SDS 441: Communicating Data Effectively

This is episode number 441 with Kate Strachnyi, data visualization expert and entrepreneur. 

Jon Krohn: 00:12

Welcome to the SuperDataScience podcast. My name is Jon Krohn, a chief data scientist and bestselling author on Deep Learning. Each week, we bring you inspiring people and ideas to help you build a successful career in data science. Thanks for being here today. And now, let’s make the complex simple. 

Jon Krohn: 00:42

Welcome to the SuperDataScience podcast. I’m your host, Dr. Jon Krohn. And it is my great pleasure to be joined today by the fun and fabulous Kate Strachnyi. Kate is a legendary figure in the data world. She’s an expert on data visualization, founder of several data-related companies, including her DATAcated Academy learning platform, and author of four, count four, data-focused books. This episode should be of interest to anyone who works with data because we emphasize how critical effective data visualization and communication are for the success of anyone working with data. And Kate provides her top visualization and communication tips. To boot, Kate also provides guidance on how to succeed as an entrepreneur, including how to build a massive social media community around your brand, as well as the pros and cons of publishing books with a major publisher or on your own. Kate is such a joy to speak to. Come have a laugh with us. 

Jon Krohn: 01:49

Kate, welcome to the program. It’s so nice to see you again. 

Kate Strachnyi: 01:53

Jon, thank you for having me. 

Jon Krohn: 01:56

So Kate, tell us, from the perspective of your children, what do you do for a living? 

Kate Strachnyi: 02:02

From the perspective of my children. So I have a four-year-old and six-year-old girl, and yesterday I was doing homework with them, and one of the questions the six year old had to answer for her first grade project was, who do you want to be when you grow up? So she’s like, well… She always has trouble with this question because she used to say, “I would like to just be your daughter forever.” But now she’s moved up and said, “Well, you don’t do anything. Why can’t I just do what you do?” So I clearly don’t do anything, which is really good news for me, because I was under the impression that they think I work all the time. But it’s a win in [crosstalk 00:02:43] for me, where they think I don’t do anything. I later explained to her that I’m a business owner, so she wrote down, “Business owner.” So, future business owner in my house. 

Jon Krohn: 02:53

So, Kate, tell us about your businesses. I think they are highly relevant to our audience. 

Kate Strachnyi: 02:59

Yep, absolutely. Happy to talk about that. So I’ll go ahead and start with Story by Data, which is something I started a couple years back and is currently focused on media partnerships. So the way I think of it is, it’s the umbrella company, under which everything else happens. That’s the actual corporation. And the other companies underneath that are the DATAcated conference, and the DATAcated Academy. So the Conference is… You’ll probably be surprised, but it’s a conference. And the DATAcated Academy is an academy where I have online courses on data visualization, data storytelling and more. 

Jon Krohn: 03:40

Yeah, I have actually, I’ve gone and checked out your DATAcated Academy, and I think it looks great. If I remember correctly, there’s a lot of content on data visualization, right? 

Kate Strachnyi: 03:51

Yes, absolutely. That’s the focus of the entire academy, is Data Visualization, Visual Best Practices. I’m currently working on a course that launches exactly 7 days from now, on January 21, where I talk about DATAcated Storytelling. It’s going to absorb all the Visual Best Practices, content, and in addition to that, there’s something really cool I’m working on that I’ve been procrastinating on, but it’s called the Data to Dashboard Series. So the Data to Dashboard Series is really focused on taking the students from data to dashboard, using a variety of tools. So at the moment, I have a course up there on Going Data to Dashboard with Tableau Public. I’ve got one with Power BI. And the vision is to have a course with Python, Arch, Sisense ThoughtSpot and all the other tools that I can find on data visualization. 

Jon Krohn: 04:45

Nice, that sounds really great. And for the audience, so January 21 will be in the past by the time you hear this; not that distant pass, just a week or two. But so that course… The first course that you mentioned, what was the first one again? Not the one you were just talking about. 

Kate Strachnyi: 05:01

So there’s Visual Best Practices. 

Jon Krohn: 05:03

Visual Best Practices. That will be live by the time our audience hears it. Nice. And yeah, you do an amazing job with creating your content. I’m sure that it will be a wonderful resource for people interested in telling better stories with data. 

Kate Strachnyi: 05:17

Thank you. 

Jon Krohn: 05:19

So what kinds of tools, or approaches, do you focus on most in your content that you teach, or in just your general life, as a business person? What kinds of data science tools? 

Kate Strachnyi: 05:30

So I don’t even call myself a data scientist per se. I started working in data, on the data visualization side of things, so mainly focused on Tableau, Power BI, and then more recently, all these other tools. But I’ve definitely studied a bit of Python and R. I even delivered some training on Python without really knowing it too well. Don’t tell the others. But I heard that the best way to learn, is by teaching. But in terms of the full data science stack, that’s pretty much all there is. I focus more on using the easy stuff- 

Jon Krohn: 06:05

Yeah. No, but I mean [crosstalk 00:06:07] knowing your background, I should have asked that question better, just in terms of what tools you use for data visualization, for making your magic happen, not necessarily your deep learning models, though I do know that you do know some deep learning, because I know that you read my book, Deep Learning Illustrated, and in fact, I’m in a huge debt to you, because you did a promotion of my book. And I don’t know if I ever told you this or not, but that day and the next day were the two best sales days that the book ever had, so. 

Kate Strachnyi: 06:41

Wow, look at that. Well, it’s a great book. I love all the colors in there, and you start out really, really simple and it progresses as we go. I was just playing with that book. It’s in my basement office library area, displayed really nice. I should’ve brought it up and kind of showed it off. But one thing you don’t know is actually, I analyzed my post for… I think this was last year. Yeah, I posted this last year, early last year. And that post was one of my top five best-performing posts, so maybe I need to take another book selfie and get some promotions out there for you. 

Jon Krohn: 07:18

Wow. Nice. Well, I will not complain about that, that’s for sure. But so, yeah, I guess the point is, you don’t need to tell us about the deep learning tools that you know and love, or data science tools, but just the data visualization tools, because that is something that definitely data scientists use all the time, or all the kinds of data analytics and data visualization people that are listening to the program. 

