Transcript
Good morning to everyone. You are here for Tableau Essentials: Dashboards and Delivery. I'm really excited to be leading this session with you guys today. So let's go ahead and get started.
First, I want to give a quick little intro about InterWorks. If it's your first time being with us on an InterWorks webinar, welcome. Thanks for joining us, and we're glad that you're here.
InterWorks is an analytics consultancy, and we're global. I'm talking to you guys today from Chicago. Rachel, you're from Raleigh, correct?
Yes, I am, Raleigh.
She's talking to us from Raleigh. And we also have consultants in Europe and Australia, so just about anywhere across the globe.
We specialize in helping people and teams succeed with tech. Tableau is a great example of what we're going to be talking about today. We've been a longtime partner, and they've built a great analytics product that we love, and we'll be showing you today. But what InterWorks does alongside our partners and customers is we help build strategies and problem-solving solutions to help succeed with the technology that you have invested in. We can help with all kinds of different things, whether it's just general analytics, data preparation, data management, enablement, or maybe administration.
Today, we're going to be talking about Tableau Essentials. But I also recommend that you visit the InterWorks blog, where you're going to find a whole lot more content about the tech that we support. We're going to have webinars much like this one. And also, follow us on LinkedIn. We're going to be pushing out whenever we have sessions much like this one coming up in the near future.
Just a few reminders: we're going to be recording this session and it'll be on our website in a few days. We'll also send you an email if you registered, and all of you did since you're listening to us right now. You'll get an email that is also going to have a link to the recording. And also we're going to have a survey at the end of this session as well to see how you liked it and also if you need any follow-up.
During this session, if you guys do have questions, feel free to use the Q&A function. Rachel's going to be monitoring that, and she's going to politely or non-politely interrupt me if you guys do have any questions. And we'd be more than happy to try and answer those today.
So with that said, let's go ahead and do some introductions. You guys heard a lot about me. I am from Chicago. My name is Maxwell Croft. I am a membership enablement lead at InterWorks, and I am here to help you guys succeed.
So with that said, I'll go ahead and let Rachel introduce herself.
Hi, I'm Rachel. I'm an analytics architect, like you said, based in Raleigh, which is in North Carolina. We're right in the middle of the East Coast, and I work with the entire lifecycle of data when I help clients with everything from data preparation, data visualization, and data science models as well.
Real quick before I move on from that, we got a question—we both went to Tableau Conference. And I did not go to Tableau Conference, and Maxwell, I can't remember if you did.
I didn't, not this year.
We did not. We did have a whole bunch of us who were there. Just Maxwell and I were not able to go this year. So if you went, I hope you had a great time. I heard good things about it.
Yeah, same here. Rachel, thank you, and I am so glad to have you as my co-host today. I'm excited to talk about this fun topic.
So today, we are going to be discussing Tableau Essentials: Dashboards and Beyond. So first, we're just going to do a little refresher of what is Tableau? Why are we here using this visual analytics software?
And my assumption on this call is going to be that some of you have touched the tool before. You've opened it, you've maybe built some worksheets, built your first dashboard, and you might be thinking what's next, or maybe you need some tips and tricks on how to make your dashboard better. We're going to discuss that. We're also going to go through a design checklist to think about what are the things that you missed.
For myself, I definitely did not come from an analytics background. My background is in chemical engineering. So whenever I heard of Tableau, I was like, what is this cool tool? And I had to learn all these things much like you guys. So I've been in your seat before, and I'm really thankful for webinars much like this one.
We're also going to finish up talking about once we finish building that dashboard, it looks great, we then want to publish this to server. And we're also going to look at something that's called embedded analytics, which some of you might have heard of today, some of you might not have.
So with that said, let's go ahead and jump into things. And I want to start off by taking a quick poll. And I want to know what is your experience with Tableau? So I'm going to let Rachel go ahead and open that up for us, and we have three levels: beginner, intermediate, and expert. So we're going to give that a second to let everyone answer.
A lot of responses fairly quickly. You guys are paying attention, ready at the trigger. I love it. This is great.
I love the live polling feature because it lets you guys be interactive, and it also lets us learn who our audience is.
It seems like we're kind of coming to a point, so I think I'm just going to end the poll and share results.
Yeah, so it looks like the bulk of you on this call are intermediate, which is great. That means that you've opened up the tool, you've built a few dashboards, and hopefully you know what you're doing in the tool. We also have thirty-nine percent beginners. Don't worry, we're not going to be doing anything too crazy that is going to be beyond a beginner level in this workshop. So you guys are in the right session. And a few experts—maybe I should be asking you guys to lead this session instead of me.
