Jonas Christensen 2:22
Kate Strachnyi, welcome to Leaders of Analytics. It's fantastic to have you on the show.
Kate Strachnyi 2:29
Awesome, thank you so much for having me here.
Jonas Christensen 2:31
Yeah, I'm really happy to have you on here. Without further ado, let's get straight into the questions for today. So I've given a bit of an intro of you already. But in your own words, could you tell us a bit about yourself, your career background and what you do?
Kate Strachnyi 2:46
Yeah, absolutely. So, I started my career in risk management financial services. And then about eight years ago or so, I've sort of journeyed into data analytics. So, it came sort of as an accident where I was looking for a role that simply kept me working from home, because I was expecting my first child at the time and at the moment, I had a very busy schedule. I was doing consulting, travelling, late nights, weekends and lucky for me, I was, after several months of searching, I don't know if you can call that luck, I was able to find a role that happened to be a Data Analytics Insight Strategy Manager. Had no clue what that meant but I'm like, ''Yes, I will do it. As long as it keeps me home, I will do whatever it takes''. And this is pre-COVID, so this was not the norm at the time to be able to work remotely. So, I basically was given a dataset as part of my first gig on the job and I was given access to a data visualisation platform. And it truly was love at first sight. I completely fell in love with data analytics, data visualisation, data storytelling. And then I basically put all of my efforts into learning everything I can about this space, the data visualisation data science. I took courses. I've read every book I can get my hands on and ultimately started interviewing other data scientist, other data professionals. That was sort of how my data journey started. Fast forward to march 2020, I ended up leaving my employer because I wanted to start my own company called DATAcated, which is really focused on educating data professionals, bringing communities together with conferences, live shows. We also do media partnerships for data companies to help promote their data products, data services. And yes, I've been off on my own since March 2020 and loving every minute of it.
Jonas Christensen 4:40
Yeah. Wow. And you know what? That really comes through in the content that you publish. I've been following your content for probably a couple of years now on LinkedIn. And first of all, there's just so much of it. And you can really see that passion that you have for the topic and your chosen vocation that you've fallen in love with. You can really see that shine through. And Kate, you have built this huge worldwide community of data lovers in what I'd say is a very short time really. Just a few years. And anyone like me who has a LinkedIn profile has likely come across this content that you put out and you've created the DATAcated brand, as you talked about as well, which does quite a lot of things. Could you tell us a bit about what DATAcated is and what it's about?
Kate Strachnyi 5:27
Yeah, absolutely. So, interestingly, I don't even remember how I came up with the term DATAcated or DATAcated, but essentially, it means being dedicated to data, as well as the sound of my name, Kate, sort of baked into that. And I've had several people tell me, I should call it DATAkated with a K instead of a C, but I think for whom English is not their first language, I think it would be a little bit lost on them with what DATAcated really means. But yeah, essentially, the company is focused on a few different things and I touched on this a little bit. But we started out as an academy, teaching individuals how to use tools like Tableau, Power BI and CLICK and learning about the best practices for data visualisation and data storytelling. And currently, we're transitioning that all into a community called DATAcated Circle, which if folks are interested in flying to join the circle, it is free to join. You just have to go to circle.datacated.com and there's a quick application there. But the goal here now is to build a community of data professionals across all different industries, all regions, at all levels and really across different professions within data space. So, think data analysts, data scientists, machine learning engineers, students who are just learning about the chief data officers, I want them all centrally located in this one stop shop community where we'll have live sessions. We'll have courses. I'm currently importing my academy into the community to sort of have this one central place and that's really all about the data professionals and the community. The other side of the business really is supporting companies that are innovating in this space and are trying to reach an audience. So luckily, I have been able to build a wide enough profile, I guess, on LinkedIn, where I do have the ears and eyes of some of the data folks out there who are looking for the next product to use. So, the way I really help organisations is help them share their message by either going on the dedicated show, putting out a dedicated feed newsletter or different methods really, where we just help educate the community on some of these new practices like data mesh, data fabric, data ware. Educating them on some of this cool new technology that's coming out there that they simply have not heard of and I get to just have so much fun, just engaging and interacting with all my favourite people.
