Alex Freberg @ Analyst Builder | Data Science Hangout
We were recently joined by Alex Freberg (@AlexTheAnalyst) Founder at Analyst Builder to chat about teaching and advocating for data analytics. Speaker bio: Alex is the host of YouTube channel “Alex The Analyst”, Founder of Alex Analytics Consulting, and Founder of Analyst Builder. Lover of all things data. Timestamps: 2:41 - Start of Hangout (past intros and welcome) 5:55 - Lessons learned on influencing others in your company 11:03 - Upcoming Shiny/Quarto tutorials preview 14:20 - Pivot into becoming a data science influencer 20:35 - As someone who teaches, how do YOU like to learn 28:50 - Alex's process for creating tutorial videos 40:32 - Advice for starting your own consulting company 54:36 - Working with clients who are just getting started with data literacy 1:00:00 - Most excited about in the year ahead ________________________ ► Subscribe to Our Channel Here: https://bit.ly/2TzgcOu Follow Us Here: Website: https://www.posit.co LinkedIn: https://www.linkedin.com/company/posit-software The Hangout is a gathering place for the whole data science community to chat about data science leadership and questions you're all facing that happens every Thursday at 12 ET. To join future data science hangouts, add to your calendar here: https://pos.it/dsh We'd love to have you join us in the conversation live! Thanks for hanging out with us!
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Transcript#
This transcript was generated automatically and may contain errors.
Hi everybody, welcome back to the Data Science Hangout. I'm Rachel Dempsey. I lead customer marketing at Posit. Posit is the open source data science company building tools for the individual, team, and enterprise. I'm so happy to have you joining us here today.
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I'm so excited to be joined by my co-host today, Alex Freberg, founder of Analyst Builder and host of the YouTube channel Alex the Analyst, and Alex, I'd love to kick things off with having you introduce yourself and share a little bit about Alex the Analyst and Analyst Builder as well, but also something to do for fun too.
Something I do for fun. All right, I can definitely do that. I do things for fun every so often. Depends on the week or month, but my name's Alex Freberg. If you guys haven't seen my YouTube channel, go check it out. I just crossed 750,000 subscribers two weeks ago, which is a big milestone, so I'm heading for the million, which is really exciting. Thank you very much, and I teach everything about data analytics. I've been a data analyst for, let's see, almost eight years now, and I don't have any background in data. Before that, I was in healthcare, and so I worked at hospitals and ERs and rehabilitation centers as kind of like just a caretaker, different positions and that, and so the world of data I was kind of thrust into by accident, and I fell in love with it and became obsessed with it.
It's a great channel. I teach Excel, Python, Pandas, Tableau, Power BI, and I'm sure I'm forgetting some, and so that's what my YouTube channel is, and then I created a data analyst learning platform called Analyst Builder, and that just is kind of my full courses, and we have an integration of coding in there, and so you can code while you learn, which is a really great way to learn. We launched it like last October, and I think we have about 35,000 users, and so it's grown pretty well. I'm really happy with it.
I recently just flew out to Dallas. My father-in-law, he's retired, so now he just does music. He's a musician. He just does gigs, and so I play a lot of guitar just when I have time in between stuff, and so I flew out there, and we did a few gigs at some hotels and stuff like that, and I have videos of it, and I don't know if I'm going to share it on my Instagram or not, but I might because people, I play guitar on my live streams on my YouTube channel, and people like it, but it's a bit different when you're actually really trying.
Influencing others in your company
Some of us here might not necessarily be an influencer or planning to be a data content influencer, but I think a lot of us do actually want to influence people in our own organizations, and I know there's a lot of people here who maybe started an internal community within their companies to help teach others how to use Python or R, and I was just wondering, I would love to learn from you some tips that you would like to share with all of us.
Yeah, it's funny. I've actually done exactly that, which is I've introduced new tools to my team just when I was like a beginner. I was like, my second year in, I found Python, and I was like, what is this? What is this programming? This is amazing, and I fell in love with Python, and I was like, I got to figure out how I can use this in my job because it's so good.
