Happy New Year! Welcome back to another episode of the PolicyViz Podcast! I hope you, your friends, and family had a relaxing and healthy holiday season. I’ve got a great lineup of guests coming your way over the next few months and am excited to kick off 2022 with Kevin and Ken Flerlage to talk about their work and experiences in the data visualization field. I hope you enjoy it!

Kevin Flerlage has been in the field of data analytics for over 15 years.  He is a two-time Tableau Zen Master and works as the Manager of Business Intelligence at Unifund / Recovery Decision Science, a financial services and technology company led Zen Master Hall of Famer, Jeffrey Shaffer.  Kevin is an active member of the Tableau Community and frequently blogs about Tableau on flerlagetwins.com, a site that he shares with his identical twin brother and fellow Zen Master, Ken Flerlage.  He is also a Tableau Public Ambassador, has five IronViz top ten finishes and he and his brother are the second and third most favorited authors on Tableau Public (although who holds second or third changes regularly between them).

Ken Flerlage is an analytics architect, strategist, and evangelist with 20+ years of experience in information technology. He is the Associate Director of Data Analytics at Bucknell University, where he is responsible for architecture, design, and development of enterprise data & analytics solutions.Ken is an active member of the Tableau community, a Forums Ambassador, and a four-time Zen Master. He spends a lot of his time answering questions on the Tableau Community Forums, engaging in data visualization discussions on social media, and blogging on www.flerlagetwins.com, a site that he shares with his identical twin brother and fellow Zen Master, Kevin Flerlage.

Episode Notes

Flerlage Twins Website

Kevin on Twitter

Ken on Twitter

Bucknell University

Nadieh Bremer

Adam McCann

Makeover Monday

Jeff Shaffer

Ryan Sleeper


Zen Master



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Welcome back to the PolicyViz podcast. I am your host, Jon Schwabish. Happy New Year, everybody. I hope you had an enjoyable holiday season, a happy new year, and are ready for a better 2022. I think we’re all looking forward to a 2022 where we can go out a little bit more, stay safe, stay healthy, and maybe return a bit to normal. So on the continued season eight of the PolicyViz podcast, I’ve got a great set of guests coming your way with data visualization, data communication, presentation skills, a whole bunch of great guests that I’m excited to chat with over the next few months. If you have folks that you’d like to hear from on the show, please send them my way. Connect me with those folks that you want to hear from, hear about their work, hear about their processes, hear about maybe a specific project that they worked on. I’m always looking for good guests to come on the show. If you’d like to support the show, don’t forget to share it with your networks. Send a review up to iTunes or Spotify or Stitcher or wherever you listen to the show. And if you want to support the show financially, head over to my Patreon page or to PayPal. But all that being said, let’s get on to the show.

On this week’s episode, I’ve got two guests coming your way. I’ve got Ken and Kevin Flerlage, who are the Tableau twins, brothers who work together on Tableau related things. They don’t work together-together, but they do a lot of Tableau stuff together, which I find pretty fascinating itself, as you’ll hear in the interview. We talk about how they got so into Tableau. We talk about some of the challenges that they’ve had with Tableau, some of the successes or lots of successes, I’ll say, that they’ve had with Tableau, and how you could go about using the materials that they put out on their website for free. It’s just an amazing resource that if you are in the area of learning and working with Tableau, I cannot recommend highly enough, because there’s just great material there.

So here is my conversation with Ken and Kevin, I hope you’ll enjoy it.

Jon Schwabish: Hey Ken, Kevin, welcome to the show. I think you might be the first twins on the show ever.

Ken Flerlage: Yeah, thanks for having me.

Kevin Flerlage: Yes, thanks.

JS: Yeah, I’m excited to chat with you guys. So we’re going to get to the whole part about working with your brother in a little bit, because I think that, aside from all the great work you guys do, and also, I should just say, like, making it available for people for free to use, like, the fact that you guys work together is probably the most impressive thing that I could say about you guys, because I’m not sure I could work with my brother on a daily basis. We’ll get to that. So I want to start by talking about your Tableau journey, how you guys got to where you are, I guess, in all senses – in terms of how and why you got to the spot where you are creating all these great dashboards and tutorials and things and you’re putting them out for people to use and open and for free. And then also, we can talk about, you guys as Tableau Zen Masters, and what that is, and Tableau Ambassadors and what that is, because, I’m sure there’s a lot of people out there who don’t know all about that. So maybe I’ll just point to Ken, to get us started, so sort of just a broad open question about your journey to where you guys are now with Tableau.