Well, you might get some tips and tricks from us as well with some fresh eyes to look at.
Well, guys, thank you for taking this poll for us. I'm going to go ahead and click out of this, and we'll continue on here.
So again, today's topic is going to be about Tableau, and Tableau is a visual analytics software. So we're wanting to connect to some kind of dataset and tell a story with it. We want to be able to analyze and visualize what's happening with that data. Are we trending up? Are we trending down? Is there something that our stakeholders need to know? And then we want to be able to share those insights. We can develop these dashboards and workbooks on our local computers, but at some point, we're going to need to share this to server or maybe somewhere like Curator to let others see what we're building and how we're doing.
Tableau has a ton of different data connections available: Salesforce, Excel, SQL, PDF—you name it, it's probably located right in there.
Now where we all need to start is with the data, and what I will say is we do need to have clean data to start building dashboards. So we're not going to dive into that today, but know that data preparation is key. And I know Rachel can definitely agree with me on that.
So the tool that we're looking at is really nice because it's fast, iterative, and it has this drag-and-drop functionality built into it. We're not just looking at some flat file like PowerPoint. PowerPoint is what you see is what you get. Tableau allows us to explore data through visualization.
We can look at trends. We can find the insights to the questions we're asking. And again, we're telling a story with visual analytics.
On a dashboard, if I open it up and I quickly see something highlighted in red, I'm going to think, oh, something's bad here, and it's going to trigger me to want to dig in for more details. And that's what I really like about this tool and the functionality it gives us.
Now the Tableau workspace has a few things included. One, a worksheet. I know most of you are familiar with this. This is where we're going to be building those bar charts, line graphs, crosstabs.
Then we're going to be putting those worksheets into a dashboard. A dashboard is a collection of worksheets.
And then on top of that, we're going to have the overall workbook, where the workbook is a collection of worksheets and dashboards that we're going to be publishing to the server environment.
Today's focus is going to be looking at a series of completed dashboards, but we're going to see how these different components go into the overall workspace of Tableau.
I want to start off today talking about some dashboard best practices. And it was really nice seeing that poll because a lot of you have had experience with the tool and most likely building a lot of dashboards on your own.
Now whenever I start building a dashboard, I always think about what is the overall story of the data? A lot of times I'll tell a client to open up their dataset, investigate the columns, and figure out what columns are you going to go to first.
Meaning that a lot of times, we want to build a high-level summary of the dataset so people can understand how the data is trending, how things are doing. So this is creating maybe a high-level KPI dashboard.
What that'll do is it'll allow us to at a glance see how we're doing and then drill down to the details as needed.
Now upon doing that, building and creating that overview dashboard, we're going to have to think about what different personas are going to be looking and navigating through this visualization.
Just like on this call, I have some beginners and I have some experts. If the experts were to open up these dashboards, they're probably going to quickly navigate through the view and get to exactly what they need. But if I have a lot of beginners that are looking at these visualizations, they might be confused. They might not know how to navigate, click, filter, and find those insights that they need.
So it's important that we add in instructions and context about the data and how to use these visualizations overall.
Now to me, this is—sorry, just interruptions. Go ahead.
That is probably one of the biggest things for me that I had to learn when I first started getting more into building these kind of workbooks is giving the instructions and context. Because as you're building it, right, you're so in it. You know exactly what you're doing. It makes complete sense to be able to see something and be like, oh, well, obviously you would use this filter to do this or whatever it might be. But allowing others to—not assuming that others are going to be thinking the exact same way you are and giving instructions almost to the point of over-explaining how someone can use it—that would be probably one of the biggest things that I had to learn how to do.
Yeah, I totally agree with you. You know, you and I probably spent forty hours developing a dashboard before, and after we complete it, we're like, that's it. But after spending forty hours, your eyes are glazed over. You can't see if it's good, if it's bad, if others are actually going to be able to utilize it. And I definitely had to learn that as a young consultant at InterWorks, how to upscale this, how to make sure that this is reusable by other end users. So Rachel, thank you for adding in that tidbit.
Also, we're going to see that on a dashboard, real estate is precious. We don't have all the space in the world to share everything. So we want to make sure that we keep it clean. Whitespace is a good thing on a dashboard, but also intuitive. So if you're finding that you need to add a lot of instructions, you need to add details about the data, you can always add in an info button where users can hover and have a tooltip open up and list all those details if needed. So it's more on demand for people.
So let's go ahead and take another poll. We've talked about dashboards and Rachel and I's experience with it. Where do your current dashboards fall short?