I started finding about automation, and I, again, was very new to this, and so I didn't know what it was, and so I started practicing it just on my personal computer, and I was like, I could do something like this for this project at work, so I went to my boss, and I pitched it to him like, hey, Sabrina. I was like, we do this manual Excel stuff all the time, and it's this and this, and it's always the same. It's very manual. It takes too much time. I was like, how would you feel if I automated that, and she's like, I'm in, so then I built it. I built the whole thing. It took me like, you know, an hour here, an hour there for maybe about a week it took, and it worked, and I showed it to her. I was like, it does all this work automatically through Python, and then, you know, here's the output, and she was like blown away.
And so I kind of got to introduce it by a use case, which was really neat, and it saved our team a lot of time, and she ended up having me show everyone else on the team how to do it, because everyone did it, and so that was kind of how I introduced Python to my team who did not use Python at all. We weren't a Python team, and so I've done that many times over my career. I've introduced new tools like we switched over from like on-prem to the cloud, or we switched from Tableau to Power BI, and I'm like, hey, listen, you know, we got a good thing here, but let's look at this other tool, and so my tip is always just go for it.
I've worked with a lot of people like not in the workplace, but just talking to people like this, where I'll say, hey, you know, there's a real use for this skill or this tool. I was like, you should just go and tell your boss and see what they say. If they say no, it's a terrible idea. Well, he's probably a bad boss. I was like, but if you have a good boss who's open to it, they'll at least let you try, and that's, you know, what you're hoping for, and so I think, you know, there are some bad managers out there, but if you have a good manager, just like a person, like a normal good human being, they'll give it a chance, and they'll let you, you know, test it out or try it out as long as you're not like, you know, destroying something or, you know, doing something wrong. They're going to give you a chance, and so I always just say go for it, you know, just see if they'd be willing to let you try.
My team had a lot of visibility. We were on data collection, and so we had our hand a lot of different pots with a lot of different teams, and so my boss, Sabrina, was just really had a, she was super outgoing, was not technical at all. She wasn't a technical manager. She was a people manager, and so when I started showing her this, she was like, we got to show everyone else, and so she's friends with all the other bosses and like managers and VP and everything, and so she was like, hey guys, so we jumped, we did daily stand-ups, and so like one of the daily stand-ups, she was like, hey guys, Alex built this thing. He's going to demo it, and I want you guys to use it if you think it's applicable, and so I just demoed it really quick, and people were like, oh my gosh, why haven't we been doing this for the past four years or five years.
I think having good connections to promote it is really important. I started to find that in my career as I started kind of climbing the corporate ladder that making connections with people became really important to get my job done, and even more so as I had more visibility in bigger projects that cost more money. You had to have connections to get things done, and so those connections are really, really important.
Upcoming Shiny and Quarto tutorials
I love your tutorials very much, and a request for some Shiny content.
Funny you mentioned that. I'm actually working with Curtis and Joe, and I'm sure I'll work with others along the way, but I'm making a whole Shiny series, which is really Shiny Express to be specific, but I'm also going to be making a Quarto, some Quarto videos as well. I love it. I've been diving into them like really a ton the past couple days, but I've known about it before that, but now that I'm like really diving into, I'm like this is really great. I'm excited to make these, and so yeah, I'll have a whole series on that probably next month. They'll probably be out.
What's neat about things like Shiny and Quarto is one, you get to build a user interface, and in a lot of data analysts work, that stuff is not anything you do. You don't get a touch on that. You mostly work with something like Tableau, or maybe, you know, there's a hundred different tools for data visualization, but most of them have UIs that you just drag and drop, which is not a bad thing at all, but then if you want to build some type of web-based application, there are ones that have embeddings, but they're not, in my opinion, not a lot of them are very good, and so you typically have to do some customization.
