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Visualizing the Future: Navigating the Shifts in Data Storytelling with Enrico Bertini
835 Plays7 months ago
You know Enrico Bertini, right? Writer, teacher, co-host of the Data Stories podcast, Enrico does it all. Now at Northeastern University, I invited Enrico to the show to talk about his research, great Substack newsletter, and for views on the evolving landscape of data visualization on social media. In our discussion, Enrico emphasized the significance of interdisciplinary collaboration at Northeastern University. He has some concerns about the current state of visualization theory and tools and talks about his ideas around “critical data thinking” as a crucial way of thinking about data visualization, highlighting the challenges of data accuracy and interpretation. We also talk about Enrico’s teaching methods to help students improve their data interpretation and data visualization skills. Enrico and I share some of the same feelings about the shifts in social media use in the dataviz community, and how it has led to a loss in diverse intellectual exchanges, underscoring the importance of finding new ways to foster community engagement and creativity, including through writing platforms like Substack and LinkedIn.
Keywords: visualizing the future, navigating the shifts in data storytelling with enrico bertini, data storytelling with enrico bertini, data visualization, navigating the shifts, enrico bertini, storytelling with enrico bertini, analytics, business intelligence, data storytelling, Jon Schwabish, jon schwabish, tableau, bar graph, flourish, data analytics, flourish studio, flourish studio tutorial, coping with change, intuitive, annabelle drumm, data visualization for data science, mathematics, Al, machine learning
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Transcript
Introduction: John Schwabisch & Enrico Bertini
00:00:13
Speaker
Welcome back to the Policy Vis Podcast. I'm your host, as always, John Schwabisch. And I am excited to have a special friend with me this week on the show, Enrico Bertini, now at Northeastern University, comes by to talk about his work, his research, his newsletter, and the quickly shifting landscape of data visualization social media. Now, if you don't know Enrico Bertini,
00:00:36
Speaker
Well, I don't know what to say. Maybe you just got started in the field and you don't know him, but you should because Enrico was one of the first people that I discovered when I got started in data visualization. At the time he was at NYU and now he's at Northeastern, which is growing by leaps and bounds in their information visualization, media, journalism fields. It's really interesting about how they're sort of bringing all these different fields together. You'll hear more about that in the conversation.
Enrico's Work & Contributions
00:01:05
Speaker
But Enrico is the host of the Data Stories Podcast. He has a new sub-stack newsletter, a really thoughtful guy about how we communicate our data, how we think about reading other people's data visualizations, and just a whole bevy of research in the field that if you're a practitioner, maybe you haven't really thought about a lot, but Enrico is doing a lot of work of trying to bring
00:01:30
Speaker
some of that data visualization research to those of us who are not really, you know, neck deep in the field. And so it's great to have someone who can kind of be that translator. So I think this conversation will be useful for those of you who may not be as familiar with especially the data visualization research field. And also I think will be useful for thinking about
00:01:51
Speaker
how the changing landscape of social media impacts where the data visualization field is today and where it's going to head over the next few years. And plus, you get to hear Enrico's Italian accent, which is always just enjoyable. So
Transition to Northeastern University
00:02:07
Speaker
Enrico and I go way back. We have a great conversation. It's a lot of fun. And I hope you'll enjoy this week's episode of the podcast. So without further ado, here is my conversation with Enrico Bertini.
00:02:21
Speaker
Holy moly. It's Enrico Bertini. I wish I could have gotten a rhyme there real quick, but I... What's up, friend? Long time, no see. It's been way too long. Way too long. I mean, I think since the last time I saw you in person, we were in New York eating at a restaurant outside around other people. It was the good life.
00:02:50
Speaker
The world has changed dramatically. You moved. We each got 74 years older. Yeah, it's good to see you again. We don't look like, we don't look like. No, no, no, no. Our hair is just as dark and silky as before and have just as much of it. I mean, there's no extra poundage anywhere. Yeah. Not at all. We look the same. We haven't aged a day.