KF: Right. Yeah. So I started out as a programmer 20 years ago out of college, and I think what was interesting about my career is, as I was building applications, I always had this, my mindset was always sort of focused on making sure that data was inadvertently sort of focused on making sure the data that was being produced was usable and useful for analysis. So I think when I moved into analytics full time, just 2013 maybe it was, sort of a natural place for me to be, and I started using a variety of different data visualization tools at that time. And they sort of, quickly glommed onto them, I just sort of got it right away what the value of it was. And then 2016 timeframe, I was looking for a change, and just sort of noticed a lot of the jobs had Tableau, I was aware of Tableau, hadn’t really worked with it. But I got this job at Bucknell University, and Tableau was a big part of their BI stack, so I thought, wow, I can take an online course or something like that and learn this pretty quickly, and at least be able to be somewhat knowledgeable coming into it. So I did that, I took a course online by Matt Francis, a lot of people know in the Tableau community, and just got the basics of it; and then started to work and jumped right into more of a system type architecture projects. I didn’t really use Tableau at work, but at the same time, I started having kind of these, just these personal questions about data that I wanted to explore. And I thought, well, here’s a great opportunity for me to practice Tableau a little bit, and I knew that I could embed it, so I thought maybe I could throw it on a web page or something like that, and embed this content and just create some sort of interesting analysis, right – politics and sports and a variety of different things that I looked at. And as I was doing this, I really just started to fall in love with Tableau. I loved how easy it was to create some really, really good data visualizations, without having to do a whole bunch of writing code and that kind of thing. But I also love that it allowed me to be sort of creative in a way that I hadn’t been in a number of years. So most of my learning, at least initially, was primarily just doing personal projects; and from there I think, I started to get noticed in the Tableau community. I started doing some things that were maybe a little non-standard things with curvy lines and things like that. And as I was communicating with people on Twitter, I realized that some of the math and things like that involved in that, people didn’t really quite understand. So I just started writing about it, you know, I started writing about how to do these different things, and it was sort of an organic thing where my blog turned into this free help where I was just writing tips and tricks and things like that. And it was never meant to be that, but it just sort of turned into that naturally, as I decided to. So many people helped me along the way. I thought now it’s time for me to sort of turn that back, and help other people as well. So that’s kind of my journey if you will.

JS: That’s cool, yeah. Kevin, your journey?

KF: Yeah, so I kind of was an analyst in Excel, so I kind of started doing that. Ken jumped out of college, and he was more focused than I was. He got a degree in computer science, I was kind of not caring as much as he did. I end up getting a degree in mathematics, focused on statistics. But when I got to college, I didn’t really do much until about – I mean, I did lots of jobs that just weren’t analytics jobs – about 29-30 years old, I started doing analytics, and hyper focused on Excel, you know, get the data into Excel and manipulate it. And God forbid, you had a million rows, you’d be in trouble. So there’s lots of piecing things together. So anyways I’d done that for, I don’t know, 12 years. I start hearing Ken talk about Tableau, Tableau, Tableau, he’s going to this conference, and he’s talking to all these people on Twitter. I used to just kind of – he actually posted a couple of personal visualizations on Facebook, which is a terrible mistake. Because your twin brother comes in and starts poking, right? And so it’s just like pick and fun, and I remember him going to the conference and the teleconference, and that’s, oh, have fun at your nerd conference, again, yeah.

JS: [inaudible 00:08:41] working in Excel.