Jonas Christensen 7:56
Yeah, you would no doubt have fun with that. And I think it's so valuable what you're doing there, because as someone in this field, one of the things that give me fear of missing out or make me feel like I know nothing at times is just the vast amount of new tools and techniques that are coming out constantly. It's so hard to keep up with what actually matters and frankly, we don't know what matters today, whether that's going to matter in five years, from a tooling perspective. How do you help navigate students and others through choosing what to learn versus what not to learn?
Kate Strachnyi 8:31
Yeah, I think it all depends on what this specific individuals goals are, right? In some cases, they simply want to get a job, let's say, as a data analyst and they just want to create dashboards all day. In that case, I usually tell them, ''Pick one too, let's say Tableau, Power BI or CLICK and learn this tool really well to the extent where you can just take any dataset, put together data visualisation, put together some dashboards''. Because the beauty of that is, let's say, you end up getting a job and you know Tableau really well, if the company that ended up hiring you uses Power BI or something different, well, it doesn't matter that much because once you've mastered the proper data visualisation best practices, you know when to use which chart, you know when to use which colours and sort of design principles, then the tool itself is pretty similar. I always tell people it's sort of like a kitchen inside a house, right. You have a kitchen and I'm assuming most people who are listening to this have a kitchen unless they're one of the cool people who live in a bus or van and just travel the world. I have a few friends like that, but the majority will have a kitchen and your kitchen will have forks and you'll have a drawer for your utensils and knives and plates. And similarly, Tableau will have a place where you can change the colours of the bars and change maybe the currency symbol in front of your numbers. And then Power BI will also have sort of their kitchen, right? Things might not be located in the exact same places as they were in the kitchen that you we're used to but chances are they also have the forks and knives and all the formatting tools. So, it's really a matter of just knowing where the things are and it's a lot easier to learn that once you've already mastered one tool.
Jonas Christensen 8:34
Great analogy. I love that kitchen analogy. And I think those tips are really helpful for someone starting out in their career, because on the face of it, all these things are very similar. And it's hard to pick which one to go for, but going for one and going deep and you'll learn something along the way that you can use across other things. That's good. Now, Kate, you seem like a very productive person. So, what does a typical day look like for you and what drives you to keep going at this pace?
Kate Strachnyi 10:43
Yeah, thanks. I'd like to think of myself as productive but then again I'm looking at my huge to do list of things I want to accomplish. Because I think I'm very driven and motivated, not sure exactly why. But there's just a million things I wanted to get done every single day. So, I'll walk you through my typical day and they do range sometimes. But I essentially wake up at five o'clock in the morning. Sometimes a bit earlier, sometimes a bit later. But on average, I'm up by five. I have my first coffee, because I have two coffees per day and one has to be at 5am. And then I get to my desk. So, everybody sleeping. I have two kids, two girls, and my husband here who sleeps a little later. So, I sort of get the morning to myself between 5am and 7am and that's when all my productive work happens. It's interesting, because sometimes I forget that I've even done the work, because my body might still be sort of sleeping, right? You just wake up. I get all these emails out and I'm like, ''Wow, when did I do this?''. So, those are my first two hours. Then 7am to 9am is typically for the kids. So, making breakfast, packing their lunch, getting them to school, then by the time they get home, it's about 8:30. I have my breakfast and then nine o'clock, it's sort of back to the office. My office is in my house. So, it's very convenient. Very little travel time for me. And then from 9am to 2pm, I essentially take some calls. I only have about four slots a day that I tend to take calls. And yeah, 9am to 2pm, Monday through Thursday are my work hours outside of that short, early morning stint. After that, it's really about the kids again, so go pick up the kids. Lunch, dinner, homework, bedtime, whatever, running and TV, very minimal TV in my life and some reading and then off to bed like by 9:30. That's my day and that's just Monday through Thursday. Fridays, typically cleaning and catch up and home stuff and Saturday, Sunday, I just don't work. Just family time.