So we're going to have a few answers here. Is it bad data? Maybe you just need training on how to build these, standardized formatting, or low engagement.
You all aren't able to see the results yet, but it's feeling like it's pretty divided. Everyone feels like—I think I know what my answer would be of those. I think just being on the data prep side, bad data, right? Data in, data out, kind of thing where if you have bad data, then it's going to be a problem when you're trying to visualize it.
You know, I should have added in one of the responses to be all of the above because I'm sure—
Exactly. Exactly. That's the reason why I said that as well.
Well, Rachel, I think we can go ahead and share this.
All right. Yeah, I think we've got a fair amount of people, and then we'll share the results.
So again, I asked where do your current dashboards fall short, and it is a tie between standardized formatting and training needed. I think that Rachel and I have both been in that seat, one being the trainers of how to instruct people on how to use Tableau, how to build these dashboards, but also being on the client side thinking, do we need a style guide? Do we need to tell people how to start building this within the company? Because it's not one size fits all. It's very specific to your data, to your infrastructure, and all those things. So I think that both of those answers are great.
And then low engagement and bad data. Low engagement, I think, is a big one too because you might have spent all this time building and curating this perfect dashboard that you thought of, push it out to server, and then no one's touching it. Why is that? Is it because you didn't add instructions? Is it because maybe there's too many things in the visualization, in the dashboard, and people are overwhelmed? Or is it because it's slow? Maybe it's a performance issue, and people go to use it and it takes more than ten seconds. Most likely someone's going to press exit and say, no, I don't want to use that dashboard.
So I think that all these are valid answers and what we expected.
Rachel, do you have any comments towards that?
No, that seemed to be what I would assume it to be. And I'm sure, like you said, a lot of the answers where they chose one of the reasons, but I'm sure a lot of them will be multiple things, right? It might be bad data and training needed or something along those lines. So this feels like it fits about exactly what I was thinking.
Yeah, same here. That's great.
So today I want to navigate between looking at some best tips and tricks for you guys, but also looking at a sample dashboard.
So I've built this dashboard using a dataset called Sample Superstore. And for those of you that have used Tableau before, I'm assuming you've used this dataset. You can kind of think about it or think of it as an Amazon store. We're selling different products, and we're trying to see how much money we're making from those products.
This dashboard that we see here is pretty clean and crisp. I can see that it's a regional analysis. I'm looking at different regions across the US and how my sales are doing. I can see how they've been trending over time, my different categories that I might be selling in—technology, furniture, and office supplies—and also some different products here.
Now I did say that this is a nice, clean, crisp dashboard. But Rachel, what's missing here?
Well, I mean, instructions, right? There's no instructions. I wouldn't be able to look at this and know outside of—I mean, I see select the date range, which is very instructive for it—but I wouldn't know how else to interact with it. That's giving me total sales, but I don't know when, right? Just a little bit more help to understand would be helpful.
Yeah, I totally agree with you. So know that you can create something that's nice, clean, and crisp, but again, we need to ensure that we're adding context and we tell users how to utilize this dashboard.
So I purposely took a screenshot of the dashboard without the instructions, but this is something that we're wanting to look for. I can see again that this is a regional analysis. I can come up here and hover over one of these KPIs and highlight information in the view. I'm pulling forward the Central region to know what states are included, how those different sales were in the categories down at the bottom, and maybe what product I was selling down there in the scatter plot.
So again, think about who's landing on this and the story that's being told. You're going to hear me bring up the story a lot because, again, we're on a data journey. We're connecting to some kind of dataset, and we need to think about what persona, what user—whether it's a C-level executive or an analyst—are utilizing this view and what they're going to be searching for.
Let's say I was an executive and I was looking at this view. I can quickly see that the West has the highest sales. I say great. Maybe I'm looking at the South. It's a little lower, only one million. Maybe I want to figure out why that is.
Now I see that there's this highlight function put in, but also I'm going to notice that maybe some of these filters and different items are missing. So what's going to be next is adding in that interactivity and making sure that it makes sense.
Now why is this important? Why should we be using interactivity? Again, I mentioned that this isn't a flat file like PowerPoint. We have the ability to allow our end users to come in and explore and control the data visualization. It's going to give us that customization that we desire because each person is going to want a little different flavor of that dashboard, and it's going to allow for that self-service, which is a really nice thing.
So coming back to the dashboard, how can I add those in? If I was looking at this KPI up here at the top, I probably want to make this a quick filter to where if I click on the South, it's going to filter everything in the view.
