 Hello, I'm your host Alex Friedberg and this is the Alex the Analyst Show. Thank you so much for joining me today. We are going to be talking about automation and if it's going to kill the data analyst profession. Now, I have a lot of things or a lot of different topics I want to talk about, so I'm going to quickly go through them all because it's going to kind of be all over the place today. But of course, I'm going to be talking about the automation piece of it first. So we'll talk about that. I'm also going to be going into whether or not I think that AI or artificial intelligence will destroy the world. I think it's on the same vein. So I wanted to touch on that because I think, well, the end of the world is somewhat important. We will also be doing Question of the Day. I have a Patreon poll that I took a while ago, but I haven't done an ATA show in a while. So I will be doing that. They voted on what they wanted me to do at the end and I will be sharing my favorite thing that I like to cook and how I like to cook it. So stay tuned for that. And then at the very end, of course, the vegetable of the week. So we have a lot, a lot to look forward to, to be honest, in this episode. So let's get into it because I want to make sure that I have enough time for everything that I want to talk about. I have lots of notes, so I'm going to be looking over here quite a bit. But the first thing I want to talk about is just what is, what do they mean by automation, right? Automation can mean a lot of things. Are we going to be completely replaced by machines and robots? And they're going to be clicking away at the keyboards and doing our job. No, that's not really what they mean. They more mean, they more likely mean the actual work that we're doing is created in a way or structured in a way that can now be automated through machine learning or artificial intelligence so that we no longer really have to do it. It is all automatically processed, all automatically done. And the manager above us now just has to pay for this automated process each month or each year. And it completely would replace our job. And so that kind of to me is what they mean by automation. It's more replacing the functions of what we do, not necessarily replacing us by, you know, I guess robots. I didn't think anybody else thought that. But so here's my overall thoughts. I think that on some level, on a small level, that there will be parts of data analysis that absolutely can be automated. We're already seeing things like that where, you know, visualizations can be automated to an extent, creating reports can be automated to an extent or just created much more easily. So we're already seeing some, I guess, some foreshadowing into the future that this is definitely possible, is definitely possible that certain parts of this profession can be automated in a way. Now, does that mean that data analysts are going to go away? In my opinion, no, I don't think that data analysis or data analysts are going to go extinct. I think that they will always have a place in the industry. And let me kind of comment on why I think that automation allows things to go faster and better. But it doesn't do the logical reasoning like we do. I guess I'm going to skip ahead to my next one. It doesn't. Artificial intelligence or automation is not going to provide context and logical deductions and reasons based off of the data. Right. And they don't understand the context to what the data truly means. Okay. So so they're not directly talking with. So in me, my profession, I talk with hospitals and doctors. Sorry, Max is crawling on the ground. He's making a lot of noise. I don't know why he's doing that. I'm going to get him up here because you guys haven't seen him in a while, but he's gotten huge. Just wait, I'm going to get him up here. He's coming. He's getting old. He's he's like nine months old now and it's late. So yeah, buddy. So if you go back to the very first episode, I showed him when he was just a tiny little pup. And he was like the size of like a water bottle, a little bit larger than a water bottle. He has now grown. He's a much larger puppy. He's so cute. And he's now like 25 pounds. So he's a big puppy. Oh, I love you, Max. You're a good boy. All right. He's going to go lay back down in his dog bed to pick back up where we left off because I just had to. I just had to show you guys him. If you guys haven't watched any of these episodes before, and this is the very first one, you may think that this is really odd. These are normally how my episodes go. They're kind of all over the place. But this is just this is my place to just talk about subjects that I think are interesting, but they don't know context. So in my profession, I talk with hospitals and doctors and other departments relating to health care data. And so if a machine were to come in and replace my job, I guarantee you there are certain things that that can be automated, like things like data mapping. I think that data mapping, there is some level of automation that can be done there, but there is a lot of context that's needed to actually transform that data, right? So taking the raw data and transforming it for the all the applications that we use it for, all the reports and the products, transform that data requires a lot of context. Why does this specific practice or this specific person need this data? What do we need to remove? What do we need to clean? What do we need to change that a machine I don't believe can really ever fully grasp and a manager may be able to input some of these like parameters in there to aid in this, but it's a very involved process. And so I don't think that's something that a machine will ever really understand until maybe, you know, we create some process where they use like natural language processing where they can then talk through this. And then it, you know, runs, I have no, I don't know, artificial intelligence, but, you know, where it can understand what we are trying to accomplish, what we want, and then it does it. And I don't see that anytime soon. Now, is it possible? And this is something that people have asked me, well, if it is going to be automated, how far out would that be? My