KF: Right, yeah. So, I mean, I didn’t really do much DataViz, it was mostly numbers, lots of tables, and lots of, you know, and I was pretty darn good at it and successful at it. But it came to a point where I was starting to look for other jobs, just didn’t feel comfortable in the current role, and it felt like there was much room for advancement. So I started looking, and my current company is a large pharmaceutical distributor, one of the biggest companies in the world. And so I look in their analytics, job listings, and Tableau, Tableau, Tableau. I think, I don’t know, 95% of the listings, I looked at said, Tableau. At this point, Ken had kind of been asking me, hey, you want to – I can teach you this stuff, you want to get involved, and I’d be like, you know, go have fun with your nerdy friends. And so, this is maybe six months later I started looking for jobs, and Tableau is on every single listing, and not like, it doesn’t say like data visualization, it said Tableau specifically. So I kind of tuck my tail between my legs and went to Ken and said, hey, can you teach me how to do this. The funny thing is, at this point, I think Ken became a Tableau Zen Master. I think we’ll touch on what that means here in a minute, but Ken became a Tableau Zen Master I think in January 2018. I actually messaged him in February 2018 and said, hey, it’s time for me to learn Tableau, this is via text, time for me to learn Tableau, can you help me out. And his response was, yeah, here’s a great video from Matt Francis. I have an identical twin brother, that’s a Tableau Zen Master, and he wants to have some other dude teach me. So I said, no, that’s not happening. We had a three-hour session one night, and just like Ken said, absolutely fell in love with it. It’s weird, like, in high school, I loved mathematics, I loved art. I should say not just in high school, but throughout my whole life it was mathematics and art, mathematics and art, and this seemed like that perfect combination, when we used to sit there and draw transformers for 10 hours straight. Now, we get to do it with data, and actually, honestly, if you do it with the right data, you can have a huge impact in the world. So yeah, that’s kind of how it happened, and similar to Ken, Ken became a Tableau Zen Master, and I think in a year and a half, I was a little longer, took me like a year and nine months or something like that. So he always holds that one over my head, and so, yeah, that’s kind of how it happened. And ultimately, kenflerlage.com and kevinflerlage.com became flerlagetwins.com, because nobody knew which website to go to for the content they were looking for. So we just merged them and yeah, we got 299 blog posts on there right now.

JS: So before, Kevin, before you got into Tableau, you guys were not working together, you guys had your own jobs, your own thing going on.

KF: We don’t actually work together today. We have our own jobs. But we do a lot of outside work, I guess, the free kind of stuff, the blog – we do a lot of joint presentations and things like that. But we still, you know, Kevin and I still have totally separate jobs from each other.

JS: Right. So I want to just ask two things. You each mentioned something interesting about that journey. So I want to touch on the thing, Kevin, you mentioned, on learning Tableau, you reach out to your brother, a three-hour session, let’s sit down and let’s hammer this out. And I had a similar experience learning R where I had a colleague of mine at Urban, Aaron Williams, I said, Aaron, can you just sit down with me for two days and teach me R. And not everybody can do that, not everybody has a twin brother where they can, you know, who’s a Zen Master and say, hey, can you teach me this thing. But do you find that one on one, for some pretty, I mean, even three hours is a pretty extended amount of time to have someone sitting next to you, helping walk you through the ins and outs of, in this case, Tableau?

KF: I think it’s special for Ken, and I because we are identical twins, we have the same DNA. Right? You know what I mean? We think alike. We’ve always thought alike. Yeah, we’re very different people, but we’ve always thought the same. So to have your identical twin brother who’s very knowledgeable, teach you how to use the product, yeah, I mean, I can’t imagine anything better than that. But I mean, after that session, we didn’t have any of these long drawn out sessions. He wasn’t teaching me every day. He wasn’t doing that, you know, what I ended up doing is going through the Matt Francis’ Udemy videos, so that were nine or 10 hours of content. So even though he introduced me to it, and helped me along the way a ton, probably a big chunk of my learning was just watching those videos and trying to replicate what he was doing, what Matt was doing in those videos. So yeah, I mean, I think there’s – I think lots of people learn really well by that one on one. I think a lot of people learn by watching videos. We hear that all the time. I personally learn better now that I kind of got a base of knowledge through blog posts. I prefer reading a blog post, because I can skip what I want and get to the point, you know what I mean. So, I mean, if you are going to pick the ultimate way to learn, three-hour session from your identical twin brother, yeah, heck yeah. But I think I learned lots of different ways, and I think a lot of people would say the same.

KF: I mean, at work, I mean when I – we try to operate very much of a self-service type of environment, where people, you know, we help people to learn the tools and prepare their data, and then we give them the basic training, and we let them go. And so, I do a very similar type of thing with new Tableau users at work. I sit down with them for maybe an hour and a half, give them that sort of crash course, here are the basics of using it. And then usually follow up with one or two other additional hourly sessions, and then they’re off and running, and they know my name, they know how to get a hold to me, and when they need help, they reach out or we set up a time to collaborate on something. But generally speaking, I find that works really well. It’s just to give them that real quick sort of crash course, get them in there – because to me, the only real way to learn anything is to get your hands dirty, to really get good at anything is to get your hands dirty, get in there and try things. So that’s always my goal is give them the basics, push them out there, and then let them learn by just doing things, and then come back to me when you have questions or need to fill in those gaps.

