# This Bartender Became a Data Analyst With One Tableau Project

## Метаданные

- **Канал:** Avery Smith | Data Analyst
- **YouTube:** https://www.youtube.com/watch?v=eW9lbvboE4c
- **Дата:** 02.06.2026
- **Длительность:** 31:48
- **Просмотры:** 1,531

## Описание

Brandon was bartending when he found this podcast. Two years later he's a data consultant at one of the best Tableau shops in NY.

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⌚ TIMESTAMPS
00:48 – Bartender to data analyst
02:54 – How he found me
11:39 – Networking event
15:33 – 100 hours on one dashboard
21:15 – Get paid to learn
28:45 – You'll never know it all

🔗 CONNECT WITH BRANDON
🤝 LinkedIn: https://linkedin.com/in/brandon-traditi/

🔗 CONNECT WITH AVERY
🎥 YouTube Channel: https://dcj.app/youtube-averysmith-eW9lbv
🤝 LinkedIn: https://linkedin.com/in/averyjsmith/
📸 Instagram: https://instagram.com/datacareerjumpstart
🎵 TikTok: https://tiktok.com/@verydata
💻 Website: https://dcj.app/datacareerjumpstart-eW9lbv

## Содержание

### [0:48](https://www.youtube.com/watch?v=eW9lbvboE4c&t=48s) Bartender to data analyst

Let's get into it. Brandon, you were able to land your first data job after being a bartender, you're able to land this data consultant role. Tell us a little bit about your transition. What were you doing before bartending and why did you end up doing bartending? — Yeah, absolutely. Um well, first off, all thanks to you. Uh but before bartending, uh so I was actually studying my masters in cybersecurity. Right after that, I got a job with the New York State Department of Education. And with them I was a cybersecurity analyst and a day-to-day involved just kind of waking up, reading some reports, making some calls, helping people update different types of systems. And it came to a point where I was really looking at it and just trying to think, is this what I want to do for the rest of my life? With that being said, I made the bold move to kind of just leave that job, leave that industry. It wasn't where my passion was. Um I had always had background in the hospitality industry. So I decided to just take a jump, go in, go back to bartending, um and try to figure out what that next move was. Funny enough, while bartending and setting up the bar and if anyone is in the hospitality industry, they'll know this is you know, it takes about an hour to kind of set up the set up shop. I would always listen to podcasts. Uh one day lo and behold kind of came through and saw Avery Smith data career jump start and I was like, oh, I wonder what this is. I put it on and I was hooked. I at that time before starting, I want to say in the first couple months of bartending, you had about 105 episodes out and I want to say I watched through almost 85 90 of them. It was just every morning I would plug them in, I would set up everything on autopilot and I would just be listening to all these success stories and all these different how to crack into the data world. And having that background in tech, I was like, you know, I never really knew this was kind of a possibility and then it opened up the floodgates and I said, you know what? Let's give this a go. So, I joined DAA. Uh I started exploring