Kate Strachnyi: 07:41

Yeah, absolutely. I mean, I love all the data visualization tools that I’ve used so far, but I tend to go back to Tableau, just because it’s the tool that I started with and it’s the tool that I know best. And I always get this question, like, “Hey, what’s your favorite data visualization tool?” And I feel like the tool itself doesn’t really matter as much as just getting the job done and visualizing the data that you need and telling that data story. But for me, the answer has typically been Tableau because it’s given me all the things I need, in terms of telling that data story, and all these data visualization tools, I talk about them like they’re a kitchen, okay? So, let’s say, there is a kitchen, a Tableau kitchen, a Power BI kitchen. Every house, for the most part, has a kitchen. But not in every house you’ll know where the spoon is, or where the fork is, or where the plates are. You’ll know that they’re there, because clearly it’s a kitchen… or how do you turn on the stove. And it’ll take you some time fumbling around, but you’ll make dinner in any kitchen, but it’s a lot quicker for me in my house, which I call Tableau. 

Jon Krohn: 08:44

That’s a beautiful analogy. I love it. But then, that kind of also implies that maybe the best thing about Tableau is that it’s the one you’ve used the most, which I guess is kind of true, but what else… I mean, I know that Tableau is an amazing tool. I have read all kinds of surveys that suggest that it is one of the most popular and in-demand tools in data science, that people should know. So what is it about Tableau that makes it better than other tools that you use? 

Kate Strachnyi: 09:12

I think it’s the ease of use, the interactive, the functionality, the ability to build a dashboard really, really quickly- 

Jon Krohn: 09:21

Oh, yeah, dashboards. 

Kate Strachnyi: 09:21

… and [crosstalk 00:09:22] multiple data sources together. Yes, dashboards, absolutely. [crosstalk 00:09:26]. 

Jon Krohn: 09:26

Yes. That is, and now I’m remembering. I obviously don’t have much experience with Tableau, but it’s one of those things I’m like, I need to learn Tableau because I keep hearing such good things about it. And now today is just another one of those days. 

Kate Strachnyi: 09:37

[crosstalk 00:09:37]. You can take my course. I mean, okay, so if you’ve not used Tableau, I’ll describe it for you. If you’ve used Excel before, and you’ve put together a pivot table. It is like a pivot table on steroids, where you drag and drop things, and you select the rows and columns that you want to visualize, and then it gives you, I think, probably 30 or so charts in the Show Me tool, where you can click a bar chart, a line graph, and pick around how you want to visualize things. It makes things so, so easy, and I think that’s why I fell in love with it right away, because there was zero learning curve. Obviously, you can get really complicated, and go into all these advanced level of detail calculations, and make things animated, and all that good stuff. And that’s the best part, right? It’s easy to start, but you have the room to grow if you need it to do something more complicated. I think that’s why they’re doing pretty well in the market. 

Jon Krohn: 10:29

Brilliant. Well, I mean, I definitely need to do that. So your Tableau course is on the DATAcated Academy? 

Kate Strachnyi: 10:35

Yes, it is. 

Jon Krohn: 10:38

Nice. Okay, that’s easy. I will do that. 

Kate Strachnyi: 10:39

[crosstalk 00:10:39] from Data to Dashboard, take an hour. Yes, do it. 

Jon Krohn: 10:43

In an hour? All right. 

Jon Krohn: 10:52

Eliminating unnecessary distractions is one of the central principles of my lifestyle. As such, I only subscribe to a handful of email newsletters, those that provide a massive signal-to-noise ratio. One of the very few that meet my strict criterion is the Data Science Insider. If you weren’t aware of it already, the Data Science Insider is a 100% free newsletter that the SuperDataScience team creates and sends out every Friday. We pour over all of the news and identify the most important breakthroughs in the fields of data science, machine learning and artificial intelligence. The top five, simply five news items. The top five items are hand-picked, the items that we’re confident will be most relevant to your personal and professional growth. Each of the five articles is summarized into a standardized, easy-to-read format, and then packed gently into a single email. This means that you don’t have to go and read the whole article. You can read our summary and be up to speed on the latest and greatest data innovations in no time at all. That said, if any items do particularly tickle your fancy, then you can click through and read the full article. 

Jon Krohn: 12:04

This is what I do. I skim the Data Science Insider newsletter every week. Those items that are relevant to meet, I read the summary in full. And if that signals to me that I should be digging into the full original piece, for example to pour over figures, equations, code or experimental methodology, I click through and dig deep. So if you’d like to get the best signal-to-noise ratio out there in data science, machine learning and AI news, subscribe to the Data Science Insider, which is completely free, no strings attached, at www.superdatascience.com/DSI. That’s www.superdatascience.com/DSI. And now let’s return to our amazing episode. 

Jon Krohn: 12:48

So in your job, that from your perspective, from your child’s perspective, which I do agree, it’s great that they don’t think you’re working all the time, because I’m sure you feel like you’re working all the time and you’re abandoning your children. But beyond abandoning your children, what do you do on a daily basis in your role? What’s your day-to-day like? 

Kate Strachnyi: 13:09

Yeah, that’s an interesting question. And actually, if you ask my husband, he’s going to say, “You just sit on social media all day,” because anytime he passes by, I’m just scrolling through LinkedIn or making videos. So everyone has an interesting perspective in my house. I don’t want to know what the [crosstalk 00:13:24]. So, yeah, I’m between doing nothing and being on social media all day. I think a large part of my day is actually working on LinkedIn and being on social media, putting out content, engaging with the audience, because half the company is focused on media partnerships, and the only way to obtain media partnerships is to have an audience, and to have an audience, you have to engage that audience. So that’s a part of what I do. Other than that, I obviously run the DATAcated Academy, which involves recording courses, which I was doing right before our call today. I’m recording this new course standing up- 

Jon Krohn: 14:05

[crosstalk 00:14:05] recording, because I… Yeah. Standing up? 

Kate Strachnyi: 14:07

Just for storytelling. Yeah, standing up. It’s actually different. You can project, you can use your hands more, it’s just you’re a lot more with, I don’t know, with the audience, I feel like. And it’s a nice storytelling- 

Jon Krohn: 14:18

Oh, you mean you were recording standing up? I thought that- 

Kate Strachnyi: 14:22

Yeah. 

Jon Krohn: 14:22

… you were saying that the content, like the topic, was standing up. 

Kate Strachnyi: 14:28

No. No. 

Jon Krohn: 14:30

And I wasn’t literally thinking like a lesson on how to get off of your chair, but I thought maybe it was like a lesson on how to do a stand up presentation, and how to gesture properly, and all of these things. But obviously [crosstalk 00:14:47]. 

