Become a Creator today!Start creating today - Share your story with the world!
Start for free
00:00:00
00:00:01
Episode #156: Ben Jones
156 Plays5 years ago
Ben Jones is the founder and CEO of Data Literacy, a training and education company that’s on a mission to help people learn the language of data. Ben is a highly experienced and passionate instructor, having taught data to thousands...
The post Episode #156: Ben Jones appeared first on PolicyViz.
Recommended
Transcript
Season Conclusion and New Beginnings
00:00:11
Speaker
Welcome back to the Policy Vis Podcast. I'm your host, John Schwabisch. Everyone, this is the final episode of the podcast for the season. That's right, I'm wrapping up the sixth season right now so I can get on to vacation and enjoy some quiet time, gonna do some writing, gonna do some reading, maybe even make some data visualizations. We'll have to see.
Career Shift: From Tableau to Data Literacy
00:00:30
Speaker
So to help me close up this season of the show, I invited Ben Jones over to chat with me about his new project on data literacy. Ben Jones, as you might know, worked for Tableau for a very long time and now he recently left the company and started his own venture
00:00:45
Speaker
to help people understand data visualization, understand data, understand analytics, even a little bit more. And obviously data literacy is something that's near and dear to my heart as I spend a lot of time in my workshops helping people understand how to read lots of different data visualizations that are probably familiar to you and me, but maybe not to everyone. And so part of the goal, I think, of becoming better at visualizing and communicating data is to understand some of these other and new graphs that people can use.
00:01:15
Speaker
So, Ben and I talk about his experience at Tableau, his new project, and lots of other things that are going on over there on the West Coast. So, I hope you'll enjoy this week's episode. So, here is the final episode of this season of the Policy Vis podcast, my interview with Ben Jones.
00:01:35
Speaker
Hey, Ben. How are you, man? John, doing well. How are you? I'm good. I'm good. How's the West Coast treating you? It is great. We got some early sunny weather out here. Absolutely. Really? Is it like this? Is this like the one week that Seattle doesn't rain?
00:01:48
Speaker
You know, may has been gorgeous. I'm supposed to tell everybody, my neighbors remind me that, yeah, it's constantly rainy. So you don't want to ever come out here and move out here. We've had some good, always terrible. We've had some gorgeous days. I gotta say I'll take it. You know, but yeah, I'm enjoying it. I love the West coast. I've been out here for so long now. Yeah. Well, so, so tell me, so I know you do a ton of hiking.
Balancing Digital and Outdoor Life
00:02:10
Speaker
So where have you been and camping? Where have you been lately?
00:02:13
Speaker
Yeah, so it's sort of just getting started. A lot of the mountains are still frozen and whatnot. Just this past weekend went out to this really actually an amazing hike. It's about maybe an hour sort of north east of downtown Seattle. It's called Bridleville Falls and Lake Serene. And what I love about it is sort of has three things, usually one or two of which you hope to have on a hike, which is an amazing waterfall, a great mountain view, and then an alpine lake. And it has all three.
00:02:39
Speaker
That's great about it, but because of that, that means Memorial Day is basically like Disneyland with the Lions and everything. It was a busy day out there on Monday for sure, but we enjoyed it anyway.
00:02:50
Speaker
That's great. I'm actually doing this wonderland trail, which is going to be wild. I'm actually doing 10 days off the grid all the way around Rainier starting at the end of August. Yeah. Going through over labor day. So it's a pretty cool, you know, like 93 miler and you're out there for a while, you know? So hopefully I come back and civilization is still going. I don't know. I'll find out. So that's the sort of thing you feel like you need to train for. You just sort of go out there. You're already good to go.