### [2:54](https://www.youtube.com/watch?v=eW9lbvboE4c&t=174s) How he found me

with different tools that I had never touched before. I've heard of SQL, I you know, knew of R, but I never really got in-depth with them. And it was one day sitting down was I think it's one of the first modules in DAA of the Massachusetts school Tableau dashboard and I thought it was the coolest thing ever. And I thought Tableau was awesome and it from that moment on just got me hooked. So, going with that, finishing um DAA, this was in about the summer of 2024. So, it took me a little bit longer than I think it's scheduled for. It took me about 6 months to kind of get through the course. Um and through that time, I'm sure we'll touch on was my favorite part of it was the capstone, um which was my NFL betting dashboard which I ultimately used as an application for my current role. With that, um the place that I work now I'm a data consultant for the Information Lab and the Information Lab is a little different than a traditional job. At least in the application process that is. Um, so the Information Lab is built off of purely an aptitude-based application process. There is no resume attached to it which was blinking lights there, you know, they don't care. Uh, no cover letters. It was you submit a Tableau dashboard and the team will take a look at it and then if they like it, if they think you put a lot of effort into it, you know, you can see things with a different eye view in the data world, they'll bring you in for an interview. Um, that second interview is a little more of the behavioral interview process. Uh, so that was where I got to present that NFL dashboard. I got to really show the true colors of what I thought about data and how my mind worked with the things that I was interested in. From there, uh, once you get past that round it turns into one which is they give you a data set and it's you have about a week and a half two weeks to build out another dashboard which you would then present to the board at the final interview. And looking back, I remember just being so nervous. I loved Tableau so much and I think that NFL dashboard between your program and that time, I probably spent close to 100 plus hours on easily. Um, late nights just going crazy but I was hooked. Uh, and I think that's what they saw in me and I think they saw that intro of this guy really wants to be here and he really loves it. So, I ended up getting the job. I have now been there. We just hit our one year anniversary with my cohort. So, just over a year now. — Well, congratulations. That's absolutely amazing. Uh, like incredible that you're able to go through this journey and like you did so many things right that I want to highlight and I want to make sure that all of our listeners and watchers can learn from your journey. So, first off, I think there's something to be said about your job, the systems uh cybersecurity role, where you were like, "I kind of hate this. I want to be done with this. " Because I've heard that role is very time-demanding. Like, people get burnt out a lot. People get really bored with it. And they're like, "I don't want to do this the rest of my life. " I'm curious like, why didn't you go from that job to just like trying to land a data analyst job? You kind of went to this intermediate job. And I don't know the answer, but like one thing I've noticed is a lot of people who are pivoting their careers, when they're trying to get out of their current career or their current job, they they, for instance, sign up for my boot camp or they, you know, watch a bunch of videos and they're trying to do their current job, which is probably very demanding, very taxing, and do the data stuff on top of it. And a lot of people get burnt out doing that, cuz they're already burnt out. That's why they want a new career. So, I'm curious kind of like, if that was where you were at and you're like, "Okay, you know what? I'm just going to I I mean, you weren't taking a break, but you're going to go to a job that maybe you actually enjoy more, that maybe requires less demand and stress on your life to ultimately have the space to pivot careers. Is that true or am I kind of just saying that? — Yeah, no, that that's totally true. I think at the time, uh it was more of I didn't know what I wanted to do uh after being a cybersecurity analyst. I just knew that at least bartending, I had flexible time. You know, I at least still had my day and I would work at night, so that daytime I knew I could at least take that and explore. And there were so many other options, honestly. I was looking into um social media marketing, like starting an agency, or I was looking into uh at that time, blockchain was even blowing up, too. I was like, "Oh, should I be a blockchain developer? " And I just And I think that's how the tech side of things started. And then that's how I found your podcast. And then once I started learning and the possibilities of a data career, I was a little more inclined to like this sounds fun cuz it brings in the logical side, the computer side, the tech side, but it also brings in the creative side of things. Which was what I was searching for. Was that creative side of letting that out in data. — Right. So, you decide you want to become a data analyst and you're like, "Oh, I've been listening to this Avery Smith guy uh a lot. " If it took you 105 episodes to finally like pull the trigger and join the accelerator, what was like what did I say on the 105th episode that was so important? — I it's no test to you and honestly anybody who knows me knows I do just so much research before I do anything. Like even the Mac that I'm talking on right now, it took me over 2 and 1/2 months of research before I knew this was the exact model, makeup, everything. So, I want to say in it was just hearing other people's success stories and how and if anybody's listening to this and they're in that type of stuck feeling, it's not until you hear other people who were in your spot that made it out that you actually get like, "Oh, I can do that, too. " Cuz after a while, you're kind of sitting there and you're like, "Well, maybe this isn't for me or you know, nobody that I heard of came from hospitality. " But it was hearing teachers, it was hearing I believe you did have another hospitality worker construction worker. And I was like, "If they can do it, why can't I? " And I think that was finally the moment where I was like, "Let's Let's do this thing and if we're going to do it, we're going to commit. " — That's amazing cuz now we're full circle and you're on the podcast and now you're going to be inspiring people in your shoes. Um let's dive into a little bit more how you did it. So, listen to the podcast, end up joining the accelerator. We follow the SBN method. So, like you said, you might have been more familiar with some skills versus others. Um but you learn the skills and we're building the projects as we go. And I guess for you the second project was really impactful cuz you kind of got hooked on Tableau. Tell me about like what in Tableau made it so interesting to you. — Yeah, so I think what it was it was it's low code, but it's still enough that you can do some really creative things with it. Uh but I think the barrier to entry is it it's a free tool online. Anybody can go download it and play with it today. Um I think it normalized data for me and it was one of those things I just looked more familiar to a drag and drop type feel to it and being able to just go in and not even know what I'm doing, but be able to create something. And just wow, like I just made a dashboard and I don't even know how half of it works, but I did it. And then it kind of scratched that itch of now I really want to know how it works and get in depth with every intricacy of Tableau and that's when things uh below surface level get really interesting. — Some excellent points there that Tableau is free. A lot of people don't realize that um that you can literally download it today and you have the free version of Tableau Public. And it is really easy. Like the barrier to entry is so low and that's why it is the second thing we do inside of the accelerator after Excel cuz most people have touched Excel at some point in their life and they're familiar with it. But the next thing we touch is Tableau because it's so much less intimidating than SQL or Python or R. It's just drag and drop. So I'm glad to hear that like you got in there and you're like oh, I don't really know what I'm doing, but I'm dragging stuff places and it's making charts and I'm oh, I can you can kind of play and learn as you go. And I think also visualization is so important to us as humans cuz we like to see things and we can't really compute numbers without seeing them in a visualization. So it makes sense you were hooked there. So you do the Tableau projects. We have two Tableau projects in the program. Um you do the other projects. Tell me about like your job hunting experience. Were you applying to lots of jobs? Were you getting lots of interviews, were you kind of more focused on building the projects? How was that going? — Yeah, so taking us back to that process