Jonas Christensen 12:50
Yeah, good on you. I think that's what a lot of people struggle with these days is when we are working from home, it's a little bit like when you were a student. If you were that kind of student, there's always homework to do. You can always do more in the office is just in the other room. So, it's good to cut the weekends off like that.
Kate Strachnyi 13:07
Yes, it helps when you have kids. They don't really give you a choice.
Jonas Christensen 13:14
Yeah, that's true. I used to get up at five, like you many years ago, I don't do that anymore. But I can recognise the productive time that I got. It was amazing and you can get the most done.
Kate Strachnyi 13:26
Why did you stop?
Jonas Christensen 13:27
Why did I stop? I stopped because I wasn't getting enough sleep, basically and I was doing it because I had a startup on the side and I was working full time and I started running out of mental energy from it, basically. So, I took a break from it and I realised that I also need sleep in my life. And I think your approach sounds a little bit more balanced because I wasn't going to bed at 9:30. So that didn't kind of mesh. But those hours in the morning where you have your own time, there's no no one around, the world is still asleep and it's just you and can be really productive.
Kate Strachnyi 14:00
Definitely helps.
Jonas Christensen 14:02
Now, Kate, dare I say, that you're a bit of a data nerd.
Kate Strachnyi 14:06
Sure. Okay.
Jonas Christensen 14:08
Like me. Nothing wrong in that. And you're a prolific content creator in this field of data, data science, visualisation, etc. And you've actually also written four books. Could you tell us a bit about these books and what made you write them?
Kate Strachnyi 14:25
Yeah, absolutely. So, my first book ''Journey to Data Scientist'', I wrote simply because I was learning about the data science space and I was having similar conversations. You know, like just interviews with data scientist asking them, ''So, how did you get to where you are?'' and I started that because I was full swing into wanting to become a data scientist. And I figured, what better way to learn how to do this than to hear other people's journeys? And early on through my interviews, I realised that this information might be interesting to other people in the world. So, I decided to make this into book. Just by self publishing. It was a pretty simple test to do. The second book was ''The Disruptors'' and this is where I took a similar approach but decided to interview 10 famous or really well known data scientists or data professionals and just simply hear their thoughts, right. So, each chapter in that book is dedicated to an individual sharing their story and their insights and sort of their wisdom off to the next generation. In the book that came after that was the ''Mothers of Data Science'' and, again, similarly sharing stories of mothers who became data scientists and seeing what advice they had to other women in this space and sort of the added factor of dealing with children and I think that was an interesting way to share their stories. Last but not least, the ''Data Literacy for Kids'', so have to cover all the spectrums here. It's a kid's book. It's an online book that I wrote with Jordan Morrow, who's the king of data literacy or the godfather of data literacy. I forget what he calls himself. But essentially, we got together at one conference for, I don't know, like an hour, and we sort of drafted this book together. It's very simple. It's for like six year olds to explain to them what data literacy is. So that was more of a little fun side project. But now I'm actually working on my fifth book called ''ColorWise'', which I actually might end up working with a public publisher on this one, to talk about the importance of colour when it comes to data storytelling.
Jonas Christensen 16:32
Yeah, fantastic. And what I'm reading between the lines here is that you just go and get it done and you're not afraid to have a go at it. And I think that's really a lesson for a lot of people who are out there, thinking about doing something. You're not waiting for the perfect publishing contract or just the right connection. You just get it done and the magic happens around that and that's probably why you've been able to grow such a community in such a short time.
Kate Strachnyi 16:59
Yeah, I think it's important to simply do it. And this brings me to the one thing I think I didn't cover yet for the DATAcated perspective is: I also run conferences. So, I'm planning my fifth conference in March of 2022 and I've recently just started planning this out. But my first ever conference was in October of last year. And I remember, I had a little less than two months to plan it and I was talking to a friend of mine, Scott Taylor, The Data Whisperer. We were just on a zoom call, randomly chatting. And I'm like, ''Scott, you know, I think I should put together a conference'' and he's like, ''Yeah, that's a good idea. Maybe a few years from now''. And I'm like, ''No, no. In two months, I'm gonna do a conference''. I decided to just go forward with it and try it because the best way to learn something is by doing, right, and I figured, what's the worst that can happen? A bunch of people get together and learn. We ended up having over 7000 people register for this random data conference. So to me, it became so real, so quickly. So, then I ended up doing again in February, May, and in October of this year, and now planning my fifth event.
