm sort of cheating. This isn't created in Tableau, and it is the UK government's website to show COVID data. It came up as an example of really good data visualization during a workshop that I was leading, and as we dug in, we noticed a lot of things that we liked about it. If you take a closer look, I think that this data visualization does a great job of layering in context through tooltips and by combining multiple chart types to show some really rich analysis. It offers a really flexible user experience through time period buttons and different ways that you can choose to look at the data. But despite all of these options, it's not overwhelming. It still feels really easy to use. -We also found a lot of inspiration in the Tableau community. Some quick examples, Luke Stankey, his sales dashboard for executives. It's flexible. It's contextualized. I love the little drop downs on the right. We had this one, Kisley Benedict, the dark superstore dashboard. A different look, but still really clean and beautiful. I love the use of icons, and there's lots to choose both from the menu on the left and the different tabs above the charts. We wanted to share this one from Ludovich Stabranier, the salesperson dashboard. Also built on SuperStore, but a completely different look, and something I really liked here were the clear headers and explanations surrounding the charts. And from our own Beth Carries of in Australia, she made a great blog as well as visualization for current versus comparison periods. So different ways of presenting time comparisons, all clean and beautiful, suitable to different use cases. If you're wondering where you can find any of these dashboards, instead of dropping a dozen links in the chat, I've actually gone ahead and just favorited them all on Tableau Public. Check out my profile. If you navigate to the favorites tab, you'll see all of the dashboards we mentioned as well as a few that we're going to mention later in today's session. But we're excited to dig into these themes with you today and share some of the ways that we try to produce more intuitive, flexible, and contextualize analytics experiences. We'll go ahead and start with a foundational element of dashboards, KPIs and big numbers. Actually gonna start by showing you what not to do. So here's a really old dashboard that Tableau produced as an early example of what the software could do. And at the time it was built, which was probably about a decade ago now, this was a top notch dashboard. But I will say that I think dashboards have evolved quite a bit since this was created. And one of the ways that they've evolved is in the way that we treat those KPIs and bands across the top. If you look closely at those numbers, I don't really know if two point million dollars in sales or three hundred and sixty thousand dollars in profit is good or if it's bad. I'm not really sure if the sales are trending up, if they're crashing down, if they've been relatively stable. So unless I'm really familiar with what's normal here, the numbers alone don't really tell us much. So when you have important numbers, KPIs, bands to put at the top of your dashboard, you can make them much more effective if you support them with other context like thresholds or trends or even just indications of whether they're good, bad, or neutral. So let's go back to that example of the COVID data that we showed at the beginning. I think it's a great example of where that top line number, a hundred and twenty nine thousand, is supported by other pieces of data. They show a trend line to help you place that one hundred and twenty nine thousand in context of a recent spike. So as it turns out, one hundred and twenty nine thousand isn't very normal in this situation given the historical trend. But they also add a seven day total and a percent change compared to the prior week, and that helps us see a more recent trend. Recently cases are going back down. And I really appreciate how they connect that week over week trend to the larger historical trends so I can easily see how those pieces fit together. And then altogether, it does provide this really rich and layered and intuitive experience. I know what the picture looks like now, and I also know how it fits into the broader context. Here's an example where I tried to put some of those same ideas into practice for our client last year. Now the client came and said, we just wanna see a number, just show us, you know, percent change of sales from last year. And we said, sure, we can absolutely show you that. We can also tell you some more information. We can put that number in the context of our historical trend to show you what that number looks like today, but also how it compared to the previous period, or the or the time before. We visually identified they had a goal of increasing their sales by seventeen percent, so we added a simple reference line there. And then we also added an icon, just a quick check mark so if anyone was scanning the dashboard, they could quickly see, oh, we're doing okay here, or actually this is worth digging into. And I think all those things combined to tell us a lot more than just a simple twenty point six percent. And there's other places where we're able to layer some more information into that dashboard. So rather than just showing an average per state, we could combine that with a distribution plot to show the underlying stores that made up that average, and it gives them a fuller picture of how that average is made up and allows them to dig a little bit deeper if they want to. Just like seeing a number without any context, getting launched straight into a dashboard can be confusing, and often we do that in Tableau where we just have a dashboard link to click on. It's almost like being dropped in