JS: And for you, when you’re doing that, like, I totally agree, you got to get over that initial hump of something, so in that hour, hour and a half session, what are those initial things? So if someone’s listening to this podcast right now, what are the, I don’t know, whatever, six, 12, 100 things that gets them over that initial hump, so that they can really start building some stuff?

KF: I think the core concepts of Tableau and sort of terminology is introducing the basic data model, and then what we call things, we call them dimensions and measures, and then, it’s talking through the difference between a green pill, a continuous pill, and a blue pill, a discrete pill, and how those work differently as you put them on different places on the Tableau pane or whatever. And then it’s introducing the rows shelf and the columns shelf as well as the marks card, and what all these things do, and then, ultimately, how, when you bring all those pieces together, you’re able to create kind of anything you would like to create or anything you could imagine. And usually, I show people some basic how to build basic charts with a bar chart, a line chart. But the key thing is those foundational types of things that you use, because Tableau, you know, everything you build, you’re using green pills, blue pills, the rows shelf, the column shelf, and the marks card, I mean, everything. And there’s not really anything you’re doing outside of that necessarily. Right? So once you understand those core concepts, and understand how they all work, that’s the basic pieces that you need there to move forward.

JS: Yeah, getting that lingo and that jargon down.

KF: Yeah.

JS: Ken you mentioned something earlier that I wanted to get back to too, because you said you’re building some things, you’re publishing some things, and you sort of got notice in the community, and then it sort of, you know, build from there. I get questions every once in a while, especially from younger folks that are like, how do I, quote-unquote, get famous in the data visualization field, and unlike, well, first off, famous in the data visualization field is not like, that’s not really a – famous is not a thing, but like, when – because my answer is going to be, I think, the same as what your answer is going to be, but I want to give you just a, and both of you really, because you both have this platform and this website and this blog where you are known as leaders in the Tableau field. So when someone would come to either of you and say, hey, how do I get noticed, or, how do I get famous in DataViz field, like, what would your response be to that kind of question?

KF: I mean, I think my initial concern would be, if that’s the right – I don’t think that’s the right goal, right? I don’t think getting famous – if you want to be famous, then don’t do it in the DataViz [inaudible 00:18:30]. There’s a finite group of people that are going to be able to be fans. And I just think, generally speaking, that’s the wrong perspective. If your goal is to get really, really good at, and I’ll talk just more generally around data visualization, if your goal is to get really, really good at data visualization, so that you can have a great job in the field or create beautiful pieces of data, art, thinking about like Nadieh Bremer, and some of the stuff that she does, that’s a good goal. Or a goal of getting really good, and then helping other people to get good, that’s a great goal as well. Getting famous, I have had people ask me that, and I’ve given this advice to them, and I will say that the people who want to get famous, they usually don’t, right? Because they just don’t think it’s the right – I don’t think that’s enough of a drive in this to get really good at it. And that was certainly never, I don’t know that we’re famous, maybe within the Tableau community we’re famous, but it was never a goal for me. I mean, I wanted to get good at it for work, but I also started to love it, and I just wanted to get good at it so I could create the thing that I saw other people doing. Adam McCann was one of the big people, like, how can I create these crazy things that Adam’s creating, and I just wanted to get to that point, just for my own development. And I think where we started to become well known was that when we started to share that knowledge with people freely and openly. You go to our website, we make $0 off of it. There’s no advertisements. That’s just, you know, it’s purely there because we love the stuff, and we want to help other people to learn it and get better at it. And yeah, so the goal was never to be famous, and I just think that’s the wrong sort of perspective coming into this.

JS: Yeah.

KF: But if you agreed 100% with Ken, but if you want to grow a following, you’re going to have to share content, you’re going to have to help people, you’re going to have to put blog posts out, you’re going to have to create interesting visualizations, you’re going to have to create some techniques that maybe people have never seen before. So I 100% agree with Ken, the goal shouldn’t be to be famous, but there is some idea of, if you are going to be, you know, create your own consultancy company, and you wanted to be able to grow your business and be kind of known for your skills, I mean, there are ways to do that, and I think, like tessellation run by Luke Stanke, another Tableau Zen Master, he’s done a great job of building his company through sharing lots of free content, visualizations, lots of blog posts, and all that content is free on his website. So I think there is some level to not necessarily being famous, but to building your credibility in the DataViz community.