00:03:16
Speaker
Yeah, that one, it's got about 22,000 up and down total. So I probably, I'll be spending some time on the trail with at least like a moderately weighed down pack just so that I don't kill myself on the second or third day. But it's not like extreme. Like if you're going to say maybe like go to the top of Rainier or one of these other, it's just, you know, you don't ever go above 6,500 feet total. So it isn't like a mountaineering scenario. It's a trail the whole way. So there's no technical aspects to it. It's just, you know,
00:03:46
Speaker
I have no idea what I'll feel like on day 10 of not having a shower or plugging anything in or whatever. So I'm looking forward to it. So I think the moral of the story is if anyone is into hiking and camping, when they visit the Northwest, they should just call you up, right? Yeah, absolutely. I'll take them out. I love it. It's a great way to balance out the digital side and all the data. You know what I mean? Yeah, absolutely.
00:04:08
Speaker
So why don't you tell folks about yourself? What's going on? You have a whole new company and project going on. And so maybe for folks who don't know who you are, maybe dive back a little bit further. But I'm really curious about the data literacy and all the work that you're doing now.
Journey to Tableau and Community Building
00:04:25
Speaker
Yeah, sure. So the quick version of it is I joined Tableau about six or seven years ago. I came up here to the Seattle area from Los Angeles where I was a data blogger and using data kind of in a Six Sigma kind of a context in a medical device company down there. And they kind of caught wind of my blog. Also, I was in the Iron Viz contest and I got to meet them.
00:04:47
Speaker
And so they brought me up to manage the Tableau public platform for the last five or six years, you know, which was such an awesome gig for me. That thing grew by 20 fold over the course of my time there. And just got to see so many amazing visualizations, interactive data saw the, you know, the wave of data journalism and then also mobile and really got to be I felt like in a position of
00:05:11
Speaker
Seeing a lot of amazing people's talented work coming across that platform and just being part of a community that was growing and thriving. So it was really nice for me. I transitioned into an evangelist role and was doing a lot of presenting for companies over the past year. Well, early on when I moved up here, I published communicating data with Tableau, which is the O'Reilly book.
00:05:31
Speaker
Then because of that got looped into some University of Washington continuing education courses on data visualization theory and just fell in love with the teaching side of things and started to notice in my conversations with people in the evangelist role that there was just this massive gap where so many people felt like they're being left behind this data revolution where they didn't really feel like they could understand what was happening,
00:05:57
Speaker
like they could participate the concepts all the visuals and there's so many people out there that didn't receive a formal education you know people in the nineties that went to school like me this really wasn't covered i mean you know right courses we were in uh i was even in a technical course in engineering and and came nowhere near you know learning
00:06:17
Speaker
the sorts of things I need to know to be able to work with data to the degree that our careers, our communities, even our personal life requires of us nowadays. That's where I started to see, oh, this is actually a major need. I think that Tableau does a great job, as many vendors do, helping you learn about data through their tool, and that's really great. But I felt like it would be a good opportunity for me to step into a scenario where I was able to teach people the concepts like,
00:06:46
Speaker
you know, simple ones like how to read and interpret data visualizations or how to dive in and clean dirty data or visualize it themselves or communicate it. So that's
Founding Data Literacy LLC
00:06:56
Speaker
what I've been doing. So back in December, I left Tableau and started up Data Literacy LLC at dataliteracy.com. And I've been teaching my own classes and programs, working with some companies, working with some individuals.
00:07:07
Speaker
And yeah, just learning a lot about what it takes to help people become comfortable working with data. I call them, you know, there's so many data-phobic people out there. They really, you know, the worst thing you could do is send them a spreadsheet or something like that. They really wouldn't, you know, kind of feel confident enough to make good use out of it. So yeah, that's sort of what I've been doing these days. It's been a real fun first, what is it, I guess, five or six months now out of the gate. And yeah, learned a lot already, but having a good time with it.
00:07:35
Speaker
That's great. So are you focused on both the data side of understanding how to get and use and clean and understand data and the statistics that one might need to do at least some basic descriptive analysis and statistics and then also the visualization and then into the storytelling part of things?