I can simply turn on a quick filter by selecting the sheet, and you're going to see this little funnel in the menu bar of that worksheet. And if I turn it on, it's going to allow me to filter this dashboard just for the South.
So again, let's act like I'm the account executive for the Southern region. I'm clicking on the South because I see that my sales are lower compared to the others.
Now I want to keep looking for more and more details. Maybe I'm curious about, I don't know, how is Kentucky doing? It's actually originally where I'm from. I can see that Kentucky has sales of ninety-three thousand, and maybe I want to be able to click on it and filter for more details.
So I see I'm getting more and more specific as to the story or the answers that I'm trying to get to. So now I see just Kentucky sales down here in the bottom sheets, and maybe I'm curious about this outlier way over here in the scatter plot. Global Troy II Executive Deluxe High-Back Manager's Chair. That sounds fancy.
Must be comfy.
Yeah, must be comfy. I'd probably be sitting in it right now. I don't know about you guys, but again, I'm able to click and manipulate this view to find this specific product.
Now we both said that this is comfy. What if we are curious about more information about this product? This is where we're going to want to keep going down that rabbit hole or creating that narrative for our users.
Maybe I want to be able to click on this point and look at some product details. I've already created another dashboard that actually lists out all the product details that we have in the dataset, how many items were purchased, discount, sales, whatever.
We can also create filter links. I'm going to come up to the top to Dashboard and Actions. And I'm going to quickly add in a filter here.
I'm going to say click to view product details about, and I'm going to insert the product name. So it's going to update to whatever product I'm looking at or whatever product I select.
I'm going to ensure that I only select the scatter plot in this view. And the target sheet is going to be that last dashboard that I have, Product Detail Dashboard.
Now I know we're all curious what this high-back manager chair is going to look like. So now if I click on that point, I'm going to see a hyperlink that shows up that allows me to see the details for this specific product. It's going to drill me to that detailed dashboard, and I can see that I sold thirty-seven chairs. I gave no discount, and I made a profit of three thousand dollars here.
So this is really cool about Tableau. Again, it's this nice interface to where I can click, filter, and manipulate the view to answer my specific needs.
Now I'm going to come back to this view really quick. I showed how we could manipulate this singular view to answer a very specific question about a manager's high-back chair. What if I was curious about how a specific state is doing in details instead of looking at one singular product?
I have another dashboard here that is a detailed view of a specific state. Just like I did for that Product Detail Dashboard, I can also create another filter action for this State Sales Dashboard.
So I'm going to do the exact same thing that I did for the product detail. I'm going to add another filter action here.
One of the great things while he's doing that, one of the great things of being able to do this is so that you aren't creating a dashboard that has all of this information in one spot, right? I think Maxwell touched on that already where you can have your high-level information, but you can also have the detail in later dashboards that they can dive into. That way you're not giving too much information for them to try to see all of it on a single dashboard, which is definitely something we've found with working with clients, right? They want the one dashboard to rule them all, but it ends up that we end up having to break it into a couple where there's interactivity between them.
Yeah, and in the last poll question where I was asking where your dashboards fall short, and we said low engagement. If you have a dashboard that has a ton of different worksheets, people are going to look at it and they're going to feel overwhelmed. It's called the cognitive overload, and they're not going to know where to start, where to finish, anything. They're just going to honestly click off of it and avoid it.
And we had one more point in the chat that someone said this also addresses a performance issue, which it can, right? You don't have a single spot that has fifty worksheets on it, a single dashboard with those fifty worksheets. Every time you go to that dashboard, it has to render all of those images, all of those views. So that's a very good point as well.
Absolutely.
So now that I've set up this other action, I'm talking to you guys from Chicago. What if I wanted to see more details about this specific state? Just like with that product, I can click on Illinois. I see a hyperlink to see more details about Illinois. And now I have a state-specific dashboard.
I see that here in Chicago, we're not doing so hot. We have negative profit. I see that I'm losing money in a lot of my categories—tables, binders—and that's a big issue. Chairs, even though I had some high sales in here.
So if I was an account executive, I'd be like, what is happening? Am I giving too high of a discount? I'm unsure.
But what's really cool here is, again, we get to keep digging into more and more details as we see fit.
Now I could add in these actions all day, but I think you guys get the point here. Make sure that you think about the overall story. What are the different pathways that people are going to need to go to, and what views do you need to curate to answer those specific questions? You're not going to answer all of them at first. It's not going to happen. Dashboarding is a very iterative process. You're going to start, you're going to push something to server, someone's going to say, hey, I'm missing this specific sheet or I'm missing that. You're going to add as you go on.