Jonas Christensen 18:05
And what would you say is unique or different about the DATAcated conferences?
Kate Strachnyi 18:09
A couple of things. So one is we are live on LinkedIn, YouTube, Twitter, Facebook and Twitch. So it's 100% live. You won't see this polished, pre-recorded, people dressed in suits and ties and slides up and going on and on. So that's one differentiator. It's also very fast paced. Speakers get about 10 minutes to provide their presentation. So, they really have to simply get to the point and then because it's live, we actually take questions from the live audience. We try to engage them as much as possible and also there are giveaway. So, throughout the live sessions, we also have fun little giveaways and contests and trivia and each event has been different in a unique way. So, we had one focused on the data analytics process, taking the journey from the beginning to the end. We had one that was focused on different industries like healthcare, financial services and food and beverage and how data plays a role in that. So, really trying to spice things up.
Jonas Christensen 19:10
Yeah, I love it. You're innovating in a few years here in this conference space when I think about it because I'm used to the old way of doing corporate conferences, where you go to a hotel and they've rented out an area in there and these stalls with all the vendors from different software companies that you have to meet. It's either prohibitively expensive to attend or you're only attending by invite. Whereas this is for everyone and very fast paced. So, thank you for challenging the status quo and allowing the community to grow. Now, Kate, back to your books there. So, when I look at those books, all of them are created to help others succeed in the field of data science. I want to zoom in though on the topic of Data Science leaders, because this is the Leaders of Analytics podcast. Personally, I think the data science leaders have one of the toughest jobs in the corporate world at the moment, because they basically have to invent a new discipline and forge a path for themselves, rather than walking in the footsteps of anyone before them. So, what do you think are the traits that make successful data science leaders stand out and have an impact?
Kate Strachnyi 20:27
Yeah, I think the leaders that will stand out in the future and those that have stood out in the past are those who understand the problems of the people. So, what I mean here is if you want data analytics to grow as a profession or as a field within our organisation, showing the rest of the population the value that you bring to the table and really taking them on that journey is extremely important. So, having that pulse of being, I guess, a good communicator, understanding what the people care about, what they want, making sure that your data team when they're building products, and they're providing services, making sure that those are actually the services that matter. You'd think this is common sense. But then when you look across organisations, you'll notice data professionals building these great dashboards and building all these assets that get unused. They're just sitting there. Their adoption rate is extremely low because they have not done the right job of understanding what is it that people actually need? It's not the ''Build it and they will come''. It's the ''What should we build and how can we help you do your job?'' or ''What are you actually going to use?''. And I think it's still a journey that we're on as people are understanding the value of data, which I obviously get it. I'm sure you get it. But there are some people who still think that, ''I'm used to doing this for the past 20 years and this is how I'm going to do it''. Right? They don't want to get on this data bandwagon, because they either feel that it's maybe too complicated. That it's not based on the real results. You know, there's various reasons for why adoption rates could be low, but really having a focus on delivering business value is what's going to make leaders stand out.
Jonas Christensen 22:12
So really, you could say that analytics leaders are also in marketing, whether they like it or not. It's internal marketing in the organisation, if nothing else,
Kate Strachnyi 22:22
We're all in marketing. We're all in sales. Yes.
Jonas Christensen 22:25
That's it?
Kate Strachnyi 22:26
Yes.
Jonas Christensen 22:26
So what would be your top marketing tips for someone wanting to really make an impact in their organisation that you see are typically missed?