I'm familiar with Streamlet just because of other data science people, and so I had started with Streamlet, and Streamlet's really good, and so I like trying new tools, and I was like I really want to try Shiny. This seems like a great tool, and as I'm getting into it, there's just, especially Shiny Express is very user-friendly, which again, when I make tutorials, I can't really, I don't try to go crazy in depth because I know my audience may not be, they may not know CSS or HTML or, you know, different web-based building tools or ways to make things, and so I've really been enjoying Shiny Express because it's really simple to say, hey, I want a slider here, I want this visualization here, render it here, it makes it pretty easy, but you also feel like a boss because you're just like, I am stinking coding right now, and I look awesome, and so when you get all the pieces to connect, like, it's just a, you know, it's a great feeling as a non-web developer to be able to do that stuff because I'm just like, I'm just a data analyst who uses Python, but, you know, because I like Python so much, Shiny really, really hits home with me.
Pivot into becoming a data science influencer
Hey, Alex, I'm just really curious about kind of your journey from, from there to here. There had to be some point where you said, oh, I really like this educational, this technical, whatever, and you must have had a bunch of new stuff to learn in, like, how do I make a tutorial? How does video work? I'm just curious about, like, how did you make that, that pivot for yourself, and what's that, what's that process been like?
Yeah, that's a great, that's a great question. I, I had never made, actually, that's not true, I made one YouTube video. Oh, well, actually, I'm going way too far back. I did have a YouTube channel before Alex the Analyst. I totally forgot about this. It was a watch review channel, and I used my iPhone 6s, and I, it's not this one, but I would just hold it up while I was recording, and I would talk about a watch, or I'd set it on a pile of books, and I would do that, and I liked reviewing the watches, but I didn't have enough money at the time to buy enough watches to keep that channel alive, and I realized that pretty early on. I was like, wait a second, I forgot I'm broke. This isn't good. So I was like, you know, so I stopped that channel, a couple months later, I was like, you know, I really liked making videos, and I really had been getting into Python, so let me see if I, how I could make, like, some Python videos.
The process really was a ton of research on YouTube about how to screen record on, like, a budget, how to edit on a budget, and I, when I was breaking into data analytics, I took a ton of courses, mostly on Udemy and Coursera, and so I had a pretty good idea of how people made the videos, or, you know, how to structure them, and so I just tried to make them as useful as I possibly could, and some of my earlier videos were not as good as I had hoped, but I, you know, it's all iterative, you know, as I go on, I get better audio, I get better, you know, screen capture and all those things.
It is funny because my dad's a teacher of 30 years, and he's actually the principal of my kids now at his school, and I never thought I'd go into education or teaching in any way, but now we kind of laugh about it because I, you know, I came back to it in the end.
Now, you know, I quit my job. I was a manager of data analytics for a Fortune 10 company back, back in, at the end of 2022. I quit my job to do consulting and then my YouTube stuff full-time, and so I made that decision because, one, my full-time job, I was not enjoying that much. The pay was great, but it just was not as technical as I was hoping. It was more people managing, and I learned after I took that role that I really need to be building something to keep myself engaged. My wife is convinced I have ADHD, and she's, she diagnoses those types of things, so she would know, so I'm convinced that all these things kind of played into the fact that I have a really good attention for detail and, you know, kind of outlining everything, and then I just need, I have this desire to keep building and keep learning.
Most of the videos on my YouTube channel, maybe half of the tutorials are things that I learned, you know, within the past year, and so it's not like I'm a mega expert in all of it. When I recorded it, like things in Python, as I was learning, I would be like, well, this is super cool. I need to make a video on this. Like, I learned this last week, and now I'm teaching others how to do it, and so it was very go with the flow and very just, I took it all as a learning process, and I'm still learning today.
And so it was very go with the flow and very just, I took it all as a learning process, and I'm still learning today.
How Alex likes to learn
The first one is, I mostly, when I was first starting out, learned through like Udemy and YouTube. I was very, very, very broke when I started becoming a data analyst. I had $500 maybe to my name, and I'd just gotten married to my wife. She took a big risk on me. And I was taking Udemy courses in YouTube, and that's how I get most of my content when I was first starting. As I progressed, maybe past my first year as a data analyst, maybe my second, I did most of my learning hands-on in my job.