best guess is our job, this profession won't really start getting automated for another 10 years. And that's, I think, on the maybe the medium end. That's not really an end, but it's kind of in between. Some people will say five years. Some people say 15 to 20 years. I think 10 years sits a little bit right in the middle, simply because I think that within five years, there's just too many different applications and too different too many different software that people use throughout the industry that you can't just take one application and create it. And then, you know, in five years, nobody needs data analysts anymore. I think 15 to 20 years out. I think that that also could be possible or even to an extent. But I think that that far out, I think things will have already started getting more automated again, not everything. I don't think that everything will be automated. There's just certain aspects of it. And so 15 to 20 years out to me is a long ways out. I think it'll start happening before that. That's why I say around 10 years. Another reason I don't think that data analysts will be automated is because our jobs are to some extent, they are repetitive. But for a lot of what we do, it's not repetitive. The same every single day. So, you know, what I wrote here, I guess, is data analysts jobs are not the same every day. Each task is very different in the way we accomplish it can vary. So if I'm looking at just to speak in very vague terms, if I'm looking at a task that I need to accomplish, I can look at that and think of three or four different ways to accomplish that. And sometimes I need to get creative or I need to I need to use different methods or different ways to do that in order to make it the best it can be. Again, super vague, but a machine is only going to know like the way it's supposed to be done. You you. And again, I'm not an expert in this so that may not be 100 percent true there. You can set it up to do many different things. But you have to use some critical thinking, right? You have to look at a problem and be able to understand a lot of the nuances and complexities of it that I don't believe a machine as of right now can do. And there's a lot of things that within data that automation has already taken big steps like machine learning. But machine learning, you can take the data, you stick it into a model and the model is the same every single time. Whereas with data analysis, it's not the same every time. We're not sticking into a model. We're creating different reports and different visualizations. And again, certain things that can be automated. Um, so my next point as to why I don't think that this we're going to be automated anytime soon is I think the biggest thing that people are not taking into consideration is domain knowledge. I think that I'm just going to read what I wrote because again, it sounds better when I write it than when I just kind of spitball it. And this is kind of poetic. Can you teach a machine to understand domain knowledge, understand the data where each data point is how it's collected, why it's important and take that into consideration trying to read it like it's a poem. So if you're working with a client and an AI spit something out, but you don't have someone to explain it, how they got it, why it matters and what changes in the business it can mean, it isn't as impactful. And so that's and that's what data analysts do. We take the data, we gather insights into the data and we present them for change in some way, shape or another, whether that's reports or visualizations or whatnot. And as of right now, I have not seen anything that can do that. It can't take it from start to finish and be able to give you context and the reason why where this data came from, how, how we got it, why we transformed it the way we did and then spit it out and say, here's the impact or here's the things that you need to do to have an impact on your business. So in summation, I just want to throw that word in there, in summation, I think that there are absolutely parts of what data analysts do that can be automated. But I think that will only aid to make our work faster, which historically has never has not destroyed our industry. Right. Automation in our industry, which has happened has not destroyed it. It's just make us to done it faster. It's made us do it faster and then it makes us have more work, right? And so we have higher expectations, same pay, but more work to be done. Historically, that's what I've seen. And so I don't just from everything, all the way and everything that I'm seeing as well, these are talking points and things that I've thought myself as well as I've done a lot of research on this lot of articles that I was reading were saying very similar things to what I thought already. So I think I think so many people have asked me that, especially within the last couple of months, it's a real worry, right? If you get into this profession and in five years it's gone, that's a problem. So people want to be sure that that's not going to happen to them. And I fully understand that. I totally get why people are asking that. I personally would not be worried about it. I really would not be worried about it for the next about 10 years or so. And even then, I think the job just is going to change. It's not going to disappear and it's not going to be fully reduced to. I don't think it's going to be reduced down to like, you know, we only need like one day to analyze per company. I just don't think that's how it's going to work. I really, really don't. Onto the next, I guess, thing is, will artificial intelligence destroy the world? I read a lot of things on artificial intelligence. And doomsday and things like that. Just super interesting to me, not trying to be like a weird person or anything. It's just, it's interesting topic. And I genuinely believe that once we reach that point that a computer can be as smart as a human and it's going to, it will learn at an astronomical rate, it will destroy the world. That is my, that's my prediction. In some way or another, they will destroy what we know as living. May change what humans may survive, but we may not be in control, which is a crazy thing