JS: Yeah, right. And not that that…

KF: [inaudible 00:21:54]

JS: Right, building your credibility, not so much like doing it to get that following to be famous, but that following shows up because you’re producing good stuff that people can use.

KF: Right, exactly.

JS: You both mentioned a whole bunch of people so far that you utilize…

KF: Sorry.

JS: No, it’s great. I’ll put links to all these folks in the show notes, so people can check them out. And that is one thing about the Tableau community, that regardless of whether people like Tableau or don’t like Tableau, use it or don’t use it, I mean, I think everybody can agree that there’s a very active Tableau community. And so, I wanted to ask you quickly about the Zen Master program and the Tableau Ambassador program, because you’re both, both of those, and how that, how you sort of view that as part of this bigger Tableau community. So Kevin, if you want to take a shot at describing those two, to start.

KF: So first off, the Tableau Zen Master program and the Ambassador program are both real things. That title of Tableau Zen Master, when I first heard it, I thought it was like somebody gave themselves that title, and that’s not exactly true. It’s actually a program run by Tableau. It’s basically, at Tableau, I think they call it the recognition program. So there’s kind of two levels that, Tableau Zen Master and Tableau Ambassadors. Tableau Ambassadors, there’s six different arms of it. Now I think Tableau Public Ambassador – Tableau Public is the free kind of version of Tableau that you can use and publish visualizations on the public page. Social ambassadors, forums ambassadors, Tableau Forums, where people can ask questions, and people like Ken especially help people get the answers to those questions. CRM, there’s like six different branches of Tableau Ambassadors, and how it works is essentially people in the community – they open up nominations, people in the community may say they mean Tableau – but people in the community will nominate others, and then Tableau ultimately selects a group of people to become an ambassador. Ken is a Tableau Forums ambassador, I’m a Tableau Public ambassador. Ken’s been that three or four years, I’ve been for a couple of years. I think, in total, there’s a couple of hundred Tableau, maybe 300 Tableau Ambassadors, they even have student ambassadors as one of those arms. So I think there’s 300, there may be 400 Tableau Ambassadors, and all in these kinds of different areas. Tableau Zen Masters are kind of the same general idea, so there’s far less of them. So the idea with, again, they open a – Tableau opens up nominations and peers nominate people, and say why they should, but they have a really specific criteria for that. First, you have to be a master of Tableau, and that could be a master of the core product or the Tableau server or some other aspect, but you have to be a master of Tableau, you have to be a collaborator, you know, work with other people, help other people, collaborate with, you know. I can get into it a minute, momentarily, but collaborate with the development team of Tableau. And then, third is to be a teacher, doesn’t mean that you’re sitting in front of a class and teaching, but it means you’re doing something to help others learn, writing blog post. I’ll mention another name, Tim Ngwena is another Tableau Zen Master. He has a great YouTube channel, so he does lots of videos, especially on new features. So those types of things where you’re actually teaching people, so if you can kind of cover those three categories, people will nominate you and Tableau will choose you potentially as a Tableau Zen Master. In total, I think the program have a visualization on this, I think it started in 2012, and total has been 90 unique Tableau Zen Masters. Right now, there are 41 plus 12 Hall of Fame Tableau Zen Masters. I’m lucky enough that I had, before I even started, before I even downloaded Tableau to have an identical twin brother as a Zen Master, and then six months down the road, I started working for Jeffrey Shaffer, I think you know Jeff Shaffer, I still work for Jeff. So six months after starting to learn Tableau, I start working for Jeff, who is currently a Hall of Fame Tableau Zen Master. So that’s kind of how I selected, like I said, with the Hall of Fame Zen Masters, there’s 53 in the world. So it’s a huge honor, and we get to do lots of cool stuff, like, get some insights on what’s coming up, you know, what’s future enhancement looks like, and we could provide feedback on that. So it’s really cool, because we are able to help others, we will also help shape what that product looks like down the road.

JS: And to be clear, the Zen Master title is every year, it’s not like you’re a Zen Master in 2020, and you’re necessarily a Zen Master in 2021. You need to go through the whole nomination process, and I would guess, there’s like an application or whatever you have to submit to do it every year.

KF: You’re right. That’s exactly right. Usually, the ambassador program starts nominations in the summer, and then Zen program starts nominations early in the year, usually in January. And you’re right, it’s a year. So if you went, you’re a Tableau Zen Master, and I just did absolutely nothing, I disappeared off the face of the earth, I probably wouldn’t be one the next year, yeah.