### [11:39](https://www.youtube.com/watch?v=eW9lbvboE4c&t=699s) Networking event

we'll start with I was scrolling through LinkedIn doing my normal posts and kind of trying to outreach and talk, and I saw an ad from The Information Lab. And it was big title said meet and greet New York City. And I was like, oh, well, what's this? And it was, you know, do you want to become a data analyst? And it It's one of those things that you look at and you're like, is this too good to be true? And it said, come meet our team and see what we're all about on X date. And I was like, and I think it was like a following Thursday. And there was a sign-up. So, I immediately went to sign up. I'm close enough to New York City and right across the river. Uh and it was sold out. And I was like, no, like I want to go. I want to know what this is all about. So, I showed up anyways. Um thankfully, I said my name, they're like, I don't see you here, but just go on up, it's fine. And I had shown up, and there's probably about a hundred people. And they We now do this regularly where they basically bring in everybody. You get to see the office, you're in the office, and they put on a presentation of just who The Information Lab is, how they came to be, what they do, kind of the program behind it. Um so, once I saw that, I got out, called my girlfriend, I said, hey, I said, this is where I want to be. This is what I want to do. And I think from that moment, I didn't really look anywhere else, which is different than most probably DA students, but I was eyes focused on The Information Lab. This is where I want to be. These are the people I want to work with. So, from that time, I want to say that was probably around um August-ish, cuz I want to say I was finishing up your program, and then the next application process was that December. So, I saw the applications open. I had finished our capstone, and then even after finishing the capstone, I think I put another extra 200 to 250 hours into it to make sure I can do the best that I can for this application process. But yes, I had which is very not normal, I would say, is just one company. I set on it. — I mean, that's perfect. I think that's a good way to go approach it is like, I'm not going to spray and pray. I'm just going to focus on, you know, this one company. And I think that was a good option for you because one, the accelerator has had a partnership with the Information Lab. Maybe a partnership's the wrong term, but like I I've known the people at the Information Lab. Andy Kriebel, who was one of the founders, no longer associated with it, and I were friends. We've I've had him on my podcast before. The recruiters and some of the people who have worked there, I've talked to them a couple times on LinkedIn. So, it was good because like you not only went to that networking event, but you also kind of had me in knowing, you know, some of the people there um to talk about you. I think I have some messages from people some of the interview process talking about you. I'll have to go in there and look. Um but they also are really focused on Tableau, right? They're one of the you know, one of the things they do is they do Tableau consulting. And since you already hooked on Tableau, it also made sense. And one downside to the Information Lab is, you know, they're New York City basically only. And so, if you don't live in New York City, it's not a good option for you. So, it makes sense. You were a niche down and uh you were you had your eyesight. I think that's a great way versus just the spraying and praying. You're really applying the N part of the SBN method there. And then you applied the P part, right? Because I love the way the Information Lab does their interviews where it's like, "Hey, we all we want is a project from you. Give us your best Tableau project, and that's all we want to see. We don't really care about anything else. " I think it's very cool. It's very merit-based. Um and so, I have some emails with you um from your capstone project. So, um we'll also pop up your capstone project on the screen for anyone who's like watching on YouTube so they can kind of take a look at it. But basically, this is your chance to actually do your first project on your own. So, why don't you tell everyone what your project was and why you chose