to think about. But I just want to throw that in there. I think it was, it's 100% on topic. The next part of the show is the question of the week. I won't call this the question of the month because it's been a while since I did one of these, just because I've had so many, so many other, I guess other things to talk about or videos to do. This one is from Ethan and he says, how much does the cloud play a part in data analysis? Is it worth doing any studying into Microsoft Azure, Amazon, AWS? I think that the cloud is the future of data for so many businesses because they just make it so cheap, comparatively to owning your own on prem servers and upkeep and all those things. They make it a very attractive offer and so many companies are going there for a reason. So, yes, I absolutely think it's going to play a huge part in data analysis, not necessarily because all of our work is going to be on there. We're not going to use all the built in things for our visualizations, etc. I think more the data is going to be stored in the cloud. You need to know how to use the data, get to the data, work with the data, and that's all going to be in the cloud in the future. I'm not talking in the futures in 50 years. Within 15 years, I will say the vast majority of people will have cloud platform or we're using cloud platform or almost every job will have that as some type of requirement or want for somebody who knows data analysis. That's my, I really do think that's a huge thing to know these days. I don't think it really is on the wish list anymore. It's much more becoming a requirement the further we get along. Like five years ago, when I first started as a data analyst, I think that it really wasn't, it was up and coming. Five years later now, it's almost a requirement to know. Highly recommend learning that, I really do. We're doing great on time. We're doing fantastic guys. I'm going to go on to the next part of the show, which is a shout out to the sponsor of this episode, which is everyone of you who sponsor me and support me on Patreon. You guys are amazing. I love you more than anybody else who is watching this. If you want to support the show, go on over to Patreon, support the channel, support the show, and I appreciate it. Another way that you can support the show is you can buy some merch, excuse me. You can buy some merch and I say merch. I just mean cool things like coffee mugs and t-shirts and face masks, all really cool things. Things like this mug right here, which says, trust me, I'm an analyst and you really should. You really should. Just something cool to have on your desk when you eventually go back to work. And so I have a link in the description if you want to check that out. So after this, I'm going to go on to the Patreon poll. This doesn't happen in every episode, so I think it's going to be really interesting. This says, share my favorite thing I like to cook and how to cook it. Now, it's really interesting because in my house, I have three kids. I have a wife, I have a dog. I am the only one who likes omelettes. My wife does not like omelettes. My daughter does not like omelettes. My other two kids who don't really care for food really don't like my omelettes. I don't know why. Max, he will eat it. Me, I love omelettes and I love the way I cook omelettes. And so I drown out all the cries and I make omelettes sometimes. And so, omelettes are my favorite thing to cook because they're easy. I have the capability of doing it. And it's one of those things where it's kind of like a pizza. You can just kind of put whatever you want on it and it usually turns out pretty good. And so for me, I like the staples of some type of meat, like a turkey or a sausage, then cheese, maybe some peppers, then salt and pepper, super simple. I'm going to tell you how I cook it. Now, there's maybe some advanced stuff for you guys. So just be aware. I heat the pan to a 4 out of 10, so low to medium heat. Now, you want to put the spray and I use Pam, or maybe it's like a generic Pam, I mean like a Kroger Pam or something. I use Pam on there. Now, what I like to do is I don't put the eggs directly in there and then scoop them around and break the yolks and stuff. I put in a bowl and I whisk it. And I whisk it a lot until it gets nice and airy and fluffy. And I actually put the salt and pepper in with it and whisk it then. After that, I pour it into the bowl. And again, it's on low to medium heat, a 4 out of 10 on my skills at least, on my... What's it called? Is that an oven? A grill? No, what is that? Countertop? Countertop grill? Oven? You know what I'm talking about. I'm on stove where you put it on the top. I don't... I'm really... I'm genuinely blanking on this. Just where I'm going to Google it. Stove? I put it on the stove. Let me... Yeah, it's a stove. I have no idea why I couldn't think of that or why I didn't think that that's what that was. So I put on the stove and I let it heat until literally the egg on top is not jiggly anymore. It's like just barely moving. So it's like almost cooked all the way through. Before it gets to that phase though, while it's like half cooked through, I put all my meats and cheeses and vegetables, etc. in there. And then right when it reaches that point of just about to be done, I flip it. I put half... Man, I'm not doing good at describing how I cook it. You only put the vegetables and everything on one half of the omelette. So then you take the other half and you flip it over it. I hope you know what an omelette looks like. If you don't, I'm probably talking nonsense. And then I flip it onto the other side, flip it onto the other side. I let the cheese get melty and then I take it off. No milk. I don't put milk in my eggs. Some people do that. I don't believe in that. That's weird. That is how I cook an omelette. I prefer them to be three to four eggs, which some would consider too much. Some people like to do two. I do not agree with those people. Three to four eggs. Yeah, I think that's all I got. I think that's it. I think that's how I cook it. With that being said, we're coming to the end. I feel like this was a good show. It's been all right. It's been pretty good. But with that, we've come to the