a location without a map, and that can be overwhelming for users. So last year, we found ourselves building more and more home screens like you would see on websites. It might seem a little silly because people can switch between tabs, but it can really work magic. Home screens or these landing pages can accomplish a couple of things. They can provide a soft landing for users where they can decide how they are going to engage with their dashboard, what experience would they want. We had a client recently where a user was trying to use a dashboard for all the wrong things, and we had actually built a dashboard specifically for what they were trying to do, but they didn't quite make the connection that there were other dashboards in a workbook. So it forced us to create some sort of a landing page to make it clear that there were other screens that were maybe more helpful to them, and they could go to the right dashboard immediately. It can also be really useful if you have a dashboard serving multiple use cases or you have similar dashboards that are slightly different. Landing pages can be a sort of welcome doormat to your analytics experience, a signpost of where to go. The two that were shown here were created in Tableau and embedded into our curator sites to really provide a rich analytical experience. I also want to share some cleaned, simplified client examples. Sometimes landing pages can simply be a place to document your dashboard and to provide some extra context. In this case, data source information, so what sources are we using, when was it last updated, but also if you're seeing something weird in the dashboard, who do you go to? In this case, we even had a disclaimer at the bottom because some users wanted to have this printed and shared, and it was simply for compliance reasons that that disclaimer needed to go somewhere. So we'd rather have it on this kind of landing page than in every dashboard. One more, also redacted, rebuilt, so forgive the silly icons at the top. I like the concept of this one quite a bit because the client was very clear of where the dashboard fit within their processes. So that was a great piece of context. Users were aware that this dashboard was to be used in phase two point three. They knew when they were coming here and what to use it for, so it really got incorporated in their day to day. Even more so, I liked moving the filters to the front page because it really allowed users to select their scope up front. They could tell us, Hey, we want to see this specific region, this specific segment, set their own context and keep that in mind as they were moving into the dashboard. They knew what data to expect, and filtering the data down before we load a dashboard, of course, really improves performance and ease of use because they don't have to do these filters once they land on the dashboard. So overall, people are used to landing pages. They can provide some more context and understanding, even performance improvements, and it's a nice warm welcome into your analytics experience. I'll just say really quickly, I had, a client too where moving those filters to the homepage was a game changer for performance for them. They came to us and had a dashboard that was loading terribly slowly because it was loading a huge amount of data, and just forcing users to make some selections first really improved that user experience. And I saw a question from Saraswati. Yes. These these landing pages that we showed were actually built in Tableau. We then embedded them into Curator, which is a product that we also use in conjunction with Tableau Server. So you can build them there, and there's also ways that you can build them outside and connect them to your dashboard too. Well, we just talked about how landing pages can help users orient themselves when they are new to a dashboard and make sure they get to the right place. But even after they get where they want to, sometimes complex data requires a little bit of extra explanation, and that can be really challenging when your data is constantly changing. I will say that good chart selection goes a long way to making sure that your users understand what they're looking at, but pairing those charts with some explanations of insights can can really be powerful and help them understand what they're looking at. So here's an example from an adoption report that we built for a client. We wanted to help them monitor usage of new dashboards. And with the top chart, we're showing the running total of new users over time according to the first time that they looked at a dashboard. And then at the bottom, we showed them a week by week count of how many new users they gained each week. But when we tested this with users, some of this some of them said, we're not really sure if we understand how these charts work together. Can you explain more about what we're seeing? So we decided to add a sidebar that explained exactly what was going on. A hundred ninety one users have used this report at least once, and this report gained two new users last week. It seems pretty simple, but these little additions just made it totally clear what the charts were telling them. And because we use logic to construct them, they're dynamic and those explanations change as the data changes as well. Here's a different example where we were working on a health care dashboard, and we wanted to show counties that showed disparities in care for black and white patients. While the map and the color legend tell a pretty clear picture, we also added a description of the top line insight. So in this case, ten counties were showing moderate disparities, and we wanted to drive that point home with users to make sure they saw that right away. The logic can get a little bit complicated when