Kate Strachnyi 22:36
Yeah, I think focusing in on the quick wins, the low hanging fruit, whatever you want to call them, something that you can implement quickly and simply that can have an impact almost immediately. So, then the business can see the value and sort of say, - and I've seen this firsthand, right? I worked for an organisation at some point where they liked data. They had data in databases. They have data in spreadsheets. Lots and lots of spreadsheets. And at one point, I pulled all that data together. I can't really talk about the data specifically but I pulled all the data together in a dashboard and minds were blown. ''I didn't even know you could connect this data plus this data. This has given me something more than what I've seen in the past 30 years''. And I'm like, ''That was a pretty simple drag, drop click thing that I did'' and it really opened up their eyes, because now they're like, ''Well, if that's possible, can we also do this and this and this?'', right? So, show them the art of the possible with a quick win and then if you do that right and the people that you're working with have an understanding of the value, then you're definitely going to go far in terms of pushing data throughout the organisation.
Jonas Christensen 23:43
Yes, it can be deceptively simple, sometimes, what you can actually achieve. And I think maybe that's one of the things we miss as data scientists. We like complexity. We revel in complexity. So, the simple is sometimes overlooked for that reason.
Kate Strachnyi 23:58
Yes, yes. But I also do have to tell you about the flip side of it and this is also something I've witnessed, where if you don't take the steps to validate the data and make sure that it makes common sense and make sure that your dashboard is what your audience is expecting to see, that can go terribly wrong as well. So, even though you might have not have spent too much time on it, you put a dashboard in front of your target audience and they noticed that something that was supposed to be in millions is actually in thousands, right. Like, some kind of mess up because you don't understand actual business domain or the data itself and then your audience loses trust in that dashboard. That's a very, very quick way to lose all trust and data and it's similar to friends and you know, trust and friendships where it can take you years to build up that trust and then one little lie or mess up and they're like, ''Yeah, we don't trust you anymore''. So you definitely have to be very careful in terms of making sure that what you've built is showing, reflecting what actually exists.
Jonas Christensen 25:03
Yeah, one of my mantras is ''Before you can say that you're right, you've got to make sure you're not wrong''. Double check your data. Double check your output. And I think also, there's an element here of lifting your own output up to a high standard, because the example that you just mentioned there with what you thought was very simple of connecting two data sets to someone else seems like wizardry, or magic. And in some cases, I think when we build dashboards, it might seem easy to the data person but for the receiver it's almost like you've designed a new piece of software. And their expectation is that that piece of software is just as well done as your phone app or your little application on your computer or whatever. No glitches and high accuracy.
Kate Strachnyi 25:55
Yeah.
Jonas Christensen 25:56
Now, Kate, if we take our long vision glasses on and look out into the future, sort of 5-10 years out, what do you think are going to be the most important data science skills in that period and why?
Kate Strachnyi 26:12
I think we're slowly moving into a space where a lot of the work that data scientists currently works on is being automated, not sort of taken away by robots, but slowly being replaced and transformed. So, I think, for example, data cleaning and even designing great dashboards and data visualisations, those types of skills are still important now. But looking at the technology, even today I was part of this conference watching sort of what's on the horizon in data visualisation. Slowly, those skills are not going to be needed. Because technology is there to create the dashboards for us. We'll be able to even now ask a question by speaking and say, ''What were my sales in 2014?'' and have your computer give you a chart and it will populate all your sales for 2014. It tell you your sales for before and after and show you a trend line to go along with it, if you'd like. Then you can even ask why and what's been happening. So, I think we're living in a very interesting space. But I think we'll still need data scientists to help connect all those or maybe data engineers, right, to help connect all those data pipelines. Make sure all the data's is speaking to each other properly. But then also data scientists, data analysts who can interpret some of those results and make sure that what we're putting out there in front of the business actually make sense. So vetting, validating some of the models that are sitting behind these tools. And I think there's probably skills that are out there that I'm not even thinking of, because the tools that are going to exist five years from now are not even on our horizon. Like, we're not even thinking about them right now. So, it's such a fun place for us to be. I actually even recently witnessed a demo of a tool where you upload a dataset and then instead of sort of creating a chart or looking at the data, it will give you a video of a person of robotically, you know, AI sort of individual that will tell you the story of the data and create the charts in seconds. So, you don't actually have to touch anything. You just give them data and they'll give you a story, which is so cool, right? But you've got to think about all the individuals who are cramming for their data science boot camps right now, because there's so many of them trying to learn all these skills. I'm sort of an optimist. I always think like, ''There will always be a role''. I even remember when I was - I studied finance in undergrad and I was graduating during the financial crisis and all of my finance major friends, they're like, ''I'm leaving this. I'm going to do accounting'' and I'm like, ''Okay, good, good. You guys go. They'll still need a finance person and that's going to be me'', right. So I was like, I think hold out there and I think there's still going to be demand for data scientists, but the skill sets are just going to vary.