Rachel, before I navigate back to our slide deck, do you have any more points to make?
Don't think on this one, no. I think you kind of covered all of it.
Perfect.
So let's say that we, again, have made this overview dashboard, thought about our users. Now what's next is we need to then get this business ready, ensure that it's ready for an executive or an analyst to view this in the server environment.
This is where we're going to be going beyond dashboarding. We're thinking about how can we implement best practices to showcase our views. But before we do, I want to see what is your comfort level with dashboard design best practices?
So we're going to have Low—I would like to learn more to get better; Decent—I have a good grasp and input what I know into practice; High—You're a pro with UX/UI design, maybe you should be teaching this for me; or Other. Let us know your thoughts in the chat. We're more than happy to listen to that feedback.
If you're high, please teach me some things.
Yeah, same. Absolutely. I'm always impressed. We use a lot of our—we have a design team that is helpful for us as well. I would probably—as much as I love this, I'd say I'm decent, but our design team is what makes it a lot better for sure.
I totally agree, Rachel. I feel like I divert back to being an engineer, and I become very technical, and I want to technically answer everything. But whenever it comes to making things look pretty, I do need that little nudge and a little help once in a while. We need to remind ourselves that color is nice, right?
Exactly.
All right, it seems like we've kind of come to a consensus at this point. So end the poll and share the results?
So it looks like a lot of you say Low—I would like to learn more and get better. And Rachel and I both, as we were just talking about ourselves, we've been in that seat, and at some points, we still are.
I started using Tableau six years ago, and before that, I had never even heard of it or knew even how to pronounce it correctly.
And you know, once you start using this tool over a few months, over a few years, it becomes more natural flow, and you become a lot better at it. And also a lot of you said that you're decent.
So what we're going to go through next is a UI checklist. So let's say that you've answered low, you've answered decent. How can you ensure that you're mentally going to ensure that this dashboard looks good before you push it out without having to try and consult a coworker or someone else?
So I'm going to click off these results really quick, and we're going to look at this checklist. This is actually on our blog. I know that we're going to put this into the chat as well. Feel free to go to this, download the PDF. This is super useful. And actually whenever I create a dashboard, I go through these exact same steps.
So let's say that we're a new consultant or we're new to dashboarding, and we have to build a dashboard. I'm sure a lot of us have built a view much like this one. I know I can say it for myself, and I see Rachel shaking her head. She says, yep, I've built one that looks like this too.
This dashboard is fine. Is it good? Yeah, it's okay. It's not terrible, but it's not great. If I really wanted to impress someone, I don't think this is a dashboard that I want to put forward.
So how can we improve this? How can we go through some steps to make sure that this is going to shine whenever I push this to server? You're going to see on the right-hand side, there's a lot of different things that we can call out. I'm going to go through a few of these, but not all of them. Just know that that checklist that we put into the chat, you can link to it and follow all those design steps.
So the first thing that I start with is I think about what are the things that I need to talk about in this dashboard? Again, I always start with what is the data story, and we need to define the different aspects, the different parts of the dashboard. And that's defining our titles and those different spacings.
Once I do, then it gives me the ability to call out important information. Here I can see I'm talking about asset classes. I see a few KPIs of bonds, equities, and foreign exchange. I have another two areas placed for Industry Performance and Asset Performance.
So now I've created this nice, neat, organized view for people to look at.
You have to think—a lot of us, I'm talking to you guys from the US—we read in a Z pattern. Start at the left and go from left to right and then back down. A lot of times people need to design their dashboard in the same way, so it's natural for people to look at.
Something else we need to consider is also our text size. We need to make our views easy for people to interpret.
Think about your favorite website, whether it's social media, whether it's some golf website or whatever it is. These companies will spend lots and lots of money on their design to make you enjoy the experience, and a lot of that is through text and design aspects like this. We want to implement those same practices here.
For our text hierarchy, we want to make sure that it's simple and about three different weight sizes. Maybe some of you have seen the slide that I'm about to show you next, but you will read this first, and then you will read this, then this one, and you'll read this one last.
I always like showing this because this makes it apparent that text is so important. Your titles should be the biggest and boldest. Then your subheaders after that—tell people what they're looking at—and then following that, give them instructions.
We're going to do a little experiment with our text hierarchy. I can see I have three main things that most likely you're going to be using in a dashboard: a title, a chart title, and some body information.