Kate Strachnyi: 14:46

That actually is a part of it. That’s going to be towards the end of the course, is all about how do you get over the nerves, and how do you prepare, and standing up is going to be part of that course. But, no, today I was focused more on how do you make stories sticky, memorable, how do you get to know your audience, make sure you provide the right level of detail. It’s all about data storytelling. And the course goes live in seven days, like I said, and I’m just starting to record. 

Jon Krohn: 15:11

[crosstalk 00:15:11] record. Yeah. 

Kate Strachnyi: 15:15

Yeah. 

Jon Krohn: 15:16

Oh my goodness, this is the one that goes live. So, yeah, listeners will be able to listen to this. That’s kind of trippy to think about, that something that you haven’t done yet, at the time of recording, is something that when anybody listens to this, you will be done. Yeah, I don’t know why that I find that so trippy. But there’s a [inaudible 00:15:34]… I probably, from your perspective, you’re like, “I wish I was at that point in the future.” [crosstalk 00:15:38]. 

Kate Strachnyi: 15:38

I absolutely do. And every time I set a goal, I’m like, “Okay, I just can’t wait to get to that date,” because I know no matter what happens, I will make it happen by that date. I don’t know how it will happen, but over the next seven days, something will click and the course will just come together. But that’s the other side of things of what I do. 

Kate Strachnyi: 15:55

And then the third part of my day is focused on events. So live events, interviews, conferences. And the next big conference coming up in less than a month, at this point, yeah, the DATAcated Conference. That’s taking up a lot of my energy. 

Jon Krohn: 16:15

The DATAcated [crosstalk 00:16:15]. I bet. I mean, it’s a huge… Coordinating something like that, I can only imagine. It’s something that I would never dream of trying to organize a conference. That seems like a huge undertaking. And I want to take a moment here to talk about… So this is your second conference, right? 

Kate Strachnyi: 16:29

This is my second conference, yes. 

Jon Krohn: 16:32

So your first one was really innovative. I love the way that you ran this conference. So you had 10 minute slots, and I think it was on a weekend, if I’m remembering correctly. 

Kate Strachnyi: 16:42

No, no. I think it was on a Tuesday. I try to keep things on a Tuesday, but it was a one-day event for four hours only. Short story about that, the event is streamed on LinkedIn Live, right? So I’ve not seen another conference that streamed on LinkedIn Live, I wanted to experiment. This whole thing started at the end of August last year, so end of August 2020, I decide, “Hey, maybe I should do a conference.” And I schedule one for about two months out, so October 27 was the date. So I had a little less than two months to get speakers, get sponsors, community partners, what else was there? Promotions, get people to attend, and I’m like, “What’s that missing ingredient? Oh, yeah, attendees.” I had to get attendees for that conference. 

Kate Strachnyi: 17:25

And I did this as an experiment, to see can we even have a conference on LinkedIn Live? So for the next two months, between end of August and end of October, I just spent my time trying to plan all these things out and I tried to simplify things. That’s why I gave speakers only 10 minute slots. And the interesting part is LinkedIn only let you stream for four hours. So at the four hour mark, they will just say, “Enough, cut. That’s it.” No warning, it just cuts you off. So I knew that I had 16 speakers, between which I had to throw in some Q&As, some giveaways for the community partners, some sponsor commercials, and all this great stuff. And I knew that if I am off by one minute, the last speaker will just get cut off and I won’t be able to conclude, which in my mind, is the worst thing that can happen. So I had like a stopwatch, and I was just like, “Okay, go.” And I was so nervous this whole time. But it was probably the best thing to happen to me career-wise, and I learned so much in that process. 

Jon Krohn: 18:30

You mean the conference in general? Not just that everyone spoke for 10 minutes. 

Kate Strachnyi: 18:35

Yep. 

Jon Krohn: 18:35

Or everyone spoke for 10 minutes- 

Kate Strachnyi: 18:36

The conference in general. 

Jon Krohn: 18:36

… it was the best thing that’s ever happened to [inaudible 00:18:37]. 

Kate Strachnyi: 18:40

No, no, no. So people definitely went over, but I cut them off. So- 

Jon Krohn: 18:43

I mean, you have to, with that kind of tight timeline. And you had amazing speakers, some of the biggest names in data science. You had Kirk Borne and Mico Yuk, Ben Taylor, Cassie Kozyrkov and Bernard Marr. Those are big names. So I have no doubt that the conference that’s coming up is also going to be big. And I think, by the time viewers are listening, so it’ll be coming up in just a few days. So tell us about this upcoming one. Is it going to be on LinkedIn Live again? 

Kate Strachnyi: 19:15

Yes, so this one is slightly different because I am not limiting myself to the four hours. It is still on LinkedIn Live, but I found a work around. This event will go on for three days, but only three hours per day. This way if we run over, I have that one hour buffer where I don’t have to stress or pull my hair out while people are going over their time. The speakers will still have 10-minute speaking slots and presentations, but they also have about 8 to 10 minutes of Q&A. So I know that’s about a 50% breakdown, where I think most conferences do like a 20-minute talk, with a 5-minute Q&A at the end. The first conference generated over 5300 comments in a matter of four hours. Now, I literally couldn’t even keep up. It was just flying, right? But I also didn’t have enough time to engage with them. 

Jon Krohn: 20:07

[crosstalk 00:20:07]. 

Kate Strachnyi: 20:07

Yeah, and I really missed out on that, because people are joining live so they can talk to us. And this time each speaker will stay on the live event for some Q&A afterwards. 

Jon Krohn: 20:18

Beautiful. That sounds really smart to me. And so on the note of conferences and social media and LinkedIn, you were talking about one of the things you do day-to-day, is you’re on social media all day. And I’ve got to say, it must be working. So your ability to engage with audiences, as far as I’m aware, in the data world, is unparalleled. So you have 150,000 followers on LinkedIn, Kate. What are your secrets? Is it just putting in the hours? Is it just putting in the time? Or is there anything that people could be doing with… Are there any shortcuts you can provide to us if we’d like to be building a social media following, or just getting more engagement, helping our personal brand as a data professional? 

Kate Strachnyi: 21:06

Yeah, absolutely. So not many shortcuts, but I’ll tell my story of how this happened. I never set out to be a social media anything, right? I was actually a very private person, especially a couple years back. I still never posted pictures of my children. I talk about them, but I’ve never shown them. They do exist though. You heard one of them earlier. But yeah, the way it happened was, when I was just learning Tableau, about six-and-a-half years ago, I decided to just post online. One of my first post ever on LinkedIn was, “Hey, I’m taking this test, the Tableau certification test. And here’s some other goals that I plan to achieve this year.” And I had probably like five likes or one or two comments. And I was like, “Oh my God. People care. People care about my goals,” because somebody said, like, “You can do it, Kate.” And I’m like, “Wow, I can do it.” 

