 Hello, hello, hello. I got my thing over here. I got to wait till it starts so I know it's actually working. Give me a second. You may hear some feedback because I'm just making sure it's working right. So give me a second. But hey, everybody, we'll get started very shortly. Started a minute early. There we go. All right, everything should be good. Give me a second. I'm going to check the settings real quick. Bum, bum, bum, bum. I should be good. Should be good. I'm just making sure. I got to make sure everything is working before we get started. Oh, hey, everybody. I have on my computer over here your guys' comments. Oh, hey, guys. I see all the chat's coming in. All right, let's see. All right, hey, guys. All right, we're going to get started. Now, this is our monthly live stream supported by you guys. So everyone who is a member of the channel, they join the channel. And then they're a member. You can see them because there's some people in the chat. I think, like, yeah, I see a few people in the chat, like Barry Enthos, who is highlighted in green. With the star, that means she's supporting the channel. And that means that I'm able to do stuff like this with you guys. And I really, really appreciate it. So thank you guys so much for joining. We have a, jeez, like 140 people in here already. Really, really excited to do these. I love doing these live streams because I get questions from all over, LinkedIn, email, Twitter, Instagram. I get even in-person mail, which you can send to me. I have a PO box if you check my channel. And so I get messages from everywhere. And so it's really great to do something like this where people can just join in live and kind of walk through my thought processes instead of just, like, messaging something back. So I already know we're gonna have a ton of questions today, but it should be really, really fun. And, you know, I may take some water breaks here and there because I get thirsty. But this is like super informal. This is just for you guys and just time for us to hang out and answer some questions. And hopefully a lot of people have similar questions. And so I can answer, like, a lot of people's questions at the same time. And that's usually really helpful. So, hey, everybody. I see a bunch of people. We got Neptune. Let's see. Kago. Asaf. Off. That's a cool name. Ah, Hakam. Zidam. Zidam. Very cool name. A lot of really awesome names. Muhammad. Jay. Hey, everybody. All right, so in one minute, now that I know everything's working correctly, in one minute, we're gonna get started. Really how this works is I am going to answer your questions. Go ahead and post a question. If you start spamming questions, I'm gonna like just block you so don't do that. I usually also have some moderators in the house. So if they're in here, they're gonna get rid of you. Matthew's here. Matthew Alderman, he's my guy. So if you start spamming stuff, he might block you. So don't do that. It's just, it's not worth it. So anyways, with that being said, we're gonna get going, and I'll try to answer as many questions as I possibly can. I'm gonna try to, this is gonna be a longer one. I'm going to try, because we started at like what, 10.30? You see? Yeah, we started at 10.30. So I'm gonna try to go into like 11.45. Maybe even noon if we're feeling crazy. So let's go ahead and get started. I'm gonna scroll up because I saw some questions up here before. Thank you, Siva. I see some questions up here before. Let's see. This one's from Defying Odds, Donnelly. Hi, Alex. How should you go about getting, wait, how should one go about getting their first entry-level data analyst role if the jobs have been cashiering, help or clerk, and other jobs? So I've worked with a lot of people who just have completely random backgrounds. They've worked like in a warehouse. They worked as like an Amazon delivery driver, like random people. But self-admittedly, they're like, I really have this like analytical brain. I love working with these tools. I like this stuff. So this is like what I wanna do. And I'm like, let's do it. Let's get it. What I usually recommend to those people is I'm like, look, your background, especially something like cashiering, or cashiering, help or clerk, and some, those aren't really related jobs, right? You can try your best to try to phrase them and look at it in an analytical way. But sometimes you just can't, right? Here's what I usually recommend. And I have a whole video on creating a resume. Really what you wanna do in that resume is you want to put your skills up top first. Then you wanna put things like projects. Then you wanna put things like maybe certifications or certifications or your education if that's relevant. At the very bottom is where you might wanna put your, basically your experience that you have or you don't really have experience. You have like just kind of random experience. The reason for that is when somebody reads your resume, they're looking for someone with who knows SQL and knows Tableau. Maybe that's the only two things they care about, really. And then they'll see that and they see it at the top. Okay, this person has it. He's done some projects and you can talk to