00:03:20
Speaker
Great to see you again. You were at Northeastern doing a whole bunch of stuff. Why don't we start with your move? Tell me about the move up to Northeastern. You've been there like two years or so. Yeah. And it's like the growth there is incredible, the people that have been hired there. So tell me about that experience.
Research on Data Visualization & Machine Learning
00:03:39
Speaker
Yeah. So I've been here for two years now. It feels like time passed in a second. After spending basically 10 years at NYU in New York City,
00:03:39
Speaker
Not at all.
00:03:49
Speaker
And it's been interesting. I think it's I had a really good time at NYU, nothing really to complain. I think what is interesting here is that the school is really investing in in visualization in a really big way. So it's becoming a really interesting place to be if you work in that space. Right. And one of the things that is really special here for me is that
00:04:19
Speaker
that are data visualization people in at least two different schools. So we have people in the, let's say in the computer science space, and we have people from the art and design space. In fact, my position here is across the two colleges, which is really interesting. And so I think this is really unique. And this also means that even just with the
00:04:45
Speaker
faculty that we had even before I joined, there was a really interesting group of people coming from a different background. Now the school is investing in a big way in this area, so
00:04:57
Speaker
since when I joined other people from this organization joined and it's growing. So it's, it's kind of ridiculous honestly, but in a good way. Yeah. And what have you been doing research wise? I mean, I know there's this paper you have with Steve Frinkinari and I think a graduate student Raquel that we can talk about, but like what, how has, what are you doing research wise?
00:05:23
Speaker
Okay, so research-wise, I would say, when you move, you start thinking about your work in a
The Importance of Data Thinking & Visualization Theory
00:05:31
Speaker
much deeper way, you have some time to think. It's always hard to summarize, but I would say, so for many years before moving here, I've been doing research across
00:05:43
Speaker
machine learning and data visualization. So that's more the more core computer science type of thing. And the focus there was like, hey, we have these really complex models. And visualization seems to be the really interesting tool to help people understand what these models do, how they behave.
00:06:03
Speaker
and what the elements of the models, what roles they have, so really look inside or look outside the model. We spent quite a number of years trying to do research in that space and now that I moved here I'm still interested but
00:06:21
Speaker
in a different way. I think in the meantime, we have large language models came to the scene and a lot is happening in general in AI. So I'm kind of like a little disoriented and I'm in a phase where I want to understand what I want to do next in that space.
00:06:38
Speaker
And then I would say the other area of research is more like, this is a very general term, but I would say data visualization theory in some sense. I'm really interested in trying to make really basic progress in data visualization, trying to ask the questions that we are not asking, looking around as they go, what are the basic things that we are not looking at? Trying to get at the
00:07:06
Speaker
low hanging fruit that nobody seems to find somehow, right? I don't know if this metaphor works.
00:07:15
Speaker
I don't know, I spent quite a lot of time thinking, I developed over the years a dissatisfaction with the theory that we have, right? When you go back to the basic question of how do you visualize this, right? And we don't have a lot of tools to answer that question. So if you go through a lot of practice, you become proficient, right? But if you want to unpack what is it that you learn when you go through a lot of practice, we don't have a lot of
00:07:45
Speaker
pedagogical tools to transfer that knowledge in a better way to students or ways to think about this organization in a more systematic way. So we have a few models here and there, but I'm not too satisfied about that.
00:07:59
Speaker
And yeah, I could gone forever. But I would say these are the two main strains of research that I'm working on here. And I can give you more details, of course. Yeah, what I think is interesting on the, so we can talk about the pedagogy in a second, because I think that's, it is interesting. I get asked once in a while to like,
00:08:18
Speaker
Hey, could you write a book or something, some sort of tool where it would be like a flow chart that would help you like pick the graph for the data that you have? But like, I don't know if that, I don't even think that exists. But what I found interesting about your sub-stack newsletter, which we can talk about, is you've been focusing a lot on
00:08:37
Speaker
the kind of core principles of working with data. Like it hasn't even really been about the visualization piece. It's been about the data piece. And like, you feel like that's a missing part of the whole field? You put it much better than I, right? Yes. Mostly because I'm frustrated that, let me take a step back. So when we talk about visualization, we tend to talk about the problem of how do you
00:09:05
Speaker
visually represent information, right? So that step going from data to something that is graphical somehow is what we focus on, right? But most of the problems that exist in visualization don't depend exclusively from that step, right? And I always felt that, well, always, I started feeling that
00:09:29
Speaker
We could go on discussing whether a pie chart is better than a bar chart. At some point it's not that useful because there are many other problems before you even get to that step, right? I started thinking about visualization as one component of a much larger problem.