And what was really great about my progression in my career was that I started only with Excel and SQL. That's all we did. But the SQL that we did in that job was way beyond what I should have been doing. So I was doing a lot of really complex store procedures, and it was just trial by fire. And my boss was really hands-on and had a good mentor. So I learned SQL super well, specifically Microsoft SQL Server. Second year, we then started using Tableau, and I got some good hands-on experience with Tableau. My next job, we learned Power BI and Azure. And so I'm picking up these skills as I'm going.
I personally believe that I was a bit overestimating my abilities because I would volunteer for big projects. I'm like, I can do that. And I had no idea what I was doing. But then I learned, I forced myself to really dig into the really technical details of a skill. And I had to learn it because I told them I could do it.
So that's how I personally learned. I don't think I've ever read a data book before, nor do I recommend them. Not that I don't recommend, nor have I ever talked about recommending them because I just don't read that much. I'm like a very, very, very visual learner.
Right, right, right. Yeah. No, that makes perfect sense. I used to have to intentionally do it. Now I just subconsciously do it because that's what I do. I make YouTube videos. But when I was first starting out, when I was learning and started making videos, what I ended up doing is I went from beginner all the way to as advanced as I felt I could get. And then I would go back and be like, okay, this beginning stuff was really tough because I didn't understand this. So I need to make these connections. So I would write out almost like a diagram of here's how I got to that end project or that end result. And let me write out like the steps that I need to in order to teach it so that they understand that this is connected to this, even though they don't really know that yet, in a really beginner level friendly way that I wish the person who I was learning from had done it.
So I kind of like when I'm watching like YouTube videos, now I do it really subconscious or if I'm, you know, learning a new skill, I do it subconsciously, but I kind of critique. I'm like, man, it would have been great if they had taught that before. And then I just remember it for when I'm going to teach it. And then I still do outlines for all my videos, but they're not as in-depth as they used to be because now I just remember it.
My first data job was at a nonprofit. I was a data collection specialist and analyst. The lady who had been there for 20 years decided to retire. And so I'm like, you know, I'm like, I could I could do that. Like, let me apply. And so I got the job. It's only in Excel. We just collected data for grants in Excel. We would report it. That's all we did. So we decided to migrate to Salesforce and use their like ERM software.
So we bring in this consultant to help us migrate our Excel data into the cloud and set up some automations or not the cloud, but Salesforce set up some automations for data collection. And he's like, oh, you're the data guy. I was like, yeah. So I was working with him and it'd been a couple of weeks. And eventually he got he asked me it was like late in the afternoon. He asked me, he's like, he's like, so you're the data guy. You know, we need to, you know, bring your data from SQL into the CRM. And I'm like, I was like, what are you talking about? I was like, you mean Excel? He's like, no, SQL. I was like, what is SQL? What are you talking about? I didn't say like that, but I was like, oh, what is what is the SQL you speak of. And he's like, he's like, you don't know what SQL is. I'm like, no.
And he's like, oh, well, it's this, you know, SQL is like a database and you store the data in it and then you can query the data. And I was like blown away. He's like, you guys have a SQL database. Someone showed it to me. I, someone else besides me had access to the SQL database I had no idea about. So that night I went home and I looked up what SQL was and I was like, wait a second, I got to learn this.
And so that night I bought a Udemy course. It was for SQL server. And that like over the next two or three weeks, I just obsessed every single night for three or four hours. I was going home and learning SQL and then going to work and being like, all right, give me access to everything. I need everything. And I like became really semi-obsessive. It was like anytime I could get my hands on time to learn, even at work, like if I had a second, I would start learning more. And so that was the first time I had heard what SQL was. And it turned out to be one of the most important skills of my career. So I owe a lot to that guy. I don't remember his name, but that consultant that came in, I owe a lot to him because he definitely helped me out a lot.