there's multiple permutations to plan for and trying to get that language that seems right in every situation is tricky. You're just seeing half the calculation that I used here to write that top line, insight for the map I just showed you, but I do think investing some time in writing a clear and dynamic description can make sure that users save time by understanding the data right away and not misinterpreting it. And I'll also say that natural language isn't just helpful for describing insights in a dashboard. In the same dashboard, it was also helpful for alerting users to anomalies and unexpected things. So in this dot plot at the bottom that's outlined, there were some extreme outliers that were really skewing the axis of that scale. So we decided to exclude them by default. In most cases, those outliers could be safely ignored. But sometimes those outlier counties were actually counties being served by the healthcare provider or the hospital in focus. And so in those instances, we didn't want users to overlook the fact that some of those counties were hidden by default. So we added this conditional warning. It only pops up when there's outliers that are hidden, and it encourages the users to toggle on those outliers to see the full picture. So what if your users insist to see all details at all times? Maybe you'll end up like the lady on this slide, facing endless questions of exports. I've definitely been her in the past year. Or maybe you don't even get to build a nice visualization in the first place. We want to run a little poll with you guys. How many of you have felt frustration of wanting to build a nice visualization but your users insist on a table? Let us know if you've had to sacrifice a viz for a table. So we'll leave the question up there for a few minutes and just see what the responses are. There are definitely some clear winners popping in, so take a second to respond. We'll share the results with you in just a minute. It looks like overall people feel our pain, Rob, Robyn. People have often or very often encountered this as well. So we're all in this together. Let's talk about some ways that we can deal with this. Yes, indeed. It's unfortunate you guys feel the same, but at least it's a shared pain. Of course, tables are not all bad. They have their use cases. Sometimes they're quite helpful even. But often, we can at least elevate them to be better by combining tables with other techniques that visually encode the information. Here's some of our favorite things that we've done to spice up the tables we couldn't avoid. Of course, the trusty old classic highlight tables. Just adding some color. The use of color immediately helps draw the eye to the good and the bad, to the extremes. Of course, you don't need to use bold coloring if you don't want to, and then this can be quite a subtle option to support users to find their data within the table you built, and they want it. I personally really like convincing users by giving them a table without coloring and asking them a simple question, like the lowest performing subcategory. And then I give them the colored version of the table, and they'll find that they would have found the answer much quicker in that version. And I think that's what visual analytics is all about. Visual analytics are supposed to save you some time in getting to your insights and saving you some brain capacity from processing all this information so that you have time and brain capacity left to find patterns and ask more interesting questions. This one that I've done for a client recently was very well received. Of course, again, recreated in Superstore, you won't find your data in our webinar. The dashboard I built was already quite busy and colorful. That tree map in the top was pretty much as bright as it is here. I insisted, though, that the table could be more than just a simple table. I added some bars behind the numbers. A very simple solution just built with measure names, measure values, choosing bars as marks. Use the simple light color to not make it too intense. And of course, this gives a bit more context immediately. For example, even with this data, you can see we've sorted on sales, but the quantity varies widely between the different stores in this case. This can be a gentle way to transition from bar charts sorry, from tables to bar charts over time. Every organization goes at its own pace. Each and every single one of you might be at a different point in that journey, but this can be a gentle way of transitioning people and introducing them to more visual analytics. We also want to give a shout out to Ludovic Tavernier. He's been doing exceptional things to improve tables for a while, adding context, color, indicators within just what appeared to be a simple table. I only found this one recently, but I really hope to incorporate some more of his style in my dashboards going forward. And yes, I did give Robin that slide because her French accent is much better than mine, so I would have butchered the name. Thank you, Robin. Another way that we saw people making good use of tables or better use of tables, because they are helpful and they are essential sometimes, is just by pairing them with other ways of showing the data. In Tableau, one of the best ways and most seamless ways to do that is using the show hide feature. Think Pradeep Kumar was one of the first people that I noticed doing this. He built this dashboard a couple years ago as soon as the showhide feature came out, and he toggled on an ability to show those underlying records and see the underlying data. But because it's a showhide option, you don't have to navigate to a separate screen and then go back. You can just turn it on and turn it off as you need it. We saw that show up again in this dashboard