Impact of COVID on Data Interpretation
00:09:46
Speaker
And the much larger problem, I start thinking about it as how do you think with data, right?
00:09:52
Speaker
I think the problem of how do you think with data is the larger problem. How do you think with data and how do you then communicate data? But the general, whether you are the reader of a data visualization or the producer of a data visualization, you still have the same problem. How do you think effectively with data? And of course, visualization plays a major role there because it's one of the best tools to help you think.
00:10:22
Speaker
But what happens when you are thinking with data and with data visualizations, I don't think we have a really good understanding of what happens there. And we don't tend to talk about thinking, we tend to talk about how do you design this thing right. And there's nothing wrong in that, it's super important, but there's a lot of focus on how do you design this thing right.
00:10:45
Speaker
right? Whereas I think it's really important to start thinking, how do you think with data? Because both designers and readers need to know how to think with data. And yeah, I think that's one of the main ideas that I try to explore in the newsletter. Yeah. And do you think that's something
00:11:06
Speaker
I struggle with the thinking with data and also like the uncertainty literature to these other pieces because there's like, yeah, statistical literacy, numeracy, like is it only, is it restricted just to the people who are, you know, neck deep in data or does that apply to everybody? And how do we get more people to understand and think, think with data in that way?
00:11:27
Speaker
No, look, maybe, maybe I'm now thinking unconsciously I've been traumatized by the COVID pandemic, right? Because we've been flooded. I mean, of course, everyone has been traumatized one way or another, but now I'm referring to data in data research.
00:11:47
Speaker
It's like we've been flooded, all in a sudden, it's been not only one of the biggest events in human history, but one of the biggest events in data history. Because we've been flooded with data statistics and data visualizations.
00:12:06
Speaker
A lot of that flooding has been so poorly done, so poorly communicated, and so poorly interpreted. And even a person like me, who I think I can reason pretty well with data visualizations. If your students are listening, he can reason with data.
00:12:32
Speaker
I think I've been influenced by that. To answer your question, I think it's crucial for people to be able to reason with data and also to
00:12:45
Speaker
evaluate whatever they receive critically, right? So, in the back of my head, I always had this idea of coming up with something called critical data thinking, right? In the sense that it's critical thinking with data, right? And we are... So, point one, it's very hard to do, even if you have been working with data
00:13:09
Speaker
for many, many years, you are constantly humbled by how easy it is to get fooled with data. And in general, I think that if you look even at advanced societies that have a very high level of literacy, most people don't really know how to think with data. I think that's a fact. I don't have
Exploring Data Reality Gaps
00:13:31
Speaker
good numbers to show. You don't have data on that.
00:13:33
Speaker
I don't have data to show them. I suspect that there's a very large segment of people, even highly educated people, that are not that good at interpreting things with data. And we are not even talking about doing their own analysis. That's way beyond. So I think that's my main point there.
00:14:00
Speaker
So I think answering your question is not only for experts. In fact, I think that what is really interesting about this world is that there's a lot to do for the population of large, for family people. I mean, for me, I go even...
00:14:19
Speaker
I think a lot of my thinking has evolved over the last two, three years on just, is the data that I tend to work with, right? Those socioeconomic demographic data. Is it measuring what we think it's measuring? Is it accurate? Is it capturing the right people in the right groups? My faith in the data that we use all the time is shaken in that I'm not sure it tells us what we think it tells us. And that is,
00:14:48
Speaker
problem. And then to the, to the dataviz side, I struggle with this a lot. I was actually, I gave a talk a couple weeks ago at the dataviz DC meetup and I had this little physical dataviz thing where people could make little pie charts out of their average beverage consumption over the course of the day. Right. So, but, but while people are sort of hanging out, there was this conversation about how bad pie charts were, right? It's this whole, like, here we go. Right. This whole like Tufti thing that like, we gotta get over it.