Making YouTube videos: process and time
Not anymore, but earlier on in my career when I had a full-time job, I had little babies. My kids are a little bit older now, so it's a lot easier. But when I used to only have two hours, Wednesday nights, and that's it, to record, edit, publish, create the thumbnail. That's all the time I had. Like I didn't have any other time in my life to do it. And so I used to do it every single week at that exact time.
Now I work for myself, so I run my consulting company and then I have Analyst Builder and I have my YouTube stuff. So now I kind of make my own schedule. But here's kind of typically how it goes. The videos that you see on my YouTube channel are usually made like a month or two before. So right now I have four videos that are scheduled for the next four Tuesdays. So I won't be working on any videos for probably another month, because it's one per week, so four videos is one month's worth. Then what I do is I work at nights now, so like from 8 p.m. to 11 p.m. one night, I start, all right, let's think of my next videos. I do all the outlines, I prepare everything, and then the next day, for maybe a day to three days, depending on how many videos I'm recording, I only record just for like seven hours straight. And so then I do about seven hours of recording and I can usually get maybe five to ten videos done, which is about a month to two and a half months of content.
Tips for short-form content and handling feedback
So I've met a lot of people who kind of wanted to get into data, but they really struggle with learning coding. I started making some TikToks of TidyTuesday datasets. What I'm struggling with is like, how do you condense a lot of technical stuff, because who's going to watch an hour-long thing of me walking through TidyTuesday, into like 60 seconds and make it really engaging, not too technical. So I don't know if you have any experience with shorter content where you just get people excited about kind of diving in deeper.
Yeah, that's a great question. I actually am on the TikToks. I'm with the young crowd. I'm hip, I'm jive. I don't post on it that much, if I'm being honest. I have maybe like 20 videos, but I post on Instagram. The short content is really tough for me, if I'm being honest. It's very, very tough. I'm extremely long-winded. I like to get super technical. And if you watch some of my more advanced videos, what I'll do is I'll say, here's how you do it, but here's how it's actually implemented. And then I dive even more into it.
So what I traditionally try to do with most of my videos is I try to dive right into it. I don't talk, there's some YouTubers, and that's their thing, is they like to talk about, you know, here's what it is, here's how you use it, here's, before showing anything, they're just talking. Me, I just like to say, hey, welcome to my video, here's what we're talking about today, let's jump into it. And then I'm like, here's how we're going to implement it. I, for short, really short content, I found that a lot of people who are successful with the short content is they show the final product first. They say, here's what we're building, let's see how to build it. And then they'll cut right to the beginning. They say, let's take this, we transform it, we build this, we do this, and here's your final product.
And then, you know, it's all about iteration. You're not going to get anything perfect right away. I learn a lot from comments on my videos, people who are like, I like this, I don't like this, and stuff like that. And so feedback from your audience is also really good.
This actually wasn't an issue until I hit maybe like 600,000 subscribers or so. And before that, everyone, all I ever saw, like every video that I have is like 99.9% like rate. As you start getting bigger, I have found that people start having higher expectations. They're like, you have 750,000, how do I, why don't you have a series on Shiny yet? No, no, not, I'm not knocking the person who asked that, I was just joking. But they'll ask me things, they're like, dude, why don't you have a series on R yet? Like, we need an R series. And they can start getting mad at me.
And I'm like, like, hey man, I'm just one guy who makes cool videos on YouTube. Like, I can't do everything today. I've made like 300 videos now that have spanned four and a half years almost. And I was like, I'll get to R. I'll get to R, I promise. But there's other R videos.
I found as I've gotten more, as I've gotten larger, a wider range of people all have expectations and you can't please everybody. And so I don't even try. I don't really tiptoe around anything. I just block almost all the negative stuff out. If I see some genuine criticism, that's like, hey, Alex, in your video, the audio wasn't very good. And I'm like, oh, you're right. That's really true. Or hey, Alex, when you were teaching this, you didn't talk about foreign keys versus primary keys. And I'm like, oh, you know what? Hey, you're right. I should have added that. I'll add that in my next video. And so there's some genuine criticism. And then there's like what I deem as haters. And I just block out the haters genuinely. And I do have some, which is really neat. I mean, I've gotten big enough to have haters now, which never never happened for the first four years. And so I'm just honored that I have a channel worth hating.