### [15:33](https://www.youtube.com/watch?v=eW9lbvboE4c&t=933s) 100 hours on one dashboard

it? — Yeah. So, I did an NFL betting dashboard. And essentially, where this all kind of came to be was I grew up playing football, loved football my whole life. And uh when I moved to New Jersey, they started out the legalization of being able to gamble and bet on sports. And I thought it was so interesting and I already loved watching football and I would put some money here and there on a game. But the one thing I found was I would always lose. And I was like, "Ah, that's all right. I mean, I love football. I think I know football, but I'm just losing. " So, I wanted to see if there were any intricacies or anything that I could find that would give me a slight advantage. And then on top of it, to combine that with Tableau, I was like, "This is This is a home run. This is what I want to do. " And it was really one of those projects that you kind of get into and you get lost into. Cuz you just get so in-depth of like both loves of the NFL and this getting put together. And it was truly to this day, it's still my favorite project I've ever worked on. — I really want to say that it's a good project. And you ended up using this as your capstone for DAA, and then we ended up kind of workshopping it, and you did a lot of work, and I gave you a few notes about and I think The Information Lab even gave you a few notes on like how to make it the dashboard better. Uh and this ultimately was your submission to, you know, work for The Information Lab and ended up landing you an interview and then a second interview and then the job. This one Tableau project pretty much got you your job. Um I would say single-handedly, but also like you were really brave and networked, and you couldn't get in person like you couldn't get a ticket to the event and you still went. So, like a lot of it was credit to you. Um and this project obviously. You did it, so it's not just the project. But, um you said you spent like hundreds of hours on it, like a ton of time on it. I would bet if this was like let's just go back to the project that I gave you inside of the accelerator, you know, one of them is the Massachusetts school education project. You probably didn't spend hours on that project. Why did you spend hours on this project? Like no one wants to spend hours of work that they're not getting paid for. So, what kept you going? — I think the first note is I have never opened that workbook again because I'm scared to see what's behind the scenes. Um I was still totally new to Tableau. I was still like trying to learn all the extra things and I'm sure that a lot of things I did were a little more time-consuming than they had to be. Um but with that being said, I want to say it was trying to be the best that I could and make things work no matter what. I think at one point like a good example is they have DZV now, dynamic zone visibility, but back then I didn't know I it's relatively new. I don't know if they had it when I was building this project cuz there was something called sheet swapping. And it was basically the concept of I had a filter and if you clicked a certain thing, I wanted a sheet to move so it showed something else. I think it was like a time. Like if you clicked like all time, it was like a little another filter that popped up. And I want to say even that took me like four five hours just to figure out. But, I knew I wanted it on the dashboard. I knew I was going to do whatever I could to make it happen. And I think that's kind of that start line of I have this in my head. I have this idea and I don't care how much time it takes me. Like I want to get to that end product and I know that at the end of the day and even if this didn't work out and I didn't get into the Information Lab that it was going to make me a better analyst and a better Tableau user at the end of the day. So, for me it was just nonstop resiliency of just how do I get what's in my head on this computer. — Hearing a lot of not only resiliency, but also like not forced resiliency because um you really liked Tableau, right? Like maybe if it was sequel, you would have been like, "Ah, I kind of don't like this. I'm going to give up. " type of thing. And I also think you really, like you said, you like the NFL, you liked the betting, it was fun. So many people will choose like such boring projects with tools they don't actually really like cuz they think it's the right thing to do. And I think really choosing a project you're passionate about with a tool you're passionate about pairs really well because when you hit those roadblocks that take you 5 hours to figure out, you figure it out and you push through. So, I think you're really smart on choosing the right tool, the right interesting data sets, the right um the right settings, basically, bring forth a really good project. — And I think that's a tribute to you, too. I think that's one of the things that you stress in the capstone is like pick something you love at the end of the day cuz you can pick anything you want. And it's just pick something that you know you want to work with. And like you said, it ends up being fun at the end of the day. — Amazing. So, you present this uh dashboard to them, leads to an interview, leads to a second interview, uh leads to an offer ultimately, um and absolutely amazing of you to do that and to land this job. You've been there a year now. You're now working You're now a data consultant inside of the Information Lab helping consult some of the biggest financial institutions uh in the world. Uh I had you on a billboard in Times Square to celebrating your journey that will pop up on YouTube, as well. Um and I wanted to talk about your current job and a little bit about what you're doing. So, I wanted to know what tools you're mainly using at your job. Um and maybe like a lesson that you've kind of learned uh since being on the job that maybe you didn't expect. — Um so I think to start off it might be