KF: The exception to that is the Hall of Fame after…

JS: Right.

KF: If you qualify for Hall of Fame, if you’ve been the Zen for five years, I think, and then you still have to kind of be inducted or nominated or something like that, and then, but then you’re sort of Hall of Famer in perpetuity.

JS: Forever, yeah. Although the unplugging for a year does sound kind of nice [inaudible 00:27:47]. So we talked about your sort of personal journeys for a bit, but I want to make sure we talk a little bit about dashboarding, in general. So I want to ask you just a couple of questions about dashboarding before we wrap up. And I’ll start maybe with Ken. So this is a maybe a loaded question, I don’t know. But like, how would you define a dashboard?

KF: Well, I’m going to pass this one over to Kevin [inaudible 00:28:15]

JS: Wow, look at that.

KF: I think there’s a natural end, because I’m going to talk about the big book of dashboards. So if everybody doesn’t know the big book of dashboards, it was written by my boss Jeffrey Shaffer, Steve Wexler, and Andy Cotgreave, boy, I guess, it’s been out for, I don’t know, five years or something. And they tell the story all the time about how they started to write the book, and the very first step was what you just asked, how do you define dashboard, what is a dashboard. And they tell, I think it’s Steve that usually tells the story, and it’s just really interesting to hear them kind of go back and forth, and they said, they talked about it for hours and hours. Before they could even write a word, they had to figure out what that definition is. So I’ll read it word for word, a dashboard – this is what they end up landing on – a dashboard is a visual display of data used to monitor conditions and/or facilitate understanding. I think that’s an excellent definition. The truth is that could be an interactive display that allows exploration, that’s kind of what I do on a regular basis. It’s a dashboard. I can hover, I can filter, I can highlight different things, right? It’s interactive. I can drill down. But from that definition, it can also be just a PDF that’s emailed every day, just have certain KPIs on it. It could be, these kind of examples they use in the book, you know, you’re in a call center, and you have this gigantic big screen on the wall that just shows certain metrics in real time. Right? That can be considered a dashboard as well. For me, when I say dashboard, I think of that first one the most, an interactive display that allows exploration. But could you call a static infographic a dashboard? Probably. So yeah. Ken, anything to add to that?

KF: Yeah, I mean, I guess, I just tend to sort of try to separate the concept of a dashboard from a data visualization. I feel like dashboard is sort of a subset of data visualization and data visualization, I think of as a sort of a broad category that obviously would include dashboards, but also other things like infographics or data stories or even data art. So, to me that data visualization is that broad category, dashboard is a something a little bit more specific, and I think we tend to think of dashboard as being something sort of business centric. Right? It’s something you use from a business perspective. And I think in the vast majority of cases, I think that’s a fair statement, maybe not always, but I think it makes sense to think of it in that context.

JS: Now, interestingly, you use that phrase, data stories, because that was actually my next question. So the field throws – the people in the field, sort of, throw that word around a lot, the word story and storytelling. How do you think about telling data stories, and how do they merge with dashboards? Because I feel like a lot of people say, oh, I have a dashboard, I’m telling the story. And it’s like, well, you’re really just, and if we go back to the definition Kevin just read, it’s like, you’re really just letting me monitor this information, or, I’m just understanding these KPIs. But like, that’s not a story, that’s just like letting me explore the data. So how do you think about, I guess, dashboarding versus or encapsulating stories?

KF: Yeah. So this is an interesting trend, and I think it’s important that the end result be some sort of story, right? There needs to be some sort of insight that that helps you to then – that leads to some sort of action being taken. And, I guess, you could call that a story, but I don’t always think that it’s our job as data visualization or dashboard developers or creators, I don’t think it’s necessarily our job to reveal that story. I think a lot of the dashboards that I create, that a lot of us create, and at least from a business perspective, are those exploratory dashboards where you’re building that in a way that sort of makes the data easy to find insight, you’re visualizing it in a way with chart types and different techniques that make it easy to sort of extract those insights; but you’re not necessarily going that next step and extracting them, you’re just providing the tool that allows other people to do it. So I might push that tool out to a broad audience, and each of them is going to develop their own insights or their own stories from it, right? And I think, in a way, that’s a little bit more powerful than if I tried to just focus in on this one story. I think me focusing in on that creates sort of a narrow view of that data, whereas allowing people to find their own stories in that data and that dashboard that I’ve created, can be more effective. And those are the people that work in their division or their department, that really know their business processes, and they’re going to interpret the data a little bit differently than somebody else. And it’s going to create, sort of different types of insights. I do think there are times when telling a very clear story is important, but ultimately, it’s kind of the role, you know, am I developing something for other people to find those insights, or am I the actual analyst that’s working in that department digging into this data and trying to figure out where a problem is, or where an opportunity is, and in that case, telling that story might be really important. But I think a lot of us are kind of further upstream, in that we are building these things that are meant to be tools for other people to find those insights.