by Kisley Benedict. Similar concept, you can toggle on some of that underlying data and see a table format, but he's also incorporated some of the tips that Robin just shared about improving those tables and not having just text available. And then I saw Luke Stankey use the feature in sort of a different way. If you click on a particular category, so chairs for instance, it overlays some additional analysis where there's new charts where that you can use to answer even deeper questions about that specific category you've dug into. And those examples unlocked a new idea for me. I had seen this in websites and I figured, you know what? I can figure out how to do this in Tableau as well. So in this example, I wanted to show users a summary at first, but also allow them to dig into a more detailed view of the data. And again, I didn't want this to send them to two different tabs dashboard and have them bounce back and forth between that. There is some loading time that users have to endure, to get back and forth. So instead, I built two completely different sections. So the summary section is tiled into the dashboard by default. And then when users click on that details icon, it floats on top of it a different section that shows a whole different set of charts. Sometimes people do this with sheet swapping. It was a little too complicated to use sheet swapping here because of the number of different charts I wanted to use, and so the showhide button was was kind of the the linchpin for me. If you take a deeper look, the the showhide button is actually just two images that I created in PowerPoint, and it's set up to look like you often experience in apps and websites with the blue underline indicating what you've selected and then your other option being there as well. So as the user clicks that image, it swaps between those two images, and it also shows and hides the details tab so that you can look at either level of the data. I really love that use of show height to just switch between tabs. I would have definitely tried building it with a sheet swap first, but I think this is much cleaner. Whether you're switching between different levels of information within one view or when you're very deep in the details, sometimes it's nice to have indicators that preserve some of that context. I think Tableau's action filters do this quite naturally. You have a bar chart in your dashboard. You click on the bars, the rest of your dashboard filters, but you can still see the whole bar chart. I took that one step further in the last year where I've replaced some simple filters in my filter pane with selectable bar charts. So in this one, when you're deep into your analysis of late orders in the West that had same day shipping, you're reminded that the West is only a part of all the orders and that most orders go through standard class, and maybe those were all on time. So what's great is both the initial context that these bar charts give you as well as keeping that context when you filter in deeper. I made the bars quite minimal, so they're not visually overwhelming. They're more background information, but they do allow users to change their perspective with a single click again. To go even more visual, you could use a clickable image. Tableau allows us to use custom background images. And when you have the right use case for these, or if you're just showing off on Tableau Public, as we do, clickable images can be a fantastic way to elevate your data. So imagine you're a Game Boy repair shop. You replace buttons and screens. Now you can click on which button you still need to order. You can get an overview of where the button might be available. You click your state, and then you see the specific manufacturers and whether they have any stock. This is fake data, of course, but you can imagine the real use cases. Clickable anatomy in health care or educational purposes where you click different parts of an image and information pops up. Of course, we also do this a lot with maps. We click on the place we want more information about, And you can do this also if you have mappable things that aren't immediately recognized by Tableau. I created this viz recently with the help of CVI Studio, custom background images studio, which leads us to a tiny little ad break. Because recently, we have released CVI Studio by Interworks, It's building upon the old drawing tool that you might know, and it allows you to plot data points, whether you're starting from an image or a map. So it'll have a little grid, and you can put points down, or you can draw polygons. And basically, this will generate the data for where you selected your points. You can give it labels and different colorings, and you can bring that into Tableau or any other tools. We've upgraded it from the drawing tool version with labeling options, grid and selection options, and we're always improving. There's a blog and some YouTube tutorials already out there for this. And, of course, it is still free to use. It's our little gift to the community, and we can't wait to see what you guys make with it next. So check it out. Well, we saw lots of other cool things in dashboards, and we wish we had more time to them in detail. But if we did, this would become a four hour webinar, and you guys don't wanna spend your Friday in four hours of webinars. So we're gonna quickly wrap up and mention a few other things here at the end. I think this technique was originally by Brian Sleeper, but we have this newfound love for the stacked bar chart. One of the great drawbacks of stacked bars is that a single category can be tough to compare across, but making them sortable like this means you can still compare whichever one you'd like across, so really makes them more powerful. I saw Morgan Reeder