Jonas Christensen 29:13
And sort of reading between the lines of what you're saying, there's a potential that we're going to spend less time doing the work, the technical work and more time educating the stakeholders that are consuming the work. Do you think that's it?
Kate Strachnyi 29:27
Educating, interpreting, I think there's a new role going out there, that's kind of like the business data translator, the business data interpreter where you're working closer with the business, trying to make sure that they understand the data that they're taking actions on. And I think you'll still have those one off requests, where you do have to design very specific dashboards that individuals need to use and doing some research for some research departments with data scientists. So, I think they'll still be roles. But yeah, like I mentioned, it is just going to shift in terms of what you're focused on. A lot less of the data cleaning, data prep, ETL kind of work.
Jonas Christensen 30:04
I'm sure that's music to a lot of people's ears anyway, if we can get rid of that.
Kate Strachnyi 30:09
Probably.
Jonas Christensen 30:11
Now, Kate, what is the most underrated data science skill in your opinion?
Kate Strachnyi 30:18
Underrated data science skill: I guess taking feedback is a big deal for me. I think a lot of times you work with professionals who are very, very smart and you alluded to this earlier when you said they thrive in complexity and I think sometimes taking a step back and remembering why we're here and what we're meant to be doing in terms of, you know, we're here to a lot of times support the business and really sitting there listening to their feedback, making sure you incorporate that into the process. In addition to feedback, I guess I'll also point out to another thing we covered which is simplicity. I was talking to somebody. I forgot his name, but he was telling me that data scientists, specifically those in a PhD programme or grad school, they are taught some of the most complicated algorithms, right? They're graded on knowing some of the most complex things in the world. And once they, let's say, leave the PhD world, they leave the education, the academic departments or whatever, they get into a business and they start working, their focus is on finding the most complex way to do something because this is what they've been rewarded on for, you know, God knows how many years but then again it's really shifting your mindset. So, the skill set here, I guess, will be being flexible and trying to provide a solution that can meet, solve the problem in the simplest way possible.
Jonas Christensen 31:47
Yeah. I think it's the classic saying that to someone with a hammer, every problem looks like a nail, and we can all be guilty of that. I think this skill of looking at yourself and stepping back and going ''Hang on''. A little bit of self awareness there is an underrated human superpower in my opinion.
Kate Strachnyi 31:48
Yeah.
Jonas Christensen 31:48
Now, Kate, what advice would you give to someone starting out their career in data science today?
Kate Strachnyi 32:04
I guess it depends if they're already been educated in the space, if we go under the assumption that this is maybe a recent grad in data science space and they're trying to get their first job, I think as quickly as possible, trying to get an understanding of the full process of data science, right from the data gathering all the way through to cleaning, processing and telling your data stories and working with the business on the output and results of their process and learning early on what it is that you enjoy doing the most. Because life is short to do the things that we don't like doing. So, find out what part of the process excites you the most. Like, this is what I did early on as well. I learned fairly quickly that I did not enjoy programming that much, even though you do kind of feel really proud of yourself when you write a whole bunch of code and it doesn't break and you're like, ''Yeah, I did it''. But I knew I didn't want to do this eight hours a day, right. I knew that I personally loved the part of data science all the way towards the end, when all the data is perfectly structured and we know what we're trying to do and I would get involved in the data visualisation process and making sure the layout is perfect. I can spend eight hours a day formatting, no problem. Now there are people out there to whom this sounds like torture, right? They're like, ''No, I don't even want to think about what colours to choose. I just want to clean the data or write the code or extract data''. So really understanding what it is that you enjoy doing. And then becoming an expert in that specific space whilst understanding the full process, so you know where you fit in and you kind of know what to expect from that earlier stage of the process and what you're striving towards for the later stage of the process. But really becoming an expert in that area is what I'd recommend.