00:15:17
Speaker
And I, before I did my talk, I asked people why they think it's a bad pie chart and like a couple of responses were, Oh, well, because you can't really figure out the slices accurately. And my response to that wasn't even about any discussion about the chart itself. It was, do you think the data in those charts are even accurate?
00:15:37
Speaker
Right. Like, like if I asked you what percent of your beverage consumption in the course of the day is coffee, you would give me a number, but like, is that number accurate? Like, you know, it's like, so there's, there's just kind of maybe a false precision that we, that we often think about that it comes all the way back to, I think the data that we have at the beginning of the day.
00:15:57
Speaker
Totally. So last semester, I started teaching a new course. And in the context of this new course, I prepared the whole module on basically this specific problem. And it was inspired by something I read in one of Ben Jones' books, I think it's called.
00:16:22
Speaker
Data pitfalls, something with data pitfalls. I'm sorry, I don't remember exactly the title. And he has this really nice chapter or section in a chapter that he calls data reality gaps. Super inspiring. I love the concept, right? There's often a gap between
00:16:39
Speaker
what's in the data and what's the reality described by the data. And again, this is one of those areas where I think there's so much more to do, so much more. Because if the numbers don't represent the thing you think they represent, all the rest is completely useless. It doesn't matter. And this goes back to what I was saying before. You can decouple data visualization from these
00:17:09
Speaker
specific notions, right? All these things are glued together. I guess it's basically what you were trying to say a moment ago, right? Yeah. And so when you teach visualization from this point of view, from the interpretation point of view, right, you have to go through all these steps. And again, I feel like we haven't been talking about these steps much in the past. And this is why I'm so excited about it. Yeah.
00:17:38
Speaker
So I mentioned your newsletter a little while ago. I'm curious what you think about, and you mentioned your evolving thinking over time and moving to a new university, but I'm curious what you think of the data vis sort of community writ large now. Things have
Impact of Twitter's Decline on Data Community
00:17:57
Speaker
changed pretty dramatically, pandemic kind of destruction of Twitter. Where are you right now in this whole,
00:18:07
Speaker
changing world? I think the Twitter thing has been a really major event for our community.
00:18:22
Speaker
I don't know, well, it's always hard to say if our community is the visualization community. Maybe there are multiple communities, right? But I'm going to assume that there's a thing like our community. And our community felt, I don't know, Twitter just kind of crumbled. And looking back, I invested, what, 10, 15 years on that platform.
00:18:46
Speaker
And I got to know most of the great data visualization people there from very early on. And I never realized how important this platform was for me. But when it crumbles, it's like, holy.
00:19:03
Speaker
Can I swear on your podcast? Holy shit! It's gone. You're like, wait, this isn't the Data Stories podcast. I used to swear all the fucking time on my podcast. Right? So, holy shit, it's gone. And when it's gone, now Gerardo,
00:19:26
Speaker
there are a number of connections that are gone, right? But there's also all that beautiful conversation that used to happen in the back channel somehow. And it was so rich, so rich, right? Especially now that it's no longer there, I realized that one of the big, two values. One was that were people from so many different backgrounds that once this thing crumbled, you go back to connecting
00:19:53
Speaker
to people that are more similar to you and you no longer have access to all these intellectual, interesting intellectual contributions that you get from people that think in a very different way from the way you think. That's one thing. And the other, I forgot the other one that I wanted to say,
00:20:14
Speaker
I think, yeah, there are some of these connections you only have on social media, right? I mean, me and you, we connect since many years. I could literally just call you on the phone if I want to. But I don't have the same level of connection with many people with whom maybe have been interacting even for many years on Twitter. And once they're done, they're gone. So I think that was a major event for our community.