### [21:15](https://www.youtube.com/watch?v=eW9lbvboE4c&t=1275s) Get paid to learn

good for me to explain how the Information Lab is. Um so you don't just come in day one and just become in a consultant. Uh the Information Lab is a it's a 28-month contract where the first four months you are in a classroom setting. You're in a cohort with anywhere from six to eight other people um and you are just learning all different types of tools and learning how to not only become a consultant but become a subject matter expert in the tools that we specialize in. So those first four months are relatively intensive. Um you go through SQL, you go through Tableau, you go through Alteryx, you go through Tableau Prep. Um and with that you go through a little bit of the baseline of like Snowflake, DBT, and then one cool thing with that is that it's not I guess just studying every day but eight weeks of it you'll be on what's called a client project. So we actually do kind of like a seeing is believing where, you know, we have companies where we're like, "Hey, this set of students who are learning and doing their best, you know, how about we bring them in and see what we can do with some data problems that you have currently. " And then, you know, go from there. So you actually get hands-on experience. We worked with some pretty cool companies when I was uh when I was going through training and it gives you that hands-on experience of, "Okay, like I can do this. Like I see real-world data problems and we come together as a cohort and we accomplish all these different things in a week's span. " From there — Sorry, I'm going to interrupt. That is a really good point to bring up that the Information Lab kind of starts as like a paid apprenticeship um where you're getting paid to learn and that's one of the things I try to stress in the podcast and in the boot camp is like you can learn for free, great. You can pay to learn, that's fine, too. But, the best way the best thing to do is get paid to learn. And so, you're earning a data analyst salary, you know, during those whatever it was eight weeks to basically literally get paid to learn. And I love The Information Lab for doing it that way and doing it kind of this like apprenticeship model. Obviously, a lot of companies don't do it that way. But, everyone will have the opportunity at work to get paid to learn things. You're not expected to know everything. So, okay. That's Sorry for the interruption. Uh keep going. So, you're you went through this training program, The Information Lab basically is training you. Keep going. — Yep. Yeah, so I um just to touch on that point, it's funny you say the word apprentice because as of recent, uh within the past year or so since I've been there, we are actually registered with New York State. It's the second in New York State, first in New York City. Uh it's it is an actual apprenticeship program. So, once I hit my required hours, I will be a journeyman in uh data, which is really cool. Um so, it's funny that you say that. So, it is technically a kind of data apprenticeship. Um but yeah, so it's so that training is it's intensive, but it it's fun at the same time. You're learning from some of these smartest people that I've ever encountered. Uh some of the people who are in the Hall of Fame for Tableau. Um you really get a very in-depth knowledge of a lot of different tools that we utilize. Once those four months are up, um you move into four six-month contracts. So, being there just over a year now, I'm in my second contract um with a large financial institution. And you basically get kind of put in with a being a subject matter expert in any of the tools that we use. So, we have some people who are in all Alteryx placements. Some people like myself, I'm mostly Tableau. Um and you know, we even branched off into now we lean into the DBT space. Um Snowflake, whatever it might be. For me, current tech stack and I know something um you would asked was it is almost 90% Tableau and 10% uh Tableau Prep. So, their ETL tool. Uh a very style I'll actually put down a couple notches for a little bit of SQL now as of recent. So, going back into the SQL thing. But, one of the things that you asked was a tip. And I think this is the best tip that I can give and what I wish I could tell myself 2 years ago is that you're never going to know everything. So, just go for it. Um even with the 4 months of training, which equates to whatever it is, 500 plus hours of training, there's still things in Tableau that I am learning on a day-to-day basis and still things that I, you know, can't figure out for some reason and have to go and troubleshoot. And I think a lot of people who are were in the position that I was in have that little bit of a sense of imposter syndrome. And it's, you know, I don't know everything about the tool and it's like you never will. And I wish I can go back and tell myself that and um just, you know, to keep pushing and you are good at what you're doing. Just keep going. — Love love that. Um definitely will never know it all. I don't know it all. Um this is episode what? 216, I think, of the Data Career Podcast. Uh 213, I think. Um and uh I definitely don't know it all. I've talked to, you know, like you said, some Tableau Hall of Famers and people who are experts in everything and I have the chance to learn from so many people and I definitely don't know it all. So, it's really cool to hear that, you know, even after you going through my boot camp, you have going through the apprenticeship of the information school, and you using Tableau on the job every day for what, like a year now, uh you're still learning stuff. So, uh I think that's very impactful, and I hope everyone listening uh really takes that to heart. Do you enjoy being a data analyst? Is it better than your cybersecurity job? — I love it every day. I I'll never forget. It's like and I commute into the city, and you know, it's every morning when I go in, it's you know, you see a lot of people who are in you know, maybe positions that they don't want to, and they look a little down. It's every day I walk into that building with a huge smile on my face of just like, this is everything that I always wanted it to be. This is exactly what I envisioned when I said, you know, I wanted to get my dream job. Um I get to be creative. on the data side of things. I get to be logical, and it's combined. Couldn't I couldn't ask for anything else at this moment. — I mean, think that's a testament to a lot of people who are maybe in a job that they hate right now, that they're worried that the grass isn't greener on the other side. The grass is And in my opinion, obviously everyone's in different circumstances, but if possible, like you're going to live a long time, and you're going to spend, you know, a third of your life working, um if not more. You might as well do something you enjoy. And so, take the steps necessary today to figure out how to get in a situation where you can actually have a smile on your face for that third. That's at least my thought. Um I'd be curious to hear like any other advice you'd have for aspiring data analysts. If someone's listening right now, and you know, is like thinking about becoming data analyst or trying to become a data analyst, what would you what advice would you give them?