Kate Strachnyi: 22:01

And that became sort of addictive, where you get that feedback from people, you get that engagement. So I kept coming back and I would post more. And that kind of snowballed into something bigger. But I think what truly worked for me is not just posting for the sake of posting, like, “Oh, no. I have to post twice a day,” or something like that. I would literally post whenever I felt like it. So if I had an idea and I wanted to ask a question or share something, I would either go on camera and make a little video, or just post in text, post in pictures, and I would actually care about the responses. So it was never, “Let me post this article to get traffic to this site,” or, “… get people to think this way about me.” No, I would ask, “Hey, what should I learn? Python or R?” And then a war would begin, right? Clearly. But that engagement was interesting for me. 

Jon Krohn: 22:50

[crosstalk 00:22:50] definitely won. 

Kate Strachnyi: 22:51

Yeah, I know, I know. I think I actually did something like that early on. Don’t do that, unless you like controversy. But yeah, I think asking questions that you truly care about the answers goes a long way, because then you’re waiting for answers. Once you get, when you engage with it. And you build a relationship. The data community is huge, but at the same time, it’s very small in the sense that most people know each other, right? You just read off those names from the speakers, and I would predict that the listeners probably have at least heard of most of those speakers. And that’s because we all kind of hang out together. I don’t know. I mean, it is a huge community, but people tend to know each other. And I think building those relationships is exactly what helped. 

Jon Krohn: 23:37

Yeah, I mean, it’s a case in point. And this is off social media, but you and I have met once, and it was at the Open Data Science Conference in 2019, in San Francisco. And I saw you in the hallway. You were standing with Kirk Borne, whom we were just talking about, who’s another mega star of data science. And I saw you two talking together. I knew who he was, but I recognized you, and I knew that we were connected on LinkedIn. And I was like, “Hi, I’m Jon. And there’s no way you know who I am, but I know who you are” And then I ended up later in the conference… Actually, at the end of the conference, Kirk Bourne was leaving, and waiting for an Uber or something to arrive. And I was waiting for an Uber to arrive. We got a great photo together, ended up building some rapport, and I also sent him a copy of Deep Learning Illustrated, which he said some nice things about online. So I couldn’t agree more that it’s interesting that data science has grown so much, as a community. But online, we’re connected all over the world. You have people that are commenting on your posts from everywhere. And then once COVID is over and the conferences happen again, it’s amazing how just a handful of conferences, you can be running into the same people over and over again. 

Kate Strachnyi: 24:57

Oh, absolutely. Back, pre-COVID days, I would attend conferences, and unknowingly, people would come up to me and say, “Oh my God, are you Kate?” And I’m like, “Yeah, why?” It’s like, what’s the big deal? They’re like, “I’ve been watching you for four years.” I’m like, “Oh, wow. Okay.” But these are the people who don’t really comment or engage. They just see your content every single day so they feel like they’d know you. Sometimes it does get weird. I have definitely had some awkward moments where I wish people didn’t really know me. Like I got a message on LinkedIn saying, “Was that you walking past Bryant Park? I think I just saw you. I’d love to connect.” And I’m like, “Oh God, this is weird.” Like- 

Jon Krohn: 25:42

Oh, man, [crosstalk 00:25:45]. 

Kate Strachnyi: 25:44

I mean, obviously, telling the data people who would recognize me, but I do miss the in-person conferences. It’s so different. I love my DATAcated virtual conference, but one day I hope to run an in-person conference, probably in New York or maybe somewhere else. 

Jon Krohn: 25:59

Nice. Amazing. And we haven’t talked about that, but now that you’ve mentioned New York and you’ve mentioned Bryant Park, which people who’ve been to New York may know that that is a beautiful park in Midtown Manhattan. And that’s, I mean, just as a little bit of context, that is where you live and where you’re calling from today, right? New York? 

Kate Strachnyi: 26:16

Yes, it is. Yes. Lived here since 1996. And I don’t know why I looked at the calendar when I said that, like [crosstalk 00:26:24] it’s on here. 

Jon Krohn: 26:25

[crosstalk 00:26:25]. 

Kate Strachnyi: 26:25

Yeah, 1996, it was. 

Jon Krohn: 26:27

[crosstalk 00:26:27]. 

Kate Strachnyi: 26:27

Yeah. Exactly, confirmed, uh-huh (affirmative). 

Jon Krohn: 26:31

Oh, yeah, so you mentioned 1996 and moving to New York, which got me thinking, so building this amazing following, all these companies, over 100,000 people following you on LinkedIn, when was that post? How many years ago was that, that you had that first post where you realized you had engagement and you had this passion arise of becoming a social media influencer? 

Kate Strachnyi: 26:54

Yeah, I think that was probably about five years ago. And I think the growth, it didn’t happen so fast, but once it picked up, it actually… tI probably more than doubled since last year in terms of the number of followers. Maybe the conference had something to do with it, or potentially LinkedIn Live interviews where I would bring on some really cool people and get them to talk about their stuff. Yeah, I think that’s probably why the following has grown so fast. That, plus being consistent. I probably post at least once a day, every single day. In fact, my analytics for 2020 said I post 2.47 times a day on average. Might be excessive to some, but- 

Jon Krohn: 27:39

Wow, especially if those are all… No, I mean, especially if they are things that you’re genuinely interested in, and then it’s easy to stay engaged to yourself. And yeah, that makes a lot of sense to me. And so, yeah, things just continue to grow and grow. Now you are an avid runner, right? So do you think that fitness helps with being so consistent? Do you think that there’s a relationship between consistency, because you need that to be successful in any kind of fitness pursuit, and this incredible consistency that you have with your work? 

Kate Strachnyi: 28:16

You know, honestly, I’m not sure if there is any relationship between fitness and social media. Definitely some relationship with being consistent. But interestingly, I think running has actually helped me grow the following, because in 2019 I posted quite often about running. I had a challenge to run 1000 miles in 2019, and I ended up completing that challenge; I remember the last month in December, I still had 100 miles left, and I decided to finish it with a 12 pound weighted vest, just because why not challenge myself a little bit more? But I was very public with the challenge, and I always posted the data visualizations of my pace and my miles, and am I going to make it. But it started on January 1 of 2018, where I posted something online that said, “The journey of 1000 miles begins with a single step.” So then I’m like, “I should run 1000 miles.” And it was that random. Because [crosstalk 00:29:16] I didn’t really run that much until like… I think 2018 was the year I actually started running in general. So it happened fast. 