00:20:41
Speaker
And now I've been discovering LinkedIn somehow. And it seems like for whatever reason, many people are there, and it feels different. And at the beginning, I was put off by the fact that it feels different. But I'm like,
00:20:58
Speaker
Wait a minute, that's different, let's explore it. And it's more corporate, of course. But it also, it seems like it gives us access to a group of people that otherwise wouldn't have seen our work if we were stuck on Twitter.
00:21:19
Speaker
And I also feel like that on Twitter, the personal and the professional seem to mix a lot. And for many years, I thought that it was a really good thing because it makes it fun. It makes it more true in a way. And people know more who you are. And on LinkedIn, LinkedIn is a little bit more uptight. My thing is on LinkedIn.
00:21:51
Speaker
And I thought it was a limitation but maybe it's not a limit it is a limitation but I also like that people feel a little bit more cautious because Twitter used to go out we used to go a little bit overboard with the personal right right and I miss that aspect but on the other hand I
00:22:11
Speaker
I also like the fact that we don't get to discuss crazy things all the time. It's way more balanced.
00:22:20
Speaker
I was going to say the back and forth, I think, seems less on LinkedIn. LinkedIn feels more one way to me. I post the thing. There's not the same sort of conversation that happens. And I don't know why that is. It might just be the way the platform works, the algorithm sort of moves things up and down. Yeah.
00:22:41
Speaker
Yeah. Yeah. And I think another aspect going back to your original question, because I've only been talking about the social media aspect. I think what happened is that during the pandemic, many people just went back to reflecting about what they're doing and how they're doing it. And I feel like there has been some kind of visualization fatigue where people didn't really feel like going straight back to the same conversations, the same kind of work, the same. I've been hearing from many people, like,
00:23:13
Speaker
Do I really want to do more of that, right? And I felt it for a while and luckily I am back to finding a new angle, right? Which is basically what we just discussed. But I can imagine, I can understand why some people doing visualization for 10 plus years, then the pandemic hits, then they all in a sudden they have a way to reflect about what they're doing.
00:23:35
Speaker
And they don't feel like there's more to say in that space. So I think that's another element. I feel there's a sense that there's not much more to say in this space unless you stumble into something new. Because again, we started with, do we want to talk about pie charts for the next 10 years? Probably no. So I think that's another element in the air. That's right. I think all the things you said I totally agree with. I think the other thing that I find
00:24:05
Speaker
distressing about the kind of collapse of the Twitter community is finding individual people, individual freelancers, new people to the field doing neat, cool stuff. And I don't know what it is, but I feel like my feeds now or like my Twitter feed is all just like the news organizations I follow.
00:24:28
Speaker
There's no oh, you know, it's horrible. It's horrible. And so so I feel like all the visualizations like that I sort of collect and curate for teaching or for writing are all from like the major news organizations that I read every day. Right. The Times and the Post. And yeah. And I feel like I've lost that.
00:24:46
Speaker
that maybe that fresh eye or something like that, I don't know. And that makes me sad too. That was a lot of the excitement, right? Someone tries something new, not that the folks at these major news organizations aren't, but someone new to the field try something new. And like you said, sometimes they get bashed on, they would get bashed on Twitter, but oftentimes it was like a celebration of like, look at this new thing that someone's doing.
00:25:12
Speaker
I totally agree. I do think that we lost something really, really valuable. I'm still processing it. I don't know what to do. Yeah, I don't either. It seems like a big loss, honestly. Yeah, no, I agree. And I know lots of people complain about Twitter being a cesspool and bad stuff about it. And obviously, there are parts of it. But for me, staying within the database community,
00:25:40
Speaker
Look, I didn't want to leave. I'm still there. I'm just not that active. If only that's sad that everyone comes back, I'm ready to go back to the party.
00:25:51
Speaker
I checked it a few days ago and someone had posted like a picture from the Tableau conference last year and I had like 40 notifications. I was like, oh yeah, it's great. Yeah. But then there was like thrown in there was like the NFT stuff. Yeah. I want to wake up from the big bad dream. Right. Right. So, so tell me about the, the newsletter.