### [28:45](https://www.youtube.com/watch?v=eW9lbvboE4c&t=1725s) You'll never know it all

them? — Yeah, I think on the non-technical side of things, um, data is a fun place to be in, but you have to be curious. Um, I think it all starts there. It's asking a lot of questions. Um, that's something that we always emphasize is, you know, there is no stupid question. You should ask as many questions as possible. And understand what you're trying to do with it and what route you want to go with it and just be curious the whole time. In a technical side of things, um, I would lean in more if you want to be a data analyst on to learning a visualization tool. I'm a little biased when it comes to Tableau, uh, but there is Power BI, there is a Sigma. So, there's all different types of tools and I think they are becoming one of the leading front-runners in I think how to break in. Um, at the day even being on the job for a year, you know, I barely touch Excel other than to look at a file. I never do any formulas or anything. Um, very lightly touch SQL, but it's nothing that we don't cover in DAA. Uh, but 90% of my time is at least, you know, learning the visualization tool, learning some type of ETL tool, kind of the background of data, you know, joins, unions, pivoting, things like that, um, to get started and to break into the industry. I think that's the key parts. — And what advice would you give someone who's maybe considering the accelerator? — Do it. Um, it's a great community. Um, I look back and I wish I was a little more vocal in it and a little more on the boards. I would I feel a little more I was behind the scenes and kind of, you know, did it. But it is, at the end of the day, a great community. Um you are awesome. I wouldn't really be where I am today if I didn't start with the IAA. I don't know if I would have ever started, honestly. You know, if I never found your podcast, program, I don't know if this would have ever happened or where I'd I am today. So, I would just say do it. Have fun with it. Do it and enjoy yourself. — Well, I'm glad that you did it and I'm excited to have you come back and be more vocal as an alum. Brandon I talked maybe about doing like a session about Tableau now he's been in the field for a year and becoming better at Tableau than me, for sure. That's for sure. So, Brandon, thank you so much for coming on the podcast. Thank you for sharing your story. We'll have a link to Brandon's LinkedIn down below and you guys can check it out and you know, learn from him and connect with him. Is that okay with you, Brandon? — Yeah, absolutely. — Okay. Awesome. Well, thank you guys and we'll see you in the next episode. — Thank you so much, Avery.

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*Источник: https://ekstraktznaniy.ru/video/52852*