Getting comfortable learning out loud
No, in the beginning, I stuck with the tried and true. When I first started making videos, it was like how to help people become data analysts. There weren't many data YouTubers back in the day. Now they're a dime a dozen. There's thousands of them out there. But there was maybe like 20 of us, 30 of us that were doing it, maybe more. But there were there were like companies doing it. Whereas like individual creators like myself, there weren't many that had made actual good content.
I remember where I was going now is I started with SQL because I knew SQL really well. And so I started with things. I was like, I really know this skill enough to where I feel like it's hard for me to mess it up. I'm not going to forget what the where statement does or the where clause does in SQL, like the, you know, those details. Now, as I started venturing into things like Python, I was learning a lot of Python and teaching Python on my YouTube channel as I was learning it. Like as I was learning web scraping, I was teaching web scraping probably the next two weeks. More of it was just from like a holy crap, like this is amazing. I was like, I got to show people this.
You know, I wonder if people even know about like web scraping because I was so new to it. So I got like super giddy about it. Like I got really excited. I was like, man, I want to show people this. And so I would build something and then I would show them how to build it. And I didn't really worry too much about failing because in my videos, I like to show my failures. I think people have really liked that. I didn't intentionally do that at the beginning. I just left it in there because I'm like, yeah, it's part of the process. But now that I know how much people appreciate it, I leave it in there on purpose. But if I'm doing something and I get an error, I'm like, oh, let's see how to debug this because they're going to encounter those exact same bugs and errors and, you know, whatever. And so I don't strive for perfection. I just strive for something that is helpful. And I think a lot of people strive to make it as clean and neat and perfect as possible. And I don't usually try or never have tried to do that. I just try to make it useful for someone who's learning it for the first time.
And so I don't strive for perfection. I just strive for something that is helpful.
Becoming a consultant and entrepreneur
I kind of dream of being a consultant sometimes, more so than like... I mean, I love education and, you know, I guess like the passion and showing other people how to do stuff. But like, I really do think being a consultant one day, like my own consultant would be amazing. But I have this fear of not being able to replace my income. And so I'm just curious, like, you know, if you had a plan or if you gave yourself some kind of runway to get your, you know, entrepreneurial business growing.
Yeah. Yeah. So one thing I'll say before I dive into my own stuff is I have a good friend and you may know him. He's a YouTuber as well. His name is Seattle Data Guy. His channel is called Seattle Data Guy. He does data engineering. And I've met him in person many times. You know, just an amazing guy. He has a whole... He talks a lot on his YouTube channel, as well as he has a whole course on how to start a data consulting company, which him and I both do. And so we jump on calls like once a month, every so often, just to catch up about business and YouTube. And, you know, we're friends now. And so I would really recommend checking out his channel because it's very, very good.
Way back when, when I was actually about to get promoted to a manager of analytics role, I had a job offer from KPMG, which is a big consulting company. And my father-in-law worked for KPMG for like 20 years. He was a big time guy over there, and he did awesome. And because of that, I was like, well, I think I could get into consulting. I think I'd be pretty good at it. So I started applying without telling him, because I didn't want any nepotism or anything like that, because he probably could have pulled some strings, but that wasn't what I wanted to do. So I got a job offer, and then I went to him afterwards and talked to him about it, like, hey, I got this job offer from KPMG. What do you think? And he's like, don't do it. He's like, you have a family, you have kids, you're a family man. He's like, you would hate it.