Enrico's Newsletter & Community Building
00:26:12
Speaker
So yes.
00:26:13
Speaker
that your newsletter is really interesting because a lot of it is your, it's not necessarily like a stream of consciousness, but it's your kind of ruminations on things. And some of it feels unfinished in not the writing, but in the thought because you're clearly developing the thought and those posts sort of end with like,
00:26:34
Speaker
Well, what do you think? So, um, so I guess two questions there. How are you thinking about approaching the newsletter and are you having people write back to you? Are you having any conversation there or is that I have not found that to be the case on sub stack, but I'm curious if you're having that, that experience, but I think the more important question is, you know, how are you, how are you thinking of writing and what's your thread and all that? Yeah. You know,
00:26:59
Speaker
Yeah, well, I find that the best way to think is to write. So that's the main thing. It forces me to go deeper into my thinking. So in a way, one of the reasons why I started the newsletter is because I felt that if I could write and the ideas that I have in mind, I could become more precise.
00:27:24
Speaker
And I also accepted very early on, I accepted the idea that these are initial thoughts and nothing prevents me to go back to it and write another post in the newsletter that is either a refinement of what I wrote or a follow-up. And in fact, many of the posts that I have are like, oh, I'm going back to it from a different angle. This happens quite often.
00:27:48
Speaker
And so that's one thing. The other thing, I really felt that I wanted to build the community around the ideas that I have.
00:27:58
Speaker
and try to serve people somehow, right? And this is part of the discovery process. I don't think that one starts a newsletter knowing, oh, I want to target these kind of people. For me, it's more like, I'm going to start writing. I want to see who shows up. And little by little, that's going to be a way for me to discover what people want to learn, basically, and what they think.
00:28:23
Speaker
And also if they can help me think about these ideas better, right? So when I write about these half-baked ideas, one of the intents is to see if anyone has some brilliant ideas, right? Or even not brilliant, honestly, just adding some interesting elements in there. And it's kind of working. One thing that I discovered to answer your second question is that
00:28:48
Speaker
almost by chance I stumbled on this synergy between Substack and LinkedIn, right? So in a way the two things work together. And it's not like I did it on purpose. I almost like discovered that the two things can go well together. So there are some ideas that I shared on LinkedIn that are even more proto, can you say prototypical? I guess so. Prototypical.
00:29:15
Speaker
Prototypical then the posts, right? Mm-hmm. So I post something in there I start getting some comments and this helps me think about that idea and then I'll post that idea on The newsletter, but then when I post something in the newsletter, I put it in LinkedIn. There's more activity in there So there's a little bit of back and forth between these two platforms and it seems to work. It seems to work I'm still experimenting but it seems to work really well
00:29:44
Speaker
Yeah,
Teaching at Northeastern & Student Experiences
00:29:45
Speaker
and what about your your students? I mean I would imagine Given you know you have this kind of sounds like like a joint appointment and the department has a mix of Design students and computer science students. Yeah, probably journalism students. I know and like I'm sure all in between like Interacting with your students. How's that helped you sort of because I know you early on the sub stack you were writing about you were publishing like oh Yeah, your syllabi and your and your lectures and all that like
00:30:13
Speaker
So, so how has that helped you sort of refine? I know you've always done that, but, but given that now that you're in a more of a more kind of diverse student body, how's that helped? Or maybe not. You mean specifically for the newsletter or in general? Yeah, I guess kind of just more, I mean this newsletter, but really just generally if you're, you're thinking around all these different topics, because I can see how thinking about data is different than how do I build a, you know, a data viz tool.
00:30:41
Speaker
Well, I think, as I said at the beginning, joining Northeastern and giving me an opportunity to be kind of like 50% in a different school, in the School of Art and Design, that is a completely new element. By the way, I'm trained in engineering, in computer science, so I've been
00:31:01
Speaker
always around computer scientists and engineers. So coming here is a discovery process. And this includes discovering design students. And they're completely different. It's really interesting, the way they think, the kind of skills that they have. My interaction with design students has been extremely positive so far, extremely positive.