00:07:55
Speaker
Exactly. Yeah. So I had a lot of people when I first started this, they were saying, well, isn't data literacy, you know, just being able to read charts and graphs, like that's what literacy is, right? And so early on, I thought about that. And, you know, really felt like it's more than that. Because if all I can do is
00:08:11
Speaker
try to make sense of a visual someone else has created. I think I'm sort of at the mercy of that person to some degree. Maybe there were errors in the underlying data that I can't see just by looking at the dashboard or maybe if I were to get my hands on the data myself and look into it, I might have some additional questions or my insight might develop further.
00:08:33
Speaker
I very much became a believer that to me, someone who's highly data literate also knows how to work with data, find its issues and anomalies, uncover patterns, and then actually be able to take it from there to a situation where they can convey those insights to other people effectively. For me, that's what's so beautiful about it is because maybe there's someone who's been a specialist in data engineering,
00:08:58
Speaker
or who really fancies themselves an expert data storyteller. But oftentimes when I talk to those individuals, they don't feel like they know the full spectrum. They don't feel like they know what people upstream or downstream in this data working process when they actually do or what those concepts are. So even for specialists and experts in one part of that process, I've found that they have this desire to learn what else is going on in the data world.
00:09:26
Speaker
So they can speak more effectively to people in their organizations that are involved in other pieces of that puzzle. There was a medium blog post a while back, and I'm now forgetting who wrote it, but it was on data literacy and the writer, I'll look it up and put it up in the show notes for people, but the writer had made this point that when it comes to reading words, you were either literate or illiterate. There is no in between. And then the article went on to make the case the similar thing for data. So do you,
00:09:55
Speaker
I know I'm asking this question sort of out of the blue, but I'm wondering whether you feel that that's the same way that when it comes to data, you're either literate or you're illiterate.
Rethinking Data Literacy: Spectrum vs. Binary
00:10:03
Speaker
No, definitely not. I think there was a blog post maybe that it was written by Michael Correll, who was actually a former coworker of mine at Tableau, and he really challenges this idea of literacy and using that essentially an analogy, right, to be able to
00:10:18
Speaker
And one of the things he did mention was that there was this kind of concern that he had that people would treat it as either be either literate or illiterate and that that was a very dangerous sort of a mindset and actually I really agree with that because the last thing you want to do is walk around and sort of say, oh, you know, here are the people in an organization who are literate and here are the ones who are not.
00:10:37
Speaker
And I don't think that that's a very helpful mindset. I think it's very much degrees, like a sliding scale of literacy, where you can become more and more fluent in this language of data. So I don't believe it's an on-off switch at all. I think even people who I know who are very talented with data would tell you that they have so much to learn and feel a lack of proficiency in certain aspects of the overall scheme.
00:11:03
Speaker
I do think it's a challenging, it's not a perfect analogy. I think you're taking literacy and applying it to data. So there's commonality, like I can understand my environment. I can see what other people are communicating to me and talk back to them in this language of data. And actually there's a huge promise because it could be a universal language and in many ways it is.
00:11:25
Speaker
But yeah, I think that the analogy isn't perfect because, well, you brought up that one, which is that it isn't an on-off switch. I think that that's an important one. But also what's interesting is, especially with data visualization, as you know, John, we're actually born with certain techniques and abilities to be able to
00:11:41
Speaker
notice things without having to go to school to learn it so maybe with language and reading words and that would require us to dedicate time as children to learn it whereas with data visualization you know you show me a scatter plot with an outlier and it's colored red and I could show that to just about anybody and they'd point to that exact dot and say what's this.
00:12:02
Speaker
But also it's the case that the reason I think that a lot of people perhaps don't know how to read a scatterplot is because they never learn how to read a scatterplot. It's not like we know instinctively how to read a bar chart. Let's not imprint it in our DNA. We have to learn how to read that.