So I took the manager role, and on the side, I started... I had all... As my YouTube channel had gotten bigger, I had started getting messages from people saying, hey, you know, we saw you made this video on whatever, and we're trying to integrate Power BI into our tech stack, but we're having issues with it. Well, I... That's literally what I did, is I would help people get Power BI up and running in my company for part of my work. And so I was like, oh, yeah, okay, I can do that. And they're like, we'll pay you. I was like, whoa, hold up. You're going to pay me for this? Didn't even... It hadn't even crossed my mind. So I started taking on these little gigs here and there. And as my YouTube channel got bigger, they kept... More messages started coming in, and I was like, wait a second. I was like, you know, this is making good money.
It's pretty consistent. And I'm almost replacing my manager salary with my other stuff, and I'm only doing that on the weekends. So let me see if... Maybe I should ramp that up a little bit. So I started ramping it up, but then I was like, I got to... I don't... My full-time job is getting in my way from taking on more clients, which would make me more money. So I was like, I'm just going to quit and do consulting. And so that's what I did back in December of 2022.
And so I made a lot of mistakes along the way. Just every mistake in the book, under pricing, over pricing, taking on too many clients, taking on too few clients, taking on work I didn't fully know, taking on work I knew too well, and it took me like an hour to do that I charged too much for. I made every mistake. And so looking back, now I have gotten a really good groove, really good pricing structure and all these different things.
And if I was just starting out today, there's a lot of different paths you can take. I personally think that if you are wanting to dive into it right away, trying to grow like a following like I did, or even a following at all, is very, very tough. I think that's more time consuming than just diving into it. And so a lot of people will be like, well, you have to have like a brand and you have to have like an online, you know, face to it. I don't think that's fully true. I think it's good to have like something on your LinkedIn profile that says you work for your own company or something, but you don't have to do that.
But what you can do is you can start small. If you are already working in the data world, you probably know data people or connections. And so, you know, reaching out to those people and say, hey, I'm starting my own stuff. You know, I'm working on these three specific things that I'm an expert at. If you need any consulting, let me know. You can make a post about it, whatever. But try to get that one client. Because I found that as I started getting clients, I just stopped having to get new clients after a while because the clients that I've had just keep coming back. So one of my first clients I ever had was this startup company who wanted me to come in and help them migrate to Azure. Well, that one client I've been working with them for like two years.
And so that once you start getting them, usually it's good. Getting them and acquiring them is difficult. So there's a lot of cold outreach. There can be a lot of emailing. You could even go on things like Upwork or Fiverr and stuff like that to bid for jobs and things like that. But, you know, if you get some of these solid jobs and solid freelancing and consulting stuff, it's all snowball. So then you, you know, do your best to leave a really good impression and bring them back as a repeat client. Once you get three or four, it's mostly word of mouth. You say, you know, hey, you know, if you guys find me another client, I'll give you a 20% discount on all future work or something like that.
And, you know, it's it's all a snowball effect. The other piece to it is, is you can't really just quit your job and do that. I don't recommend it. And I've had people ask me if they should do it. And I was like, don't do that. That's a terrible plan.
Consulting work and AI
No, I haven't trained anybody in any LLM stuff. I do a lot of trainings actually. I've been doing a lot of Power BI trainings. Yeah, I think that might be the only trainings that I've been doing recently is Power BI. A lot of people or a lot of companies or smaller startups and whatnot are wanting to use Power BI but they just aren't good at it. And so they're like, hey, why don't you come in and do like a one-on-one training? So I do. My consulting work is also really eclectic. I do just about anything.
I actually consult quite a bit with companies on how to integrate AI. So I've just been doing a lot of AI stuff. And what's funny is I'll get in there and they're like, how can we integrate AI? And I'm like, you guys don't need AI. I was like, this is a bad idea. And in fact, I think it's going to really slow you down. And here's why. Then I explain it to them and they 100% agree. And so some companies have use cases for AI where it makes sense and there are certain tools that they can integrate. But a lot of companies, I've been consulting with a lot of AI stuff.