add a Zoom option to this line chart. So at the bottom of this dashboard, that line chart hangs out pretty close to the x axis because it's a pretty small percentage, and it's really hard to see the variation because it's so small. But she added a zoom toggle, and essentially what that's doing is there's an invisible reference line on that chart. It and it switches back and forth between one, a hundred percent, and the window max. So when you're clicking to zoom in, it switches that reference line to, the window max, which adjusts the axis. It just was a cool way of, I think, allowing users to see originally, this is a very small percentage, but also to zoom in and see the variation if they wanted to. And I was able to use that in a dashboard I was building. I was looking at a demographic breakdown of some different categories of people enrolled in studies, And some of those categories had really narrow ranges, and so all those dots ended up clustered on top of each other. But just adding a simple Zoom option gave people the ability to create a dynamic scale, and so we showed them originally, this is where the number is in the context of zero to one hundred percent. But if you want to look a little bit closer, you can create an individual access for each of those dot plots to spread that data out and see the variation within that narrow range. Talking about zooming in, I've been quite frustrated with the map zooming within Tableau, where you're either scrolling or frantically clicking the plus and you're not getting exactly the part of the map that you wanted to. And we saw Ellen Blackburn use layers to create a map where you can simply click on a state to zoom in, click on a city to see specific locations, and when you click on a state again, it zooms back out. So using map layers like this, I think, is a really nice alternative to the traditional zoom function. And speaking of Ellen Blackburn, I saw her do another really cool thing. She built this what if analysis in its manufacturing dashboard. At its core, it's really just a parameter that users are adjusting, so it's nothing terribly complicated. But I think she paired it with some really thoughtful charts, and so she's really clearly showing the impact of increasing inventory on cost and the time needed to recover that cost. Overall, just found it to be a really thoughtful way to equip users with flexible and integrated analysis. And lastly, one of the coolest things I got to build last year was this accordion style sidebar. It's not something I would recommend in most cases, but it actually was really useful here. I drew some inspiration from Luke Stenke. I saw something similar from him in a dashboard. And in this case, users needed the flexibility to basically build their own table from a really large data source. There was lots of different use cases, and so the best way for us to accommodate that and give them a flexible interface was to create some different sections that they could expand and collapse. And then we use set actions to allow them to add and remove certain measures or dimensions from that table so they could look at the exact data that they wanted to see. Definitely a fun challenge, a little bit of work involved, and we've got a blog that'll be published in the next few days describing the technique if you ever find yourself in a position where you need to do something similar. There's lots of other things that we could have shared with you today, but we really should start wrapping up. But we're also interested to know what cool things you all have seen in dashboards in last year or so. So if there's anything that you want to add to the chat, if you want to drop a link there, we'd love to share, we'd love for you to share your inspiration just like we've shared some ideas with you today. Let's take it back to why this matters though. Some of the tips that we've shown you today require a bit of extra work. They're not the simple out of the box solutions that you can build with Tableau, so they are gonna take more time. So why even bother? Well, at the end of the day, I'd say that we build dashboards to make people's lives easier and to help them make better decisions faster. A great dashboard can reach hundreds and maybe even thousands of people, and if they start using it over and over, the time that you invest in making a better experience for them and making that dashboard more intuitive, more flexible, is just gonna pay dividends for them in the long run. So overall, we'd argue that any changes that are gonna make a dashboard intuitive, flexible, and contextualize are worth the effort. If you were inspired by this webinar and you want to create some of these yourself, whether it's to show off on Tableau Public or in your day to day work. Check out CDI Studio if you have the use case for it. It's out. It's free. We hope you love it. Also, don't feel like you need to recreate the wheel. Tableau Public is a great source of inspiration. We've shared a few great authors today, there's lots more examples on Tableau Public. Again, feel free to go to my profile and you can see all of the examples that we mentioned today. You'll have easy links to those authors' profiles where you can download many of those workbooks. Our Interworks blog, we're always sharing great tips, how to articles, step by step guides, so feel free to check that out as well if you want help with any of the things that we've discussed today. And of course, if you're on Twitter, give us a quick follow and you'll be the first to know when we publish new content. And, of course, don't hesitate to reach out if you get stuck. Reach out to our assist team for support. We're happy to help. We'll take a look at the q and a now. I see a couple of questions in there, so we'll see if we