00:12:21
Speaker
I totally agree with you that there are ranges of this literacy and I'm not even sure that there's, even when it comes to text, there's these two, it's a binary thing, right? Like we don't start reading by opening a book and now we're able to read. We first have to identify the letter shapes and then we start to identify the combinations of the letters and then we can read some words and then ultimately, you know, later on, we're able to read full passages and phrases and sentences and chapters. So, you know, to me, saying that
00:12:49
Speaker
And I'd have to go back to this blog post and sort of review, but I think you're right that there are these ranges, but I also think that also applies to reading text as well, that it's not on or off. Yeah. And even then like to your point, right, there's reading levels. So are you in the fifth grade reading level or an eighth grade reading level? So it's something that you continue to develop further as you go.
00:13:12
Speaker
Right. Now to this point of what it means to be data literate, you also have, now this I think is probably one of the first publications of your new company, Data Literacy, is this ebook, 17 Key Traits of Data Literacy. And I've signed up for the newsletter, Ben, and I've downloaded it. So I've got it right here.
00:13:30
Speaker
So maybe you can talk a little bit about, I don't think we need to go through all 17, but you have these four groups, which I think is a really nice way to think about the basic problem or the basic challenge for people.
00:13:43
Speaker
Yeah, so I started asking myself pretty much about a year, year and a half ago as I was preparing to leave Tableau, what does it mean to be highly data literate? And so this is really just my take. Notice I call it 17 key traits, not the 17 key traits because I think that there's probably a lot more than that. But the ones that I noticed that highly data literate people that I had the pleasure of working with all seem to display to somebody or another. And they fell into those four buckets of knowledge, skills, attitudes, and behaviors.
00:14:13
Speaker
I like that framework because I think sometimes when you ask someone, are you data literate? They usually would interpret that to mean probably just knowledge or skills. Do you know the concepts or are you able to use the tools? I think that those are super important.
00:14:31
Speaker
for especially in a group environment to be highly data literate. We also need to consider sort of what are our attitudes about data and also kind of what do we do week in and week out in terms of the way we act. And those are things that I learned from, I've been
00:14:46
Speaker
lucky enough to have Georgia Loopy on my advisory board. And I think she's a person who's really brought out some key concepts around the humanity of data. And that's an attitude, right? That's a way of thinking about data that it doesn't really relate to, can you use this certain software package or code with this language? It's more around, how do you see the usefulness of this resource as it relates to human beings, what we're trying to accomplish?
00:15:13
Speaker
I found that those are really important components of the overall data literacy picture to me. This is a free little e-book that I really just had a fun putting together because again, I was trying to define in my own mind what it didn't even mean.
00:15:29
Speaker
So when you're working with groups and with clients, are you working through this book with them? Or is this like the resource that they get at the end? Or when someone calls you up to help them or their team or whatever, like how do you approach that sort of thing when it's a question of how do we become more data literate, either as an individual or in the organization as a whole?
00:15:48
Speaker
Yeah, great question. So I got a chance. So for example, with that 17 key traits, I was invited to review that in a presentation to the intelligence community in Washington, DC. In fact, I forgot to bug you. I was going to see about staying at your place, man. We'll talk about that another time.
00:16:06
Speaker
That was just been saying like, hey, talk to us about this. We want to understand the concepts, right? So that would be an example of maybe a one or two hour session where we sit down and I kind of walk through those 17 traits one by one and expand on them a bit more than what you get in the book. But usually then it goes to the next step, which is, okay, well, hey, we want to become more data literate. And so many organizations are saying this now.
00:16:27
Speaker
And you can't just talk about traits. I think you need to actually get hands-on. So right now, right, that usually works its way into more extensive workshops or training having to do with being able to interpret data visualizations, being able to work with data by exploring it and communicating it.