JS: Yeah.

KF: I’ll tell you Ken and I are identical twins, because it’s the exact, I mean, like, word for word, my answer. I was going to just touch on one thing is, I’ll mention another Tableau centric thing is Iron Viz. Iron Viz is this big competition, a data visualization competition within Tableau that they do every year. They have a feeder competition where they give you a topic, and you create a visualization, and they judge it on three different criteria and then, ultimately, you get to the finals they just had this last week, you get to the final and you build a visualization in 20 minutes using some set of data. Now, you get to do a lot of prep work, so it’s not just like two bar charts or something like that. You get to do a lot of prep, working a lot of practice. But the criteria for that are analysis, design, and storytelling. And I always got a little bit analysis of design, yes, makes perfect sense. I always got a little bothered by the storytelling, because you don’t always need to tell a story. Right? So I always wanted to suggest to them to change that to insightfulness, to where I could tell a story. I’ve done Iron Viz about when Napster basically killed music for years and years and years. In that I told a very, very specific story, but I think that there should be just as much opportunity for a winner to have a dashboard where you can extract your own stories, like Ken said. In business, the manager is going to be looking and probably getting a different story than the CEO of the company. So I love the idea of just it being not necessarily a story, but just being insightful, and to be able – to get your own story by digging through that dashboard, that digital [inaudible 00:36:14].

JS: Yeah, to facilitate understanding, right, like?

KF: That’s what Steve Wexler says all the time, greatest amount of understanding, facilitate understanding.

KF: And just like the word dashboard, right, I think this is just something that we probably need in the data visualization community as a whole. We need better definitions around what do we mean when we use that word storytelling, right? Is it specifically kind of telling a narrative story about something that’s going on, or, is it something broader than that? And I’m sure people have worked on those definitions, but I think it’s often kind of unclear what we mean when we use that term.

JS: That’s a really interesting point, right, because if you think about when you say the word dashboard outside of the date of his paradigm or field, you might probably think about the dashboard in your car, and that’s not telling you a story, it’s just, it’s giving monitoring information for you. And that’s not really a story. You could tell a story around that, I drove really fast for a while, then I slowed way down, and because of X, Y, and Z, but that itself is not a story, that’s an interesting way to think about it, yeah.

KF: We can probably blame that for all the gauge charts that we see all over the place.

JS: That right. So the Tableau Conference was just a few weeks ago. You both did a talk on making better dashboards; and those videos are all recorded, and they’re all free, so I’ll link to them, so people can go over and watch the full talk. But I was wondering if you could share maybe your top two or three or four or six, whatever it is, your, like top tips for making better dashboards, like, what should people have in the back of their heads as they’re making their dashboards?

KF: So yeah, that presentation was, I guess, loosely based on a blog post I wrote about a year and a half ago called Simple Steps for Better Design. It was kind of started off as my sort of pet peeves of data visualization, just things that I always saw people doing regularly that I just wanted to help them fix. And this is actually lots of input from Ken, and from Jeffrey Shaffer, especially. So this really ended up with 26 different things, do this, don’t do this, right? In the Tableau Conference presentation, we showed a lot of these good design tips, we also showed a bunch of cool Tableau tricks, I think they’re cool, and sounds like, based on the feedback, they were cool. But in regards to design, if we’re going to just kind of hit on the top ones, things like removing clutter, using color intentionally rather than categorically coloring things or that making sure you have a whitespace. I mean, this seems obvious, but using easy to read fonts. We also touched on color palettes, so if you’re going to use a diverging color palette, you really have to have a sort of natural midpoint. Right? You don’t just run from sales from $500 up to $2000, and make a divergent color palette, because where’s that middle point. It should be a target, should be a zero point. And then, really just to design a clean user interface that allows for easy to use interactivity, and that’s what we really did was take kind of a crummy dashboard and make it a better dashboard, both aesthetically and as you actually interact with it. And one little kind of tip that we always use, and this is what we show in that presentation is specific to Tableau but could be implemented in any software is the idea of, if you have a stacked bar charts, I don’t love stacked bar charts, but sometimes, if you have maybe, like a pie chart, if you have two colors or whatever, then I think it’s okay. But one thing that I’ve always done, and I learned this, I mentioned Steve Wexler’s name a bunch, but this is originally from Steve Wexler, kind of improved by Ryan Sleeper, another former Zen, but with a great blog. But the idea of taking a stack bar, and if I have blue on the inside and gray on the outside, we can measure the total, we can easily measure the blue because it’s along the axis. But what if we want to compare the grades, right? Well, the trick is really to add some interactivity to allow user to click on the gray, and it sorts of back to the axis, so now you can compare the gray. You compare the gray, you compare the blue individually, and you can control the total. Otherwise, they are kind of starting at different points, so it’s really difficult to compare. So I feel like that could be applied in any software, we show it obviously specific to Tableau. So I think that’d be the biggest key points. We didn’t go crazy technical, like, we have, you know, we’ve done presentations at the conference about trigonometry and building charts using trigonometry, which is highly complicated. This was kind of simple and really helpful to just about any level of user.