can knock a few of those out. Again, feel free to drop additional questions in the Q and A section. If we see something in the chat, we'll try to keep up, but sometimes it's moving pretty fast. One of the questions I see in the Q and A is from Daniel Tan. He asked about if we used an extension to get that toggle button, for the show hide outliers. We didn't actually. What's behind that toggle for show hide is just a parameter action and there's two images. As you click on the image, the parameter value changes and that value is assigned to a shape and so it switches to a different shape. So just clicking on that toggles back and forth between two images, kind of like that showhide thing that I showed you, but it just runs on a parameter action there. Great question. I see an early one. Can Tableau track user specific preferences so they won't need to reselect their filters, sorts, or other custom settings each visit? So there in Tableau Server, there's an option to create a view and people can make this their default view, and that takes into account all the filters they have selected up until that point. So if you go into a dashboard, select your filters, and then create a view from that, the next time you could make that your default. So those filters are immediately applied. So that's within Tableau Server. I see Radhika asked a question about where can I find the accordion sidebar? It is not published yet, but it should be out on our blog, I think probably early next week. So keep an eye on that. My colleague Linus wrote up the technique and also developed an anonymized workbook so that we can share that with you as well. You'll be able to download it and reverse engineer it, and there'll also be a step by step guide available for you there. I see. Oana, how do we make the stacked bar sort? So that's not one of ours, but I believe it's Playfair Data that has a good blog on this. There might be a couple others out there. If you give it a quick Google, you should be able to find one. Question from Rupert about an export button. I believe it depends on the version of Tableau that you have, but they've recently added just a quick export option. Also in Tableau Server, there's an option to export data. If you're not on the latest version, there's still a ribbon at the top that allows you to export that underlying data. Dennis was asking about our blog URL. Yeah, we can drop that in the chat. Just interworks dot com slash blog is where you'll find that stuff, and we're adding new stuff every week to that. Generally, when we run into an issue that takes us a little while to solve, we try to write up an article to help all of you just in case you're in the same situation. I see a follow-up question on those views from Nathan. In terms of performance, do views preload from the data source for users who save a view? I do believe so. I think they do. Yeah. And a question from Travis. If we've seen better Viz performance using showhide versus sheet tabs, In general, this is just anecdotal experience. Would say that in the dashboard I showed, was a faster experience to go back and forth between showhide than to navigate to different tabs. Definitely something you should check out, and the difference was probably only a second, maybe two. So it may be subtle, but that time can add up if users are using dashboards very often. I'm just going to scan through the chat too to see if there's any questions that we missed in there. You guys have been really active, so we love all of the excitement in there. I might get lost in all of the comments, but I'll take a quick scroll and see if there's anything that we've missed. Again, feel free to drop additional questions in the Q and A because that is really easy for us to see and answer if there's any other questions you want to know before we wrap up. I do see a couple of questions about sessions being recorded in case you missed it. Yes, we will send you a follow-up email. You'll get a link to, a recording of the sessions. You can feel free to share it with others as well or catch any parts that you may have missed. I see in the Q and A, when you had the bar and table, how did it download? So the download function is still there, and it downloaded as if it was a normal table, so it downloaded pretty well because it's a combination of measure names, measure values, although I would say that I don't like the exports and the downloads for everything, but when it's needed, it would still download properly. I'm mostly seeing comments that people think your tricks are really slick, Robin. People love the sidebar with the bar chart so that you can preserve some context as you're digging in. Lots of comments and people saying that that's cool. So glad to know some of these tips are helpful for you. Yeah, we would love to see the stuff that you do with them. So if you're able to use any of the tips that we shared, feel free to share on TEFL public. If you're on Twitter, give us a shout. We'd love to see what you guys come up with as well. Thanks so much. Yeah, just saw one other question come in from Travis. With the color coding tips with data sheets, have you seen acceptance from users that prefer data sheets? Oh, interesting. Yeah, so sometimes, yeah, that really is what end users need is they need a table that shows them the data in a tabular format. The accordion sidebar that I showed you is actually just a way of building a table for users. We're not opposed to giving people tables when it's what they need, but sometimes we just find if you are new to Tableau, you're new to visual analytics, if you're used to working with data in spreadsheets, introducing people to those visuals can be a helpful way to call out the insights that are harder to find, but certainly give people the tables if they