it and they're like, okay, you know, this guy kind of has what we're looking for. And then they finally get to the bottom. They're like, oh, he doesn't have the exact experience we're looking for, but he has the skills we're looking for. That's what you're kind of going for. The other thing I'd be doing really heavily is working with a recruiter, especially if you have no experience. I have almost exclusively gotten jobs through working with recruiters. They are just extremely helpful. They kind of have an in into a lot of companies that you will not get if you aren't working with a recruiter. So highly, highly, highly recommend trying to work with a recruiter. Raffu Nangrum says, please do a walkthrough of a typical data analyst interview process. Sure. So as you guys probably know, I was a hiring manager. I've been on hiring teams as well. So like for the past, well, before I quit my job and start my own company, for the past like three years before that, I was either on a hiring team or I was the hiring manager. Typically how something like a data analyst goes is you have the recruiting stage. So we, my company was like a Fortune 10 company and worked at a company called Amerisource Bergen, super big global company. What we would do is we had recruiter, recruiting companies work for us. So we didn't have to do the initial layer of recruiting. So you'll get a call from a recruiter. You'll get on the phone with them and they'll ask you questions, right? They will make sure you have like the basic things that we're looking for. We need someone with SQL. We need someone who knows Power BI. We hopefully know someone who knows Azure and has some experience with healthcare. That's what we would be looking for. Once you pass that level, you get put into like a smaller pool of like, here's 10 candidates. I as like the hiring manager on the hiring team would then review those 10 candidates and say, okay, it looks like these five are really what we're looking for. Cause again, those recruiters don't know exactly what we're looking for. They just kind of have a general sense. So we narrow it down to five when we bring those five in for interviews. You have the first interview that is typically like just a get to know you, get to see if you're gonna be a good fit. There typically isn't a, at least from, I've taken, I've also been in a lot of interviews cause I've interviewed for a ton of companies. Typically that first one is just like a get to know you. Is this person even seen like a good fit? The second one and to go a little bit more in depth, they're just gonna ask you general questions. What experience do you have? What skills do you have? Why do you think it'll be a good fit? Those types of questions. The second one is usually more technical or a lot more in depth. Tell us much more about how you know healthcare. Tell us a lot more about how you've worked with healthcare data. Take this technical test. Here's a take home test or here's a whiteboarding test or just walk us through your thought process on how to solve this problem in SQL or Python or Tableau or whatever it is. And then the third one is typically like with like the hiring manager only, they're just making sure and then they hire you. That's usually the whole process and then you can negotiate with and walk through that whole process. So that's kind of it. That's typically what it's gonna look like. Now this next one is from Danish Thakur Bakker. And it's multiple questions. I'll see if I can answer all of them. What is the impact of AI on data analysts career in 2023? What important things should aspire to be data? What important things should aspire to be data analysts 2023? Keep in mind. Okay, so what, I got it. So the first question is AI and in data analytics. It's definitely gonna impact things. It's impacting a ton of things or a ton of different industries. There's new stuff being built out all the time. The impact right now is really, it's just a good tool. It helps you get your work done faster. And honestly, I think it's gonna be like that for a long time. I don't think, I know a lot of people right now are worried about like automating jobs and data analysts jobs. I don't see that. I haven't seen it. I have a lot of connections at places like Microsoft and Google and a few other companies. And I've asked them, I'm like, hey, do you see this? And all of them are, and they're all analytics focused or data science focused. And all of them have said the same thing like, no, we haven't really seen any impact or we're not even really thinking about that for the foreseeable future. It's not as widespread as a lot of people think. It's not like, oh geez, AI's here, jobs are gone. I mean, if that were to happen, it's a long, long, long, long process to even start thinking about that. So yeah, it's not as big of a concern in my opinion as a lot of other people. And I've just done massive amount of research on that. So that the impact right now, I just see it as a really helpful tool and I think it's something people should be learning. That's really what I see. Then the important things that aspiring data analysts should keep in mind is that the basics are the