Jonas Christensen 34:04
Nice advice. Now kid, I want to shift a little bit back to you. Because you have some interesting projects in the pipe that we haven't covered yet. And one of them is you've just started minting your own NF Ts. Could you tell us about that and maybe give a bit of a synopsis on what NF T's are for those who don't know and your plans on where to take this?
Kate Strachnyi 34:28
Yeah, absolutely. So NFTs (Non Fungible Tokens). I am just a couple of weeks into learning about this, you know, what they are. But like I said, the best way to learn something is by doing. So, yes, I've minted two NFTs now. They are drawings. One of our business intelligence beaver and then there is a data lake house duck, which was just so much fun to draw on and my kids were involved in the process. But essentially I was inspired by Gary Vee, who Has his V-friends where he has these doodles and I'm like, ''Oh, this looks like fun. Let me go ahead and explore what an NFT is by creating my own artwork''. So I opened an OpenSea account and to somebody who's not in the space, this might all sound like gibberish. But basically, I did this just to learn about what NFT's are and the way I plan to implement them in my business are - I was looking into publishing my book as an NFT. The book on ColorWise. If I don't end up working with the publisher that I'm thinking of, I'll likely end up publishing the book as an NFT, which is essentially a token. So, for those who don't really understand how this would work, for example, I can list the book as a token where, let's say, I limit it to 100 individuals that can actually get a copy of this book. But what they could do later on is essentially resell the book on the market and then I as the original holder of the NFT get to keep 10% of the profits. So, there's like a whole thing that goes behind it. It's all very, very new. But that's one part of how I was planning to use them. Then there are the POAPs, which is a Proof of Attendance Protocol that I plan to incorporate into my future conference. Not sure if it's going to be the very next conference, because I'm still figuring this stuff out. But essentially, it is a token that shows you proof that you've attended an event. Now the world we're slowly moving towards with this Metaverse and all this online presence where it's no longer just social media. You're literally, like, you're gonna have a little avatar on social media that you buy shirts for. And it seems very crazy now. But I do think that that's the future we're going towards. So really trying to get ahead of the curve there. And I think it's something that's going to be interesting, where, I can issue a proof of attendance protocol for everyone who attends the dedicated conference. So, then they sort of get this like certificate of ''Oh, yeah, I've been there''. And yeah, lots of lots of fun. Still exploring, though. So I'm definitely not the person to speak to in terms of explaining most of this stuff, since I'm still learning it.
Jonas Christensen 37:07
Yeah, well, you are learning it and I think you're still a person to speak to because most people are not learning it and this is really, really something that is going to change the world, in my opinion. The web 3.0 movement is so interesting and we could go down a rabbit hole here, I'm sure, of talking about this for hours. But for listeners, Non Fungible Tokens, once you started thinking about it a bit creatively, there is so many applications for it that haven't even been thought out yet and Kate's doing the right thing by simply learning about it and then the ideas will come. So, I encourage anyone to look into that and maybe buy your own CryptoPunk and give it a shirt if you can afford it. So, I'll be following that for sure, Kate , your journey with the NFTs. Now, another thing you've just done is you've completed the New York Marathon. So, congratulations on that.
Kate Strachnyi 37:58
Thank you.
Jonas Christensen 37:59
What made you take on that challenge and what have you learned from that?