Jon Krohn: 29:27

Oh, interesting. Do you use Tableau to track all of your running and create a dashboard? 

Kate Strachnyi: 29:32

Yes, so I used Runkeeper to actually track the runs, but they have an export feature where you could just get a CSV file and plug that into, yes, you guessed it, I used Tableau. But sometimes I used other tools too- 

Jon Krohn: 29:46

I was kind of joking. I love that that ended up being right. That’s amazing. 

Kate Strachnyi: 29:50

Absolutely. So like, yeah. 

Jon Krohn: 29:52

Nice. Well, that was, yeah, great to hear about. I have another question about another thing that you do on the side, that you haven’t mentioned yet, which I might be misstating this, but I’m pretty sure you’ve published four books, right? 

Kate Strachnyi: 30:07

You are correct. Yes. I forgot all about those. 

Jon Krohn: 30:13

I mean, it must have been a lot of work. It’s crazy that you could forget about them at all. I have scars from writing by book, all the time. I’m thinking about them. I can hardly sleep at night from the scars. But do you want to tell us about that? And I think also something that’s interesting about what you did, and I think this is something in particular that our audience might be interested in, so people have ever thought about writing a book, and how to do it, if I’m right about this as well, I think all four, or some of them at least, are self-published, right? So- 

Kate Strachnyi: 30:45

All four are self-published, yep. 

Jon Krohn: 30:47

So, tell us about that. So, why would somebody self-publish? What are the advantages of doing it that way? Tell us about your experience. And maybe even tell us a little bit about the content of the books. 

Kate Strachnyi: 30:59

Yeah, absolutely. Happy to do so. So the first book, Journey to Data Scientist, it started with my wanting to determine, do I want to get into working with data? And at that point I was in risk management, regulatory compliance, doing consulting for banks. Completely different side of my career. But I figured the best way to understand if this is something I wanted to do was to talk to people who work in data science. So I set up interviews with some individuals, and I’m pretty sure Ben Taylor was one of the people I interviewed for that first book, from DataRobot. He wasn’t at DataRobot at the moment, but anyways, so I got on these calls. And as I was having these conversations, I noticed that people had really interesting stories. They were musicians, or they had all these different backgrounds. And I decided, “Hey, maybe other people are sitting around, just like me, thinking about getting into data, but they don’t know if it’s for them. So why not publish a book?” And I love trying new things, just for the sake of learning how to do it. I feel like that’s really the best way to learn absolutely anything. You want to learn basketball, take a ball, throw it in the hoop, right? 

Jon Krohn: 32:10

100%. 

Kate Strachnyi: 32:11

Don’t read about it. Just do it. 

Jon Krohn: 32:12

Mm-hmm (affirmative). 

Kate Strachnyi: 32:13

Obviously I researched things along the way, like how do I self-publish a book? And I decided to go the self-publishing route, because after some research, I learned that, A, you keep your royalties, you own everything. And I’m kind of a control freak so I wanted to design my own cover, I wanted to write things my way. I didn’t want people to say, “No. I think you should have said it this way.” No, I don’t like control. So that was book number one. 

Kate Strachnyi: 32:39

The second book is called The Disruptors, and I’ve actually interviewed Kirk Borne, Bernard Marr, Carla Gentry, and several others, in terms of trying to learn how are they disrupting the data industry? Really great stories, really fun interviews. I even had DJ Patil, who is the Chief Data Scientist at the White House, take part in that book. That was my most difficult person to get on- 

Jon Krohn: 33:05

Yeah, former. 

Kate Strachnyi: 33:06

Former. Yes, former. 

Jon Krohn: 33:07

Oh, yeah, really? 

Kate Strachnyi: 33:09

But, yeah, I mean I remember it [crosstalk 00:33:11]. 

Jon Krohn: 33:12

[crosstalk 00:33:12]. 

Kate Strachnyi: 33:13

Yes, yes, and I have stories in the book about that as well. So really interesting. I remember asking him, on LinkedIn actually, “Hey, do you want to take part in my book?” And I think he was like, “Who even are you? And why? Why would I? How are you [crosstalk 00:33:28] credibility.” So I’m like, “Yeah, I just want to write a book.” And he’s like, “Okay-” 

Jon Krohn: 33:33

Is that all he wrote? 

Kate Strachnyi: 33:35

Well, I mean, I don’t want to put words in his mouth, but it was kind of… A few others also told me kind of like, “Hey, what are your credentials? Do you have a PhD?” And I’m like, “Yeah, no, I just want to write a book.” But he was super nice and he gave me his time, and I really appreciated that. So that was book number two, again self-published, because it’s so easy. I use Amazon, and it’s for people who are thinking about writing a book. It’s as easy as uploading a PDF to the website. That’s all you have to do. I mean, there are some steps in between of formatting, and I hired some people on Fiverr to do some of my copyediting and making sure the book looks like a book, because I’m not a fan of just formatting text all day. And some people are just really good at it. So yeah, that’s two. 

Kate Strachnyi: 34:22

I’ll briefly talk about the next two. Those are both co-written with others. So Mothers of Data Science, I co-wrote with Kristen Kehrer. And again, we interviewed some really awesome mothers of data science. I think one of the most interesting was the author of Weapons of Math Destruction, Cathy O’Neil. He had some really interesting insights. 

Jon Krohn: 34:45

Oh, yeah. 

Kate Strachnyi: 34:48

So, yeah. Yeah. And the last book was Data Literacy for Kids, coauthored with Jordan Morrow, who at the time was the Global Head of Data Literacy at Qlik, but now has moved on to Pluralsight. So all fun experiences, but I’m not sure I would write a book, like it’s not on my list this year, that’s for sure. I already know that. Because people have asked. I’m like, “No. Other things, other things.” [crosstalk 00:35:12]. 

Jon Krohn: 35:12

Too many miles on this year. 

Kate Strachnyi: 35:14

Yeah. Exactly. 

Jon Krohn: 35:17

Well that’s brilliant. Thank you for that bit of insight. So I guess to kind of summarize the self-publishing adventure, so obviously you get complete control, if you go down that route. You get all the royalties. I mean, there must be some… When you [crosstalk 00:35:32] there must be some. 

Kate Strachnyi: 35:34

Yeah. [crosstalk 00:35:34]. 