JS: Right. Okay, so one last question before we go. Go ahead.

KF: I was just going to say, I think the key word I would use is, this is something Kevin and I talk about all the time, is polish. And by polish, we mean, you built the dashboard, it’s 95% there, it’s functional, you can theoretically put it out there, and it would work. But it’s that last sort of 5%, it’s those few extra steps that you can really sort of clean up, enhance the user experience, provide tools, techniques like that, clicking on the stacked bar chart that really help to sort of draw out the insights, and just generally create something that people want to spend time interacting with. So I think this was largely all about, if I summarize, it was largely all about those steps that you can use to add polish to the dashboard before you deploy it.

JS: Yeah, that’s great. Before we go, one last question. So what is it like working with your brother? Like I said, I don’t know if my brother and I could.

KF: It’s great…

KF: We love it…

KF: I mean, I’ve never had… We are identical twins. Like I said, we share DNA, we always got along really, really well. We’ve had no problems, I mean, like Ken said earlier, we don’t actually, you know, in business together, and maybe that would never work, I don’t know. But doing presentations and blog posts and really collaborating on so much, you know, creating visualizations together, we do that as well, we’ve had very little drama. I mean, we might argue, who’s more handsome, which is clearly me, and he always gets the nod for the smarter one, because he’s more focused. But yeah, it’s been great. And the cool thing is I don’t think we really touched on it, but I’m in the Cincinnati area, Ken lives up in Pennsylvania, he chased the girl up there 20 years ago, and that first, well, for the bulk of that 20 years, Ken and I weren’t all that close, we didn’t talk that much, we just kind of separated. And Tableau, this sounds mushy, but really brought us back together. And it’s a 100% true. We talk literally every day. We got a Slack channel together, just him and I, and we talk all day long, every day, and it really made us way more tight than we ever were. So yeah, I mean, in a weird way, Tableau really brought us back together to being best friends.

JS: That’s great. That’s great. That’ll be the next Tableau thing. They’ll have Zen Masters, ambassadors, and love stories, or something like that.

KF: [inaudible 00:43:51]

JS: Ken, Kevin, thanks so much for coming on the show. This was really interesting. I think you provided a ton of resources that I’ll link to on the show notes page for folks; and, of course, they can check out your site and also check out the talk and the blog posts from the Tableau Conference. So thanks, guys, appreciate it. Have a great holiday season and enjoy hanging out together in real life.

KF: Thanks, Jon.

KF: Thanks Jon, appreciate it. Thanks.

Thanks everyone for tuning in to this week’s episode. Hope you enjoyed that. I hope you are ready to kick off 2022, I hope you’re going to have a great year, and I hope you’ll tune back in to the podcast as I bring you more great guests over the next several months. So until next time, this has been the PolicyViz podcast. Thanks so much for listening.

A number of people help bring you the PolicyViz podcast. Music is provided by the NRIs. Audio editing is provided by Ken Skaggs. Design and promotion is created with assistance from Sharon Stotsky Ramirez. And each episode is transcribed by Jenny Transcription Services. If you’d to help support the podcast, please share it and review it on iTunes, Stitcher, Spotify, YouTube, or wherever you get your podcasts. The PolicyViz podcast is ad free and supported by listeners. If you’d like to help support the show financially, please visit our PayPal page or our Patreon page at patreon.com/policyviz.