I'm going to quickly click through these, but you can see throughout time as we start to transform, change different weight sizes, add in some coloring, start to break up this text, and make sure that it's obvious what text belongs where, we can make this very clear as to the story that we're trying to tell. I'm using the same typeface, different weights, and different shades of color to help break up all this information.
This looks a hundred times better than just the plain text being shown on your screen. So try and break up your information in the same way.
Now it doesn't have to look all fancy like this, but I think you guys get the point that I'm trying to make here.
Also, with this text and instructions, make sure that your charts follow a logical placement as well. Again, we want to make this very clean and crisp and easy for people to understand.
Templates can be really useful. One of the polls that I talked about earlier was standardizing dashboarding across the company. Templates can be a great solution for that. Maybe you have a KPI dashboard that everyone needs to land on in an overview. Something much like this one can really help show placement of what's important and then allow people to drill down if they need to. Make this more of an on-demand thing.
And from those high-level to lower-level views, again, keeping that same look and feel so it all looks natural and it's easy to understand.
We also want to make sure that our dashboards are accessible to everyone. We have a good amount of people on this webinar today, and I'm really happy about it. But if I had to guess, someone on this call is color blind. I don't know it, and most of the other people that are joining this call don't know it either. But if the entire dashboard was built in red and green, the people that are color blind aren't going to be able to see the differences like people that aren't. So we need to make sure that we keep that in mind.
Also limit the number of colors you're using in your dashboard. You don't want to open up a view and it look like a circus. I have definitely seen a lot of those dashboards, and Rachel, I know you have too, and it might seem cool, but it's not enjoyable to look at day in and day out. So just be aware and make sure that we try and avoid those things.
There's a lot of websites—again, these will be linked in the blog if you guys want to review it.
After you've thought about all these different UI design tips, ask people what they think. Watch them use your dashboard and lean towards simple. Because, again, I could create something that I think looks amazing. Rachel can go and use it, and she might be lost or confused by something, and I want to know that feedback so I can help improve it so no one else does or feels the same way.
We can spend a ton of time trying to curate something that we think looks great, much like this nice, beautiful paved sidewalk with a lovely little bench where you can sit. People are always going to look for the fastest and easiest route possible, much like these lovely muddy pathways.
So again, think about the people. Ask them to use it and watch them use it.
Much like this one here, right? This was me running to chemistry class whenever I was in college, and I was late and they had to put up a gate so that I would try and avoid it.
Well, if people still jumped over the gate, apparently, in that picture, they were like, no, don't care, jump over it anyway.
Exactly.
We can build something that we think looks really cool, much like this dashboard. It's not useful. There are some KPIs, there's too much text on this screen. We want to try and avoid some of these pitfalls.
You can have a really complex dashboard as long as it's organized. People can follow it, they're going to be able to utilize it and understand the story that's being told.
So iterating is important. We started here, we were able to correct this dashboard, implement some of these best practices, and make this have a great look and feel. You'll have different flavors of it. Maybe you have a dark background. I'm not one to make anything dark, but I do like the light background. But think about this as we're designing. There's a starting point, but once you do some of these design best practices, you're going to help elevate your dashboard for your end users.
And maybe you want to put this into a web portal, which we'll talk about here in just a minute as well.
So I'm going to come back to our dashboard really quick, and I just want to make a few little statements.
We've added in our instructions here. We've kept the same text and weight across all the views.
I'll say go and check the numbers that you have in the view. Is it currency? Add dollar signs just like here. My total sales, do I really need to have five million twenty-nine thousand seven hundred and forty-five? Probably not. My professor in college would be kicking me saying that those significant figures are not correct. Go and make those changes.
Come here—and I don't know why they show me that—change this to where you're just seeing a custom currency, maybe put units in millions. Show that high-level information. So again, this is clean and crisp and easy for people to look at.
It doesn't take that long for you to analyze that checklist and make sure that your dashboard looks great, and you're ready to show this off to anyone.
Now the last part here is after I built this view, I'm ready to push this to server. I'm ready to share this with others. Once I do, you know, you can click through the views, make sure that everything looks good, that you're happy with the look and feel.
But then I want to come up to Server, and I did see I do have one little issue here. I need to fix one of my dashboard actions before I publish it.
My action for my state filter, I said show all values after I leave. But I do want to keep that dashboard just filtered for one specific state.
So once I click on Illinois and I filter for Illinois, now my KPI and my map look good. Perfect.
Now once this is done and I'm ready to share this with others, you want to go up to Server on your top menu bar. You'll need to ensure that you're signed in to your specific server at your company. I'm already signed in to our POC at InterWorks. And then I just want to simply publish the workbook.