Jon Krohn: 35:34

Yeah, but it’s like it’s a small percentage, whereas if you publish with a major publisher, the standard of the industry is that you get 12.5% of sales in royalties. So for you, it was probably the other way around. [crosstalk 00:35:48]. 

Kate Strachnyi: 35:47

Yeah. But I guess the idea with working with a publisher is you get the credibility of, I’ve been published by a publisher, and you get them to market your book, which I personally never needed. I didn’t need the marketing support because that’s what I enjoy doing the most, so. 

Jon Krohn: 36:07

Yeah, that makes that makes a lot of sense. Yeah, you definitely, you have your marketing channels all set up. You have an audience ready. I think there are some shifts happening, though. I think that in the last few years, people like you, people like Andriy Burkov, by self-publishing, they have shown that this is a legitimate route to having a bestselling book. Andriy Burkov’s Hundred-Page Machine Learning Book, it’s one of the bestselling machine learning books in recent years, and, yeah, completely self-published. I think that part of the key is that you have to have the self-awareness to say, “Okay, what parts of book publishing am I not amazing at?” So in your case, marketing, no problem. But maybe, like you were saying, typesetting or something, isn’t the way that you want to spend your time. So using a service like Fiverr to find people to do that, that makes a lot of sense. It’s good tips. 

Kate Strachnyi: 36:58

Yeah. 

Jon Krohn: 36:59

Alright, Kate, so we’ve talked about your favorite visualizations tools. We’ve talked about Tableau. Do you think that that is one of the most important skills, that people working in data should have? Or, I guess I should say more… Or let me make some guesses here. So based on what you do for a living, I think it’s safe to say that you think it’s important for people who work with data, whether they are machine learning experts, or data scientists, or probably even if they’re in management related to data, being able to visualize and tell a story around that data, I suspect you would say is one of the most important things. 

Kate Strachnyi: 37:38

Yes. Yes, you got it. 

Jon Krohn: 37:39

And so the reason why I ask is because one of the things that our audience is most interested in is, for people to enhance their careers, or their capacity, as a data professional, so obviously data visualization is what you’re going to say… Beyond Tableau, are there particular tools that you highly recommend? 

Kate Strachnyi: 37:58

Again, I’m going to go back to the tool, I don’t think it matters as much. I mentioned Tableau a few times just because I’m comfortable with it. But I think there are some guidelines that people can follow, no matter who- 

Jon Krohn: 38:09

[crosstalk 00:38:09] that’s even better. Even better. 

Kate Strachnyi: 38:10

… or programming language that they use, right? So a couple, I’ll mention, are using color intentionally. You’d be surprised, when people get their hands on any data-based tool, or software, or programming language, they’ll throw the colors of the rainbow on there, just because it looks so pretty. And what strikes me as really interesting is people don’t really… They don’t really think that that makes a difference, right? Especially the more technical people, who have spent so much time cleaning the data, getting the sources to talk to each other, wrangling it all, making sense of everything. And then that last part, the last mile of analytics, as some like to call it, they don’t spend as much time in there, because they’re like, “Oh, I’m not creative, or it doesn’t really matter.” But for me, that’s truly the most important part, because that’s the section of the process that gets seen by your audience, by your decision makers, by your management, leadership, whomever. And that makes all the difference. You can use color intentionally. You can reduce clutter, remove some of the gridlines, and really clean up your visualizations, format them so they look really good. 

Kate Strachnyi: 39:19

Use the right chart to begin with. That’s another common mistake that I’ve seen people do, is not use the proper chart for representing the specific data type. And all those tiny little changes go a really long way. I mean, I remember when I started visualizing data, probably if I look at things now, I would laugh and kind of criticize myself and judge myself, but I simply didn’t know better. I felt like whatever the default settings of Tableau were at the time, I just thought they were great. Sure. If it’s a bar chart, how much better can we get? But then over time, I kept researching and looking at really good dashboards and data visualizations, and learned some of those best practices. So now I’m kind of on this mission to teach others that there is a way there, there’s like a checklist you can follow to say, “Okay, is my text all horizontal? Can you actually read it? Are the colors contrasted enough that we think about color blindness or printing in black and white?” So many things to consider, that to me is common sense, but I am realizing that to most others, it’s something that they don’t even really give much thought. 

Jon Krohn: 40:23

Those are such good tips. Yeah. Thank you so much for answering a better question than the one that I asked. That’s so valuable. Yeah. You’re exactly right. These are the things that are so important. For people working with data, you’ve got to be presenting yourself, putting the best foot forward. You could be using the most sophisticated modeling technique, but if you can’t make it clear why that’s valuable to your stakeholders, then it almost doesn’t matter in some ways, like it might not… Yeah, so I think that makes a lot of sense. And you can, presumably, all of the things you’ve mentioned, or presumably most of them, are the kinds of things that you cover in the DATAcated Academy, right? 

Kate Strachnyi: 41:10

Oh, yeah. That’s probably 20% of the things I actually cover in the Academy. We go, deep dive into what are the best practices for using every chart type. It gets really detailed. 

Jon Krohn: 41:22

Beautiful. That sounds hugely valuable. So you’ve accomplished so much. You have this quickly, exponentially increasing audience on LinkedIn, you have 4 self-published books, you have several businesses. So what’s next for you? Where are things going? 

Kate Strachnyi: 41:43

Yeah, that’s a great question. So I’ve been thinking a lot about where are things going. And I think for me, 2020 was the year of exploration. I tried a whole bunch of things. So we have the books, we have the events, we have the media partnerships, the live events, conferences. I also have DATAcated merch, if people want a DATAcated t-shirt or a mug or something. 

Jon Krohn: 42:05

Oh, wow. 

Kate Strachnyi: 42:06

Yes. So I think for me, for 2021, is the year of focus. And I’m focusing in on two things, one being those bigger events and conferences, and the other one is going to corporations with the courses that I’m building and that I have built, in addition to expanding the Academy itself to including external guest authors. So I want other people, other instructors, to come in and teach at my academy, because clearly I’m not an expert in, let’s say, Python, right? But I have a course I need to develop on how to go from data to dashboard using Python, Plotly Dash. Well, yes, I could spend the time and invest in my own education and learn it, which I plan to do, but I feel like I’ll still won’t be the best person to teach that course, so I’m going to work with external instructors. And that also gives me more time to focus on going to corporations and showing them, here is the sales catalog, here is what we’ve got, here is how we can help your staff learn data. 