Kate Strachnyi 38:04
Yeah, absolutely. So, this was not my first marathon and also not my first New York City Marathon but this was definitely my most interesting marathon. I have partnered with TCS. They've actually sponsored me to run this specific marathon and record my journey of how data plays a role in running. So it was very, very fun. One of the best partnerships I've ever had, because, you know, getting paid to talk about data and running is, you know, just all my favourite things combined, all in one. And I had a personal goal to beat my personal record for running a marathon, which at that time was 5 hours and 7 minutes and 15 seconds. And then I ended up beating my goal. I completed this one in 4 hours, 51 minutes and 52 seconds. So, I basically beat my goal by a lot more than I expected. When interestingly, I've been tracking my training data and really just hoping for the best but so glad that that run is over. It literally took everything I had throughout the almost five hours of running because my pace is generally a lot slower and I tend to do a lot of walk running during marathons, because I just feel bad for myself. I'm like, ''Oh, come on. It's okay. You can walk a little''. But this time, for the first time ever I had an actual pace I was striving for and every time I stopped, I sort of had to do a little five second countdown in my head, where I'm like, ''Okay, you get five seconds to walk and then you're running'' and it was this mental game that I played inside my own head for about five hours and just the level of joy I had when I finished before my goal, it was just indescribable.
Jonas Christensen 39:46
Yeah. Nice. And do you think there's anything from that that you take into your life in other areas?
Kate Strachnyi 39:53
Yes. Pain is temporary and we only live once. When I was running the New York City Marathon, one of my favourite things is the people, the people that are cheering you almost every step of the way. You have huge crowds of people cheering and holding up banners. Sometimes very inspirational, sometimes very funny banners. But a lot of those banners that the people cheering you are holding, say things like ''Pain is temporary, but the memory of doing this forever'' and then lots of funny ones in between. But it really helps you go along your journey when you have the right people cheering at you and sort of wanting you to succeed. And I think that's something I carry in life as well. So, one, Pain is temporary and you're gonna get through this stronger, and then two, making sure that you've got the right individuals that you surround yourself with those who actually care about your success, who are not there to bring you down, but they're there to actually cheer you on and help you achieve what it is you're looking for.
Jonas Christensen 40:54
Now, Kate, we're towards the end, I have two more questions for you. But before we get to those: Is there anything else you would like to say to the audience that we haven't covered?
Kate Strachnyi 41:05
Well, yeah, I think we did cover it. But I do just want to remind folks to go ahead and check out the DATAcated Circle. Circle.datacated.com . I really want to get as many awesome data professionals in that community as possible to really pull off having the biggest, baddest, best data professional community in the world. So, go ahead and check it out and join us there.
Jonas Christensen 41:31
I encourage everyone to do that. It carries the ethos that Kate has built up around her community, which is everyone is giving to each other. So, it's a very nice place to be on the internet. Now, Kate, one of the things we do on Leaders of Analytics is we pay it forward and what that means is I ask you: Who would you like to see as the next guest on Leaders of Analytics and why?
Kate Strachnyi 41:55
All right. I think Ravit Jain from The Ravit Show would be a great guest on the show. For those who don't know Ravit, he basically is one of the best brand ambassadors on LinkedIn. He talks about data literally all day and all night. He's based in India and sometimes I'm like, ''Hey, isn't it like two o'clock in the morning?''. He's like, ''It's okay. It's okay. I can talk to you if you want to talk about data'' and I think his passion really comes through. So, I think he'd be a great guest for the show.
Jonas Christensen 42:28
Great tip. I'll make sure to reach out to him and see if he wants to join the show. And lastly, Kate, where can people find more about you and get a hold of your content?
Kate Strachnyi 42:39
Yeah, I think LinkedIn is probably the main platform. So, looking for me under Kate Strachnyi or under DATAcated you'll find plenty of content. Then you can also look on YouTube, on there DATAcated and obviously the DATAcated Circle if you go to circle.datacated.com
Jonas Christensen 42:58
Wonderful. I really encourage everyone to check out Kate and her content and click follow on all those social media buttons. It won't be a waste of your time, I assure you. Kate Strachnyi, thank you so much for being on Leaders of Analytics. Really appreciate your time and all the best for your future conferences, NFT's, marathon running, book writing and general publishing of everything between heaven and earth when it comes to data.
Kate Strachnyi 43:25
Awesome. Thank you so much for having me on the show. Definitely a pleasure.