I'm not sure why I'm getting an error code. Of course, this is showing up in our workshop. Perfectly fine. I've already published this to server just for this specific reason.
So here I can see that I have my dashboard published. This is what your view is going to look like. And what's great is you're going to have all the same interactions available to you that you did in desktop. I can hover over the KPIs, and it's going to filter for those specific views. I can click and even look at just the Central region.
I can drill down to that specific state. Maybe I want to know how Illinois is doing. So I drill down to the state. I see again how Chicago's not doing so great.
I also want to make sure that we add in buttons so we can navigate back to the overview because different people are going to want to look at different areas. So this is allowing me to navigate, click, and answer those questions as I need.
I'm going to pause here. Rachel, do you have any comments about server or what I just showed here before we go to looking at embedded analytics?
No, I don't think so. I think server is very helpful in actually trying to share it. I think a lot of times we've gone to clients before they had server, and I think the majority of you all have server. But clients have had that before where they're just passing workbooks around, right? And there's no real version control or being able to know what's the most up-to-date one and all of that information. And server is just helpful in trying to actually share and have some engagement in your dashboards, knowing that people are actually utilizing it the way it should be used or just utilizing it at all for whatever purposes they have. So just love server.
Yeah, same here. I don't want to have to create something in desktop and be like, Rachel, I'm done. I'm going to email this to you, or I'm going to put it on Box, and then I want you to download it, and I want you to go and look at it. And then you might have a few comments, and they need to be updated, and we're constantly doing this file share.
Server, this is going to be our source of truth. We're going to be able to land here, know how we're doing, and then log off and be happy with it.
Yeah.
Now I want to display something else, and this is, again, in that Beyond Dashboarding topic. And I want to talk about the overall analytics journey.
So we're going to have a data layer. We're building, we're using some kind of database. That's where all of our data lies, whether it's in Snowflake or it's SQL, whatever it may be. Then we're going to have an analytics layer. In this use case, we're using Tableau to build those dashboards to show how we're doing.
And then we have a presentation layer. So how are we showing this to everyone? Are we sending this to server? Or possibly at our company, do we have different platforms that we're using? Maybe you're using another BI or reporting platform, or you're using some other tool? What if you're having to even flip between multiple servers and your end users are like, I'm confused. Where do I go to see all these different views?
At InterWorks, we do have a product called Curator that puts all these different viewing platforms into one. So let's say that we had Tableau along with another platform. You can log in to Curator and have the same look and feel between all the different platforms and views that you're building. You can create standardized logos, formatting, and even filters to use across all the different views. So again, your landing pages are going to look the same, and your end users aren't going to be confused.
And honestly, this is how you can make your dashboard look really slick.
One last comment: no coding required here. They can be launched in under a week, and you do get support from experts from InterWorks, from everything from working with the data all the way to trying to display that in Curator itself.
Now we saw that view in server. It looks very similar to what we saw on desktop except we have it in an internet browser.
Now in Curator, our view would also look very similar. So I can land on my Curator page, and I'm just going to refresh it really quick.
You can also have a custom load screen, which is really cool. We have a lot of different iterations here. But a user can land on this page and have that standardized look and feel. I have all the same functionality that I did in server.
I can come and look at my map. I can click on a specific state. I can filter for more details and navigate back and forth.
Now in this dashboard, I created navigation buttons in the view. You can also add in that navigation into the Curator portal as well. So it makes this nice, clean, and crisp. And again, just making this more uniform for our users because we want people to use the visualizations that we build, and we don't want to confuse them. And this is a really cool product to help us streamline this and also make us as the creators of these views look great with the story that we're trying to tell.
So I want to take one last poll here. And I'm curious where are you with embedded analytics?
We're not going to share the results here. This is for us being curious. I'm currently using an embedded solution; No, I'm not currently; You're not currently utilizing but you'd like to explore it; or You're not sure that you're ready for embedded yet. So take just a minute, answer this.
I'm actually curious myself to see where a lot of people are.
While that's happening, we did have one question that came in through Q&A that I just want to kind of touch on real quick. It was asking about how do you display your dashboard centered on the server? Right when you were showing your dashboards up on server, it was nice and in the center. And sometimes I have seen it where it's been more left-aligned, and it is a little bit frustrating to do that.
I always thought that it was just kind of like the luck of server sometimes, but it seems in doing some research that if you have any of your dashboards set to automatic sizing instead of a fixed size, then it will left-align them automatically. It'll left-align everything, even if you have some dashboards that are fixed and some that are automatic. If any of them are automatic, then it will left-align. So if you want to show Maxwell what we're talking about there by automatic versus fixed, that might be helpful.