I also do a lot of building. So I've been working with two startups on migrating to Azure, which is literally exactly what I did in my manager role. I came in and did something in a year, which they've been trying to get done for six years. They had been fighting and bickering and arguing about how to implement Azure and how to transfer into the cloud. I came in and I was like, guys, we're doing it. Let's get this budget approved. Let's get everyone on board. I worked my butt off to get that approved. And so then we started building it, hired engineers and developers, and it was awesome. And then once we got it migrated over, I quit. And so I don't know what happened after that.
I get paid. It's part of my consulting is just talking to people. So they'll, hey, come into our company and give a talk on how analytics can be helpful in a company. I'm like, heck, yeah, why not? And so I'm very, very eclectic. I build things. I consult on things. I do AI, the cloud, trainings, videos. I've done some internal videos for companies, which is really neat, because somewhere, someone is watching. They're like, that's Alex, the analyst. Why is he doing our internal training?
Data storytelling with non-technical audiences
For your data storytelling efforts, since you've been involved with many different clients, you've been in many different industries, data literacy is half the battle, right? I mean, understanding the data, but how much of it is education-based? I mean, are you teaching more before you get to the actual insights, or how does it all work when you're dealing with clients that are just first starting off, or maybe they're just getting their feet wet?
That's a good question. There's very, very differing approaches to this. And so I'm going to tell you my approach, and it has been very successful. What I do is I usually don't talk about the data that much. And I started figuring this out personally, because I used to dive into the data. I was like, well, here's how we got the data. Here's how we cleaned it. I just go... I'm technical. I'm a very technical person. And so I like to dive really deep and explain everything and how everything connects and what we did. From my experience, nobody cares about that.
When you're presenting to, let's just say a manager, but when I was presenting to the CFO of my Fortune 10 company, who's four ranks above me, I found, because I had to present to him a lot, I found that he does not care about the data. What he cares about is what can we get out of the data. So I usually just start with, like the storytelling process, I start with, here's why we're here, and here's what we found, and do you have any questions? Nine times out of 10, they don't even care about the data. Even though you have to have the data and use the data to get to the conclusions and say, here's my recommendation, here's what we found, and there you go.
Then they're going to come back with, well, how'd you get that? Sometimes. And you say, well, here's how we got to this process, and you show them the slides. What I used to do, and I think this was always really funny, is I'd have two presentations ready. One was the presentation that was the layman terms, dumb it down, here's the nuts and bolts. Then I had the second presentation that was kind of the actual, what I would consider the data storytelling. Here's what the data is telling us, here's what we found with this population, this A-B testing, whatever, and here's the conclusion. I always actually usually had two presentations that I would give. During one presentation, they just didn't know it, but sometimes I would only get to that first presentation, they didn't care about anything else.
They were just like, okay, that's perfect, how can we implement this? I would say, here's how we implement it, boom, boom, boom, done. Depends on what level, who you're talking to, but the higher you go, usually the less they care about the data storytelling and more about the final results.
I think that when they aren't technical, use as little technical jargon as you possibly can. Just talk to them like you're talking to your niece or your nephew or your son or something, like, hey, we tried to validate it this way. We tried to see if it was good this way. It didn't work, but we're going to go back and we're going to do this. Again, it's very, very dependent on who you're talking to or what you're doing, but I would just keep it as simple as humanly possible without even mentioning technical words at all. Just like natural human conversation level terms.
What's most exciting in the year ahead
This is going to sound really weird, but from my perspective, it doesn't sound weird because it just doesn't. I'm very excited about the fact that as we, and this is going to be on AI because I've just been really into it, as we get more into AI, we start seeing its limitations, and I think that's a very good thing. And the more I talk to companies and consult with them, and the more I talk to, and going into the end of this year, I have more coming up, I get very excited about actually using AI in a useful way, instead of using general AI to try to use for a specific task that's not good at, and then getting bad results. So I'm really excited about the educational piece of companies and people learning more about the limitations and the good parts of AI. That's what I'm excited about.
I get very excited about actually using AI in a useful way, instead of using general AI to try to use for a specific task that's not good at, and then getting bad results.