end, and I'm checking my time really quick. We've got a few minutes. We've come to a time in the show where I just like to hang out. I like to chat. But I also like to give you the, I guess, the validation that you deserve, which is the vegetable of the week. If you want to show that you got to this point, that you care about your job, not only now, but in the future, whether it's going to be automated or not. And you want to put that in the comments below. The keyword of the week, the vegetable of the week, keeping it vegetable-based, is cauliflower. That is a new vegetable that we're actually planting in our garden this year. Just like literally today as well as yesterday, completely get in our garden, put in a compost and dug it up and planted everything we have cauliflower for the first time. So we're going to see how that goes. Really excited about this year's harvest, because last year's was really good, except for the corn which got eaten. If you didn't know, and if you're on to follow my Patreon, I just posted a video of me gardening. It wasn't a video, it's a picture. A picture of me gardening the other day. So if you want to see what that looks like, of course, you have to go check out Patreon. But really interesting, like gardening is just, I guess when I was growing up, my parents had a garden. And when I got married to my wife, Christine, she likes to garden too. And I didn't know that until we moved into this house, which already had a garden built in. I don't think we would have gardened otherwise. But we have made it really good. We've really made it nice. So it's a really cool family thing to do, because then Kennedy and Xander get to go out and pick the vegetables when they're ready. It's really, really fun. Something that I was just talking to somebody about. What was this? Check time, because I don't want to make sure I have time for the story. Not really even a story. Somebody I was talking to somebody about this was about LinkedIn. And my persona on LinkedIn was super, super funny. Because this person, they know me pretty well. They know me both as a YouTuber as well as somebody on LinkedIn, but they knew me on YouTube first. And on YouTube, I think I come across much more as a helpful person. I'm trying to be kind. I really want people to succeed. I'm very uplifting. And then on LinkedIn, for whatever reason, and I didn't do this on purpose, I've become much of a controversial topic on LinkedIn, which I think is super fun. I like to post controversial things. If you haven't checked out my LinkedIn, you should check it out, because I like to post things like Python is better than R. That's a big one that got a lot of attention. And so I was talking about this with somebody, and they were like, it's like you have these two different identities. The people who know you on LinkedIn and follow you on LinkedIn, they know you as this controversial person. This person is like, wow, I can't believe he said that, that kind of person. And then if you go over to your YouTube, you're much more like, man, we're all in this together. We can do this. Like I'm just here to help. I love you guys. And it just got me absolutely cracking up, because it's super true. And I didn't do this on purpose. But I did that one post that one time, and people just lost their minds. And I thought it was hilarious. So now it's mostly like memes. And it's mostly like being controversial and just being going against the grain, which is completely opposite of my YouTube. And again, I didn't do that on purpose. I mostly, it's just so much fun, because LinkedIn is supposed to be a professional place. Whereas YouTube doesn't have to be a professional. You can do YouTube, you can do whatever you want. So it's kind of opposite. I feel like on YouTube, I try to be at least somewhat more professional, but more engaging, more kind, more loving, more caring. Whereas on LinkedIn, I'm much more like harsh and I'm like, I'm much more critical and polarizing is how I would say it. I don't know. Again, I don't know why that is. It's just, I think it's more fun. It's more fun to do that. It's genuinely why I think I've developed that in both categories. That's really all I got today, guys. Automation and the world, question of the day. My favorite thing I like to cook and then cauliflower. I mean, just skip to this point next time if you want to just remember what this was all about. I think, I think that about sums it up. It really does. I will be wearing, hopefully in the next episode, the vegetable of the week t-shirt. So I can point to it or something like that because I think it'd just be more entertaining. But that's just kind of one of my life goals is to wear a t-shirt that I made on my show. I think that's just something that I really aspired to my whole life. Yeah, I think I'm fading and I'm fading fast. You guys are getting the delirious, delusional Alex at this point. It's like, it's like 1130. I mean, I still got other things to do tonight. So you guys are getting like the groggy. I need to get up and get some sugar. Legitimately, I'm going to go right over here. That's where my pantry is. I'm going to go to the pantry. I'm probably going to get like a granola bar or something. And I'm going to eat it and then I'm going to keep working. I mean, I still got more to do tonight. So I think it's for the best that I stop. It was a good show earlier and now it's just bad. Thank you guys for watching. I really, really do appreciate it. In future episodes, I will try to refrain. I guess I'll try to refrain from, see, I can't even keep concentration. I'm just losing it. My blood sugar is like tanking. I will try to refrain from going on such long tangents to keep it mostly to the meat and potatoes of what we're talking about. But I can't make any promises. You know, when I start tanking like this, it's either entertaining or it's a train wreck and you just got to watch. So for all those people who are still watching, I mean, you guys are the real MVPs legitimately. I don't know why you're still listening. Maybe it's just because they're time to film. All right, I'm going to go now. Thank you guys for watching. I really appreciate you. I will see you in the next episode.