00:16:46
Speaker
And so I'm just really going through the very first iteration of those kinds of workshops with organizations now. But yeah, it wouldn't be like, let's do a workshop on the 17 traits. Like that's not really, it's more just like a concept that I'd like to get out there. And then the next step is, okay, how do we find out which ones are most important and how do we develop ourselves in those areas where we're most efficient in the areas where it's most important?
Hands-On Data Literacy Training
00:17:10
Speaker
Right. I'm going to assume that when you work with these groups, you're hoping that you can bring
00:17:15
Speaker
the different sides together. I mean, I think a lot of us who are teaching either in universities or with clients are finding, I think I'm sure you found this, that they're sort of like either the design side or the design folk are over there, and the management folk are over there, and the data is folk are over there, and then the analysts are over here. I guess the question is, what do you say when you come into an organization? They're like, help us be more literate. The designers are down the hall if you want to go talk to them. Yeah.
00:17:45
Speaker
So let's let me think about that. Well, usually the conversations I've had so far, they oftentimes they could be that it's just one department, right? So this is like the marketing group in a firm. So it might be in those instances, it would just be really training everyone in the department, whether they're
00:18:06
Speaker
data people are not. But it's definitely, I guess, there are other places where it's more broad, where it's, you know, not just one specific team or department, where they're looking for kind of cross-functionally. So my belief is that the programs would be ideally, you know, helpful for someone. It doesn't really matter what department they're in. So a big part of it for me is, and I actually learned this with the whole Six Sigma thing, which
00:18:29
Speaker
It was fun, you know, it's a real corporate training program. My dad used to give me a hard time that I had a black belt title because he thought he'd send me through engineering school. And so that was a fun conversation with good old dad. But yeah, what it did do, which I loved, is it forced people to bring their own project and their own data to the workshops. And that's where I think you really start to have
00:18:52
Speaker
the learnings cemented in because you're actually applying it. So when I'm working with organizations, I'm asking them to bring data to the training so that when we talk about concepts, maybe at a higher level or more general across that would speak to people in multiple departments, they're applying it to their data, which has to do with their team and their department. And so you get the ideas, but then you also get the practical side of going through the steps in a way that helps you right then and there on the spot.
00:19:22
Speaker
I think that in that sense, I'm hoping to be able to connect with people regardless of the department they're in, which is also a broad message. So it's a little bit challenging from a marketing point of view to say, no, this is for everybody in your organization and it's maybe easier.
00:19:37
Speaker
When I was preparing to launch, I would hear messages from my business day schools like, you have to be really niche, you have to be really targeted. And I'm like, well, shoot, I'm actually really not any of those things. And hey, I'm just going to go for it because I think this is a language everybody needs to speak. So yeah, it's early days for me, right? But that's a challenge for me.
00:19:57
Speaker
Yeah, absolutely, absolutely. So what else do you have either out or coming out to make this work? Yeah, so right now there's a course that I'm teaching, actually just wrapping it up. It's like a level one online course. And then I'm starting a level two at the beginning of June. Probably by the time this airs, it'll already be off and running. So that's cool. That's really just for me. I love that because I get to work with individuals.
00:20:18
Speaker
that maybe don't have the backing of a big company with more resources. It's just someone out there who's saying, I just really need to learn how to work with data. So I love those interactions, little groups. And then there's a book, Avoiding Data Pitfalls, through Wiley, my ever patient and saintly patient, in fact, editing team at Wiley, that's coped with just a roller coaster for me over the last four years of finally getting that
00:20:43
Speaker
Draft submitted so I love that book because you know, I kind of asked myself What would I write to myself 10 or 15 years ago 20 years ago? So that I would maybe like make fewer mistakes with data that I've made over the years
00:20:55
Speaker
So I'll turn that into a little program, you know, do some training on that too. And then I just actually, yeah, just launched a course through Udacity, which is one of these online sort of digitally native for profit education companies. They're based out of Mountain View. I think some Googlers started it up. My class is all about data storytelling and, you know, being able to tell interesting data stories as well as
00:21:20
Speaker
I love it because I got to learn a little bit about their processes, how they do things. It's a great outfit. They do an amazing job of creating this really cool educational environment with mentors.