Kate Strachnyi: 43:08

So those are some of the things. I’m sure I’ll come up with something weird, like coming up with a data literacy board game or something. I think that was on my list for this year. We’ll see what happens… Or maybe an app. I don’t know. I tend to run in different directions and get excited about random things, but I’m trying to focus really hard. 

Jon Krohn: 43:25

Well, I’m confident whatever you choose to do will be hugely successful like everything else you’ve done in the past. So one question that we always ask on the SuperDataScience Podcast, which I hadn’t even mentioned to the audience, that this is not your first time on SuperDataScience Podcast. 

Kate Strachnyi: 43:42

Oh, yeah. 

Jon Krohn: 43:42

So you were on a couple of years ago. 

Kate Strachnyi: 43:46

It was a couple of years ago, I think maybe 2018 or 2017. I don’t remember. Yeah. 

Jon Krohn: 43:53

And anyway, so you may be aware, you may recall that- 

Kate Strachnyi: 43:58

What’s coming? Oh my God. 

Jon Krohn: 44:02

We asked for a book recommendation. We’d love to know what you’re reading right now. 

Kate Strachnyi: 44:07

Yeah, absolutely. So I’ll tell you two things. One, what I’m reading right now, and then a book recommendation that I typically give. So I’ll start with right now, I am reading a book called Your Next Five Moves, which actually is the reason I’m thinking about some of my next moves, and focus has been one of those areas that came out of that book, but it’s by Patrick Bet-David, and a really, really amazing book that really gets you thinking about strategy and thinking ahead. So for the longest time, for some reason, I’ve not been really good at planning ahead. I can take action today on whatever and announce a new initiative, but I’m not planning, two, three years out or what I’m actually going to do after I launch this initiative. And that’s something I’m working on trying to get better at in my personal life and my professional life, just five steps ahead. He uses the reference of chess and how the grandmasters think 12 steps ahead now, and I’m like, “Oh, man. Let’s practice with one, right? What happens after this one thing?” So baby steps. That’s a really great book I’m wrapping up probably in the next few days. 

Kate Strachnyi: 45:16

Then the book recommendation I typically give is a book by David Goggins called Can’t Hurt Me. Truly, truly life-changing book about a man who changes his own life and goes from really overweight exterminator, who is extremely unhappy with his career, with his life, to probably the most fit guy you’ll ever meet, and the most determined, the most, as he says, “stay hard.” Like he’s a beast. And if you’ve never heard of him, just look him up. Follow him on social media. He always puts out content that will make you feel bad about yourself. You will feel like a really lazy person every time you watch him play for like [crosstalk 00:45:57]. 

Jon Krohn: 45:57

Yeah, that’s what I want. [crosstalk 00:46:00]. 

Kate Strachnyi: 46:01

More ways to feel bad about yourself. 

Jon Krohn: 46:02

I don’t feel bad after today. 

Kate Strachnyi: 46:06

No, seriously, that book has completely changed my life and how I perceive challenges. And I always liked challenges and doing things that are complex and difficult, but after that book, I feel like anything I’ve ever done is nothing compared to the things that he was able to accomplish and obstacles that he overcame. So definitely recommend that. If you have the option of doing the audio book, I recommend that even more because he delivers the audio book in the form of a podcast. He has somebody reading his book, but also… I forget who the interviewer is, he asks him deeper questions like, “Goggins, what were you thinking in this moment? You just completed this crazy 100 mile run, what were you thinking?” And he’s just sitting there and they’re just having a great time. So definitely recommend that. 

Jon Krohn: 46:52

That is a cool audiobook format. I wasn’t aware of anyone doing anything like that. I have a feeling when you make an audiobook of your book, it’s going to be like that. 

Kate Strachnyi: 47:02

Yeah, I should do that. 

Jon Krohn: 47:02

And make it full of properly colored visualizations, the right charts. 

Kate Strachnyi: 47:08

An audiobook with colored visualizations, really? That’s… 

Jon Krohn: 47:12

Yeah. Yeah, yeah, yeah, that made a lot of sense. 

Kate Strachnyi: 47:15

[crosstalk 00:47:15]. 

Jon Krohn: 47:15

That was the best idea I’ve had today. All right, so with that, if there’s anyone out there who’s listening who isn’t already following you on LinkedIn, how can they find you? What are the best places… I think it seems clear, finding you on LinkedIn is the best place to follow you, but is there any other way that our audience should be following you? 

Kate Strachnyi: 47:43

Yeah, I would say LinkedIn is probably the number one place where you can find me. I live there. I’m also on Twitter, @StoryByData. I do have other social media accounts, but I rarely go in there. So if you really want to find me, I’d say LinkedIn. But Jon, I just realized you’ve not said my last name yet, so you need to tell people my full name. So they can find me. 

Jon Krohn: 48:04

Oh, well, that’s because there is an intro segment that I recorded separately, and so the audience will have heard your last name even though I haven’t said it to you. But yeah, I think that this gives me a good opportunity to practice saying it. Kate Strachnyi. 

Kate Strachnyi: 48:23

Oh, there you go. Okay, thank you. Just wanted to confirm that it still works, yes. 

Jon Krohn: 48:27

So you can find Kate Strachnyi on LinkedIn. And she would love to also tell you about what her last name means, because it’s a really cute last name. 

Kate Strachnyi: 48:40

Oh, yes, it’s adorable. It actually took me a full year, after marrying my husband, to actually taking his last name because of how adorable it is. So for those who have any background in Russian or Ukrainian, the word Strachnyi actually means ugly or scary man. And I try to bring this up as much as I can at live events, where I would actually meet people and they’re like, “Hey, what’s your name?” And they try to pronounce the last name, you know, the whole like, “Oh, how do you say that? That’s beautiful.” I’m like, “Of course, it’s beautiful. Let me tell you what it means.” And it’s typically the men who ask. And so I tell them, it’s like an ugly or a scary man, and then they think I’m talking to them, and I’m like, “No, no. I’m just telling you what my last name means.” It’s always a good icebreaker for them to remember [crosstalk 00:49:24].

Jon Krohn: 49:24

It’s an ugly or a scary man. 

Kate Strachnyi: 49:27

Yeah, exactly. 

Jon Krohn: 49:27

That’s me all the time in conversation. I hear that constantly. Right after I suggest that people have great visuals in their audiobooks. [crosstalk 00:49:36]. 

Kate Strachnyi: 49:36

[crosstalk 00:49:36] that was perfect. Please keep that in. Keep that in the podcast. 