Yeah, so back in the dashboard view, on the left-hand side, you're going to see an option of Size. And we always recommend a fixed size. One, if you select automatic, you're going to see some issues much like Rachel was talking about. As you publish this to server, things might move around, and they might not be centered or in the exact location that we're wanting.
Also, if you're publishing dashboards set to automatic to the server, you're going to slow down the server because Tableau is then having to think about every single device that's loading. We need to re-render the dashboard to make sure that it's going to fit whenever you pull it down from server.
So a fixed size is going to fit most laptops, most computers that are logging into the server and needing to look at that visualization. At a company, I don't expect that you're using a hundred different types of laptops. Most likely you're using some standard flavor, and you can publish your workbooks with those sizes in mind.
Great question, Rachel. Thank you for bringing that up.
We're getting towards the end here, and we do want to give a little more time for Q&A. I just want to say a few follow-up things. So one, after we do end our session today, you're going to get a little pop-up survey in your browser. Take just twenty seconds to answer those questions for us. We really want to know, was this useful to you?
And a few more follow-up things. Also, I showed you Curator here at the end, really cool product, great for our end users. There's a fourteen-day free trial. If you guys want to scan your QR code, feel free to take advantage of that.
Also, follow us on LinkedIn and look at the InterWorks blog. We're going to be posting a recap or a replay to this specific webinar, and also look for our upcoming workshops that we have. We're actually going to host this workshop next month. So if any of your coworkers or anyone else that missed out, come and listen to Rachel and I again. We might not talk about pizza next month, but we'll definitely have a few interesting tips and tricks for everyone.
Maybe ramen, right?
Yeah, maybe ramen. We'll talk about ramen next month. Who knows? We'll just do a different food every month.
We had one question in Q&A that I just wanted to kind of touch on live, and that was a question about if we were planning to do any data cleaning webinars or how to set up a dashboard from already clean data. As Maxwell said, and I think we've posted in the chat and we'll post again, look at that website for our upcoming events. We are constantly adding. I do not think that there is one on the books, but we are constantly adding more and more events onto there, so just kind of keep an eye on that as well as your email for any kind of thing coming through saying, hey, we're going to have a nice data cleaning webinar coming forward.
So all that to say, we are constantly adding new events, so keep an eye out for those. And thank you for the input on what you are interested in seeing in the future.
Yeah, and we want to thank you guys. It's fun that I get to present with Rachel. So Rachel, thank you so much. And we'll sit here and answer any other questions that you guys may have. Otherwise, we hope that you have a wonderful rest of your Wednesday.
And I do see there was a question up there.
Yes, we have a couple. Where does the data structure supporting the Curator dashboards reside? If someone has to use them, what is going to be the data lift for this?
So Curator is a nice visual wrapper for server. So if you have your data up on server and that's where it's living, that's where it is for Curator as well. Curator isn't taking the data away from server. It's just giving you a nice visualization, as well as a nice wrapper around it to make it a little bit more specific to your company, as well as making the interactivity with it a little bit better.
So hopefully that answers the question that we had about the data behind Curator. If it did not, feel free to ask a follow-up question.
It seems, yeah, I think they're answering a lot of questions. I'm glad that you all have been enjoying this.
Yeah, and if we don't get to all your questions, know that we will follow up and answer those specifically for you. I'm just trying to scroll through myself and see if there's any that I can answer quickly on the call.
I did see some on formatting. Absolutely keep formatting consistent. Mine might not have been absolutely perfect, but I hope you guys get the point as to ensure that you examine that and update that as you push out your different views. And look at that UI checklist. Super helpful.
I definitely use that UI checklist sometimes even now, even years later, right? You've looked at a dashboard for so long, and you're like, wait, what was I doing? Because you've looked at that for so long and you're like, what am I looking at? I have no idea. You forget.
You forget.
Yeah, I think we've caught everything. As Maxwell said, we have this chat, we keep this chat, so we'll be able to kind of parse through that and see if there's any specific questions that we missed that made its way through. We were not intentionally ignoring you. We should be able to get back to you.
Well, Rachel, I think that we have hit the end and a lot of thank yous. So again, Rachel, thank you for joining me. To all of our guests that joined this week, we are very thankful for your questions and your time.
Again, we'll host this again next month. So if you guys want to come back and get a refresher or know anyone else, tell them to sign up. Otherwise, we'll see you at the next InterWorks webinar. So thank you so much, and we'll see you soon.