00:21:38
Speaker
you know, message boards where you can talk with each other. And so anyway, I think I went to school too just by doing that project with them. So yeah. So you are now sort of free as it were of Tableau. So when you are teaching the Udacity course, are you teaching people how to use tools and are you still focused on Tableau or is it like a broader toolkit now that you can now play around with a little bit where maybe you didn't have that chance before?
Exploring Data Visualization Tools
00:22:04
Speaker
Yeah, Tableau was always pretty good about letting me play with other tools. But yeah, a lot of my conversations with people had to do with that product, which I still love and use. And that Udacity program does allow people to, I walked them through Tableau Publix story points feature as well as which is where you kind of create an interactive slide presentation. And then also what's called the pages shelf, which you may or may not have heard of, which is Tableau's ability to animate the data. So
00:22:30
Speaker
Yeah, I definitely still talk a lot about Tableau, teach Tableau, and love it. But I also was able to, yeah, definitely branch out a little bit. I was showing them this, I don't know if you've heard of it, but Duncan Clark and his team over there at Flourish, at Flourish.studio, they just launched a new feature called the Talkies feature, which is super cool, which you can do. I think maybe, do you have Duncan on? I think maybe, or maybe Ali did. I think he was on Dataviz, Dataviz Today. Yeah, let's try to listen to that interview.
00:23:00
Speaker
He's great, and I think the tool he's building is super neat. But this Talkies feature, it allows you to make a data story, including animated data that your readers or audience can interact with, hover over, change the filters, and all that. But what's super cool about it is you can actually upload an audio file. So you can actually have a soundtrack talking through this story that automatically plays out that also your readers can interact with. So I put it all together.
00:23:29
Speaker
interactive, animated, narrated data story, and even write code. And this is not even an advertisement for it. I was just so impressed with it. When I was talking to Udacity, I said, oh, I know how to make this advanced data storytelling course really cool. Let's teach them this Takis feature. And they were really great. They embraced it. And I love that.
00:23:49
Speaker
So, yeah, we'll walk through that. But I think, yeah, for me, definitely, you know, stepping away from a vendor. Yeah, I find I've been playing a lot with R lately, and I'm looking forward to learning Python. And so, yeah, I feel like I'm broadening my horizons right now with tools. Yeah, that's cool. For sure.
00:24:05
Speaker
So I do want to get you, you mentioned Flourish and I know they have the talky feature and they also have the bar chart race feature that they added after, you know, John Byrne Murdoch, who was just on the show, sort of popularized. Let me, let me make this a broad question. So what's your take on animation in Dataviz?
00:24:23
Speaker
OK, so I really love, if you've ever read Tamara Munzner's book, Visualization Analysis and Design, this is an book I teach in my UW classes.
Animation in Data Visualization: Pros and Cons
00:24:31
Speaker
But she has a really great rule of thumb about data visualization. And she says that eyes beat memory. And so what she means by that is if you give someone the ability to see something at once in a bird's eye view, that's better than if you're requiring them to remember what happened.
00:24:49
Speaker
sort of in a sequence. And so animation suffers from that, which is that people see data move, but maybe they don't remember. It's hard to answer questions. It's hard to say, oh, what happened halfway through the animation with one of the 50 data points, right? So those types of questions are hard to answer. That's on the con side. But the pro side, I don't think you can deny is that
00:25:12
Speaker
animating data, Hans Rosling taught us this. It really brings it to life. It sets everything in motion. You sort of connect with it in almost an emotional way that I don't know. So it's a very unique opportunity to connect with your audience in a way that just
00:25:28
Speaker
really leaves them with an amazing sense of the fluidity of the environment and feeling and sensing how things changed over time. So I kind of find they both have their own purpose. So in general, I wouldn't be a person to say, never use animation. And I agree with Munzner that
00:25:49
Speaker
from an analytical point of view, if you're going to animate the data, you also want to give them the ability to go in and answer specific questions. But I was just so moved by Rosling and by others. And Nathan Yao has done some amazing data animations with the Day in the Life type surveys. And you just feel what's happening in a totally different way. So I love it. Yeah.