need them, pair them with visuals when it's helpful as well. I found one in the chat from Judy. I work at a district community college with two sister colleges. Is there a possibility to create a view for everyone that belongs to a certain school and default filter for that group? That is possible using row level security. It's like setting permissions, but using Tableau's username function will allow you to set different filters based on who's looking at it. We did get another question coming in from Biju Phillips about better export to PowerPoint. Yes, actually the Curator product that we mentioned works conjunction with Tableau Server. There's some additional features in Curator that allow you to do things just like that. You can actually build a PowerPoint and choose the slides that you want to present. So if you're finding yourself running into some limitations on what Tableau Server can do, Curator adds a few extra pieces of functionality that work really well with that as well. So great question, Dijoon. Another question from anonymous attendee. What are your thoughts on Tableau dashboards and accessibility, specifically colors used and color contrast in dark dashboards? You know, it's a really great question. There's been a lot of focus on color blindness and how to do color blind friendly palettes. Thank you all for that because I'm color blind, so I appreciate the help there. I nearly almost accidentally painted my bathroom pink because I thought it was white the other week. But color contrast is actually an issue that I don't think gets enough attention in the data vis community, and it is something that we should be conscious of. If people do have contrast issues with their eyesight, you want to make sure that you're presenting something that's still easy for them to see as well. So definitely a good thing to call out to be aware of. Sometimes just printing something in black and white is helpful to see how how much contrast there is between those colors when they're removed. So something that I would recommend is just testing that out. And if you have a user that has any contrast issues, check your dashboard with them before you publish it. Have them test it and let you know if there's anything that's difficult for them to see. I think our design team also uses some online tools that check contracts, so I think those are also out there. It might be worth a search. In terms of best of color palettes, I'm going to defer to someone who's not color blind on that one. We've got a question from Dennis about that, but I am the wrong person to ask for best color palettes. I think a lot of times it's company colors that people are used to seeing so that it's not an overwhelming world of color that you're seeing for the first time. So it really varies depending on the organization, I would say. Also just noticed in the chat that Danielle called out, there's a Chrome extension that can simulate color blindness. I have a similar extension on my computer as well, so it just mimics different visual impairments that people have. So you can also do some testing on your own, even if you don't have that personal impairment. The question came in from Radhika as well. Can we default the second single select dropdown filter to default to the first value from the list when we change? I've run into this issue before. I think that I managed to hack it somehow using like a window minimum calculation, but what Riddika is essentially asking is, as you change a dropdown, can you force Tableau, especially when that dropdown is only relevant values, can you force it to shift to the first value in the list? It is a tricky thing to work around. There may be a hack that involves table calcs. I'll have to go back to the specific example and see if that works there, but I would start with trying a window min or window max calculation to see if that works. I think those are all the questions that I see today. So unless there's any last minute questions, we'll wrap up for the day. We'll give you ten minutes to get to your next meeting or maybe just start your weekend early. Oh, there are a couple other things that came in really quickly. Any advice you have for someone that's still fairly new and using Tableau and building dashboards? Yes, lots of things that you can do. Personally, the best way for me to learn Tableau was just to start building things on my own. So get your hands on some data, start looking at what other people are doing, see if you can recreate it. I like to reverse engineer things, so I like to find examples from Tableau Public and download them and see how people build things. If you learn other ways, Tableau itself has great resources for getting started. And again, we've got lots of step by step guides on our blog that can help you get started as well. Anything else that you would add to that, Robin? I'm I'm thinking, but I don't think so. I also really got started by reverse engineering, starting to build things. Yeah. Somebody asked if we would recommend working for IntiWorks. One hundred percent recommend. Absolutely. It's been a great fit for me. I've been here for four years. So yes, if you're looking to join the team, to check out our careers page. We have a couple positions open right now, but we're always looking for great people that are passionate about data. Yes, we would love to talk to you if you're interested in working with us. I think we'll shut it down for now. I think we've answered all the questions, but thank you for being such an engaging audience. Thank you for all the questions you asked. Thanks for the funny comments that we saw in the chat. Again, we hope you had found something that was helpful for you in this presentation and hope you have a great weekend and we'll see you back here next month.