Jon Krohn: 49:43

Oh, we will absolutely keep that in the podcast. I am not embarrassed. All right, thank you so much for being on the program, Kate. Is there anything else that I missed, that you would like to add? Anything like maybe what your middle name means, or anything like that, that I missed? 

Kate Strachnyi: 49:59

I mean, if we’re going to talk about names, I’ll tell you. I’ve changed my names four or five times, legally. So, yeah, there’s that. I used to be much… I had three names, and none of them were Kate Strachnyi, so- 

Jon Krohn: 50:11

Whoa. 

Kate Strachnyi: 50:11

I’m not a criminal, I promise. I just had a lot of confusion coming from Tadjikistan, I was named with a very interesting, unique name that is impossible to pronounce, both first name and last name. And I had a middle name, which is really long as well. So as I kept going through the journey of changing my name, I finally landed on Kate Strachnyi. And I told my husband already, even if he leaves me, I am not changing my name. 

Jon Krohn: 50:37

[crosstalk 00:50:37]. 

Kate Strachnyi: 50:37

I’ll be Strachnyi forever [crosstalk 00:50:41]. 

Jon Krohn: 50:41

And I like that you were like… So now it sounds clearly, so you married your husband because you liked the sound of his last name? 

Kate Strachnyi: 50:48

Uh-huh (affirmative). 

Jon Krohn: 50:49

And then you later discovered what it meant- 

Kate Strachnyi: 50:52

[crosstalk 00:50:52]. 

Jon Krohn: 50:52

… and so you didn’t actually change your last name until after a year of being married. 

Kate Strachnyi: 50:57

No, I still remember learning his last name. We were dating, and I’m like, “You’re joking.” He’s like, “No, no. That’s it.” I’m like, “Okay, well that’s great. That’s good to know.” 

Jon Krohn: 51:08

All right, well, would you tell us your Tajikistanian full name, just [crosstalk 00:51:13]. 

Kate Strachnyi: 51:12

It’s a Russian name, so it used to be Kseniya [Vadimovna Alayeva 00:51:17], so far from Kate Strachnyi, I’ll tell you that. 

Jon Krohn: 51:19

Yeah, I just got it. What was the first name? 

Kate Strachnyi: 51:22

Kseniya, yeah, so- 

Jon Krohn: 51:23

Kseniya? 

Kate Strachnyi: 51:23

I had telemarketers call my house and say, “May I speak to K- K- Wow?” They would just literally call me K-wow, because they didn’t want to try the rest of the name. And all my teachers messed it up, it was just terrible. So early on, I think I was like 13, I’m like, “Guys, call me Kate.” I just came up with a random name and then it stuck. So now people know. 

Jon Krohn: 51:45

No, I like it, although I don’t mind Kseniya either. And you aren’t the first Kseniya I’ve ever met, but- 

Kate Strachnyi: 51:53

I’m the first Kseniya I’ve ever met, so you know. 

Jon Krohn: 51:56

Really? Oh, that’s interesting. 

Kate Strachnyi: 51:56

Yeah. 

Jon Krohn: 51:57

Now I can think of one, very specifically, right now. Anyway, the audience doesn’t need to hear about that. But I’m glad that they got to hear your whole original name. That’s super interesting. What a fun fact. Have you ever revealed that on a podcast before? 

Kate Strachnyi: 52:13

I don’t remember. Honestly, I’m so open on podcasts that I don’t really think much as I speak so I really don’t think I have. So if anything happens, and I have some people after me, then it’s going to be because of the podcast, so might be your fault. [crosstalk 00:52:31]. 

Jon Krohn: 52:33

I think I avoided anything that was incriminating today. Next time we’ll get you to incriminate yourself on air. 

Kate Strachnyi: 52:44

Okay, oh, there’s going to be a next time. Wow, look at that. 

Jon Krohn: 52:45

[crosstalk 00:52:45] just for the incrimination purposes, that’s why we’ll have you on again. 

Kate Strachnyi: 52:48

[crosstalk 00:52:48]. 

Jon Krohn: 52:48

But also because you’re an amazing guest. Thank you so much. We’ve learned so much from you. I’ve learned a lot from you, and we had a lot of fun recording this. I have no doubt that the audience learned a lot. Hopefully they didn’t mind all of my ridiculous jokes and ideas. I’m sure they gained a lot from your content and ideas. And yeah, look forward to having you again on the podcast sometime. 

Kate Strachnyi: 53:10

Awesome, well thank you so much for having me back. 

Jon Krohn: 53:12

My pleasure. And yeah, I guess even though we both live in New York, the next time I’ll see you maybe will be ODSC US 2021 in San Francisco, where I will be. 

Kate Strachnyi: 53:22

When is that happening? 

Jon Krohn: 53:24

In November. And they’re planning on having an in-person conference. Isn’t that interesting? 

Kate Strachnyi: 53:28

I’ll get my mask ready. Let’s do this thing. 

Jon Krohn: 53:31

Well, by then we shouldn’t even need masks. 

Kate Strachnyi: 53:34

Yeah, okay, sure. Let’s end on an optimistic note. Yay. Let’s do that. 

Jon Krohn: 53:39

All right. Thank you so much, Kate. Catch you again soon. 

Jon Krohn: 53:48

Wow, what a silly time we had in that episode. But we also covered a lot of rich ground, including the critical importance of effective data visualization and communication. No matter whether you’re an analyst, data scientist, engineer, manager, if you work with data, you’ve got to be able to clearly express your findings and approaches to stakeholders. We also covered Kate’s most valuable guidance for data visualization and communication, and how you can grow your professional social media following into the hundreds of thousands. 

Jon Krohn: 54:19

As always, you can get all the show notes, including the transcript for this episode, the video recording, any materials mentioned on the show, and URLs to Kate’s LinkedIn and Twitter profiles, as well as my own LinkedIn and Twitter profiles at www.superdatascience.com/441. That’s www.superdatascience.com/441. When you add us on LinkedIn, it might be a good idea to mention you were listening to the SuperDataScience Podcast so that we know you’re not a random salesperson. 

 Jon Krohn: 54:48

If you enjoyed this episode, kindly leave a review on your favorite podcasting app or on YouTube, where you can enjoy a high fidelity video version of today’s program. It sure is nice to be able to put smiling faces to all the laughs we had today. I also encourage you to tag me in a post on LinkedIn or Twitter to let me know your thoughts on this episode. I’d love to respond to your thoughts in public, and get a conversation going. All right. It’s been so great. Thank you for listening. I’m looking forward to enjoying another round of the SuperDataScience Podcast with you very soon.