00:26:09
Speaker
Yeah, yeah, no, I agree. I think there's a there's that playfulness to some of these. And I also think what's interesting about them is some of them are a lot of them, at least the last, you know, with this bar chart race thing, they seem to be made especially or specifically for social media, which is, again, a different way to interact with content than if it were on a website or if it were, you know, in a different type of platform.
00:26:34
Speaker
Yeah, exactly. It's so funny to see the rise of the GIF again over the last few years. Yeah. So much of our consumption has moved to the mobile platform. I got to watch that, you know, with the Tableau Public Platform and just seeing how all the journalists I was working with were really, you know, it went from kind of sort of asking, oh, how does this work on mobile? Maybe as a question.
00:26:53
Speaker
not that didn't really matter too like that's really in some cases all they thought about so i get that i get that oh one other thing too as it relates to data literacy specifically i think and you mentioned scatter plots and how a lot of people don't know
00:27:06
Speaker
maybe how to read them. I think actually animation can really play a role here because imagine if, let's say you've got a bunch of dots on a scatter plot, right? Instead of just throwing that at someone and saying, here you go, what if you animated the dots across the x-axis and told them what was happening?
00:27:24
Speaker
Here we'll see every country move to its GDP position. Now we'll see it and stop, right? And then the next sequence of the animation shows those circles rising to maybe their population place on the y-axis. I think that you have a way of introducing someone to a graph
00:27:40
Speaker
and or a chart and really helping them kind of like connect with the axes in a way that is I think has a lot of power and potential because I don't think yeah I don't think we can assume everybody immediately knows what it's showing but there's a way to animate it into the view such that they sort of see the build and maybe even get to a place where they see something more complex than they otherwise would have been able to read.
00:28:04
Speaker
Yeah, I think that's exactly right. Cool,
Post-Tableau Projects and Busy Schedules
00:28:07
Speaker
Ben. Well, you've got a lot going on, man. Yeah, thanks. It's been fun. I love this show. I always listen. Thanks. I'm coming your way this summer. So anytime you let me know I got a spot for you. We've got a spare bedroom, you can hang out downstairs. And my daughter will make you pancakes in the morning. I love it. And yeah.
00:28:30
Speaker
Well, let me know when you come out east and have a great summer and good luck with everything. It was great chatting with you, bud. Likewise. Thanks, John. Thanks for having me. Talk to you soon. Yeah.
Season Wrap-Up and Future Plans
00:28:44
Speaker
And thanks for everyone for tuning into this whole season. I really do appreciate the support and I do appreciate all the guests who've come on and talked with me about their projects, about their books, about their websites, about all the great content they're producing and work that they're doing. If you'd like to support the show, please review it on your favorite podcast provider or tell your friends about it. If you'd like to support me financially, that'd be great. I could always use some help.
00:29:08
Speaker
paying for transcription services, paying for editing services, paying for the website, all the stuff that's needed to bring you this show every other week. So in the fall, I have a whole new slate of guests all set up to bring to you, but if there are people that you'd like to hear from, you'd like to hear me chat with them, please draw me a note. Let me know who is out there that you would like to talk, that you'd like to hear from. I'm sure there's lots of people that I don't know about, people whose work is making a difference, that is helping you understand things about your world and your experience,
00:29:36
Speaker
And I would love to chat with him. I'd love to hear about the work that they're doing, the tools that they're using and how they think about communicating their data, their results and their analysis. So until the fall and until next time, this has been the policy of his podcast. Thanks so much for listening.