00:31:27
Speaker
So, first of all, you might think that, I don't know, somehow design students are not technically savvy, right? They are. At least here. I don't know if this is true in all the other schools. Many of them know how to code.
00:31:44
Speaker
If they don't know how to code, they learn pretty advanced tools. So it's not like they come and they don't know anything about tech. But at the same time, what is interesting is that if you ask them to
00:32:00
Speaker
This is funny, right? So if you stop for a moment in a class and you say, now, sketch this, right? For a design student, it's completely normal, right? Or if you come in class and you don't have slides, for them, it's completely normal.
00:32:18
Speaker
And when I used to teach only to engineering students, when I tried to do these things in class, they always looked at me like if I was an alien. So it takes a little bit, say, no, I don't have slides in this class. I'm sorry. No, I'm not teaching. I'm not lecturing today. You are going to do some activities and you have to sketch with your pen.
00:32:40
Speaker
Right. Well, what's a paper? Yeah. Right. But let me say something else. So even beyond students, I think what is interesting here is that now you talk with some of the faculty here. And they think in a very different way. Right. And it takes some
00:33:02
Speaker
translation, right? Because we use a different language somehow. And that's really, really interesting, because we need to understand each other and they come to the problem from a very different angle, I have to say, right? A very different angle. Yeah. And it's challenging, but also intriguing and enriching somehow, because right, they will talk about completely different problems, completely different ways of thinking about it. Yeah, and trying to solve them in totally different ways.
00:33:32
Speaker
completely different. Yeah, yeah. Now, have you embraced the Boston lifestyle? Are you like
00:33:41
Speaker
You go to Dunkin' every morning and you're a big Red Sox fan and all that, or you still got that in New York? I'm not at that level yet. I met a new person, I think I was at dinner the other day, and we were talking about, I mentioned the fact that it took me a while to adapt to Boston, kind of like a couple of years. And it was like, Boston is an acquired taste.
00:34:13
Speaker
You know, honestly, so when I moved from New York to Boston, my New York friends, they were like, Boston? Come on, dude. What are you doing?
00:34:34
Speaker
like the core New Yorkers. But no, I actually like it. I agree that it's an acquired taste, but I really, really enjoy it now. That's great. That's great. Yeah.
00:34:47
Speaker
Well, it's always great to touch base.
Conclusion & Credits
00:34:50
Speaker
It's been far too long. I'm glad to get one of these Euro voices back on the show. Yes. What did you guys used to call them on the podcast? Exotic. Exotic Euro voices, right. It was like you and Moritz and Robert Casara. Yes. And you could just pick out those three. That was a comment from someone, I don't remember who, who wrote, probably on Twitter, something like, I love the exotic Euro voices.
00:35:18
Speaker
We'll have to find that, I bet. I bet that's alive. That's probably alive somewhere. Yes. All right, buddy. It was great to see you. Thanks so much for coming on the show. Thanks so much, John. That's been a lot of fun, and thanks for having me.
00:35:32
Speaker
Thanks everyone for listening to this week's episode of the show. Hope you learned a lot from that conversation. Before you go, make sure you check out all the good stuff happening on Policyfizz website with the blog and other podcast episodes and lots of other stuff. You can also subscribe to my sub-stack newsletter that comes out every other week just before this podcast comes out with a draft blog post or some other things I'm thinking about.
00:35:55
Speaker
key insights on the podcast and some other things that i'm thinking about that i'm reading that i'm watching that i'm listening to so just sort of a grab bag of stuff that i think is relevant to those of us working in this field of data communication and data visualization so until next time this has been the policy of his podcast thanks so much for listening
00:36:16
Speaker
A number of people help bring you the policy of this podcast. Music is provided by the NRIs, audio editing is provided by Ken Skaggs, design and promotion is created with assistance from Sharon Satsuki-Ramirez, and each episode is transcribed by Jenny Transcription Services. If you'd like to help support the podcast, please share it and review it on iTunes, Stitcher, Spotify, YouTube, or wherever you get your podcasts.
00:36:37
Speaker
The Policy Vis 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 slash policyvis.