basics and they're not going away. All these new AI tools, there's a lot of hype around them. I've used a ton of them myself and I've tried them out but you still need to know the basics. Like everything in, you know, I have my data analyst bootcamp playlist, everything in there is still gonna be 100% relevant even in five years. You know, Tableau's gonna change a little bit, Power BI might change a little bit, Excel might change a little bit with some AI stuff and I'll make videos on all those things but the tools themselves are still gonna be the tools. They're not gonna be a huge overhaul of what they are and how they're used. I just might speed up the process using some AI along the way. So that's my general thoughts. I'm sure more people will ask about that later on and I have a million thoughts on it but that's my overall thoughts. Let me scroll down. We have a ton of, I see so many questions so I'm trying, maybe I gotta answer them shorter. Let's see, someone asked, PopBeat said, can you walk me through how to write an entry level data analyst resume? No, because I have a whole video on that. So go watch that video, it walks through everything, I free templates, everything. Just go watch the video, that'll help you. Let's see. So Naeem Shahzad, if that's how you pronounce it, says please guide me on how to get a remote job of data analyst in Europe or America while living in Asia. Now that's a really common thing that I hear and not just from Asia but it's people who are living in Singapore or Africa or South America and they want a remote job which makes complete sense to me. Now this I don't have a ton of experience with, I'm just gonna preface this, this is like things that I've just learned along the way, right? Typically if you're working through, if you're working for an American company, you can do that freelance, it is possible. Although it's for most larger companies, they work through certain companies like my company worked through Accenture and then we also worked through Tata Consulting Services or yeah, TCS. So we worked through Accenture and TCS. So one of my biggest advice because we worked with people in Lithuania and Romania and parts of Europe and Australia and Canada. So we had people all over the world. I would just try to work with one of those companies. That's really the only best advice I can give because that's my experience. There are people like, oh, trying to think of his name. There are people like on LinkedIn and YouTube who have more experience with consulting from like overseas into America. I don't, that's just not my specialty. I don't have a ton of experience with that. So that's my biggest advice is try to work with one of those consulting companies because typically they'll work with American clients. And then one of our people who live who's from Pakistan, we ended up hiring them on full time. So then he got a visa, he came over and then he worked in person full time. So, it's very possible to do it. It's just, there's a lot of other people who wanna do it, it's pretty competitive. That's my experience, that's what I know. Let's see. Hi Alex, this is from Neelam Rathor, a Rathor. I try my best with names guys, don't judge me. Says, hey Alex, I have worked in SQL where I used a bit of COVID but I have errors with null values but I clean all data then I import all data in SQL. Okay, I'm guessing you're talking about the COVID video that I did and you're having issues with it. Yeah, it's hard, I mean based off what you said you're having errors with null values. It's hard to say, I need a lot more context. Shoot me a message on LinkedIn, usually I answer this faster. So shoot me a message on LinkedIn with a screenshot and I might be able to help. Let's see. Hey from Poland, hey from the US. How's it going? Hi from Philippines, hey, hey from the US. Let's see. Mahesh Yadav said, non-computer science background can become a data engineer. Sure, why not? Data engineering is not my specialty, although I love it but I'm sure you can, yeah. Prashant said, kindly make real-time projects. Absolutely, in fact, one of my goals, so just so you guys know, I'm about to finish the pandas playlist then I'm gonna do a regular expression playlist, a web scraping playlist in Python, then we're gonna start a MySQL playlist. Now, that's a lot of tutorials, right, it's a ton but those are all going into the bootcamp for people who are doing the bootcamp because I have like a lot of people who are doing that. Once we're done with that, I'm gonna be doing full end-to-end projects. So we're doing projects in SQL, we're doing projects in Tableau but what I'm gonna do is I'm going to do end-to-end starting in Excel, we'll do our Excel work, we'll put it into SQL, do our SQL work, we'll put it into Tableau, do our Tableau work and then post it up, so it'll be an end-to-end project. Well, I'll be doing many of those. So Prashant, do not worry, I promise you I will be doing that. This is why am I sitting in the dark, that's a great question, I have a light right here, I have a light right over here and then I have this light in the background, so I'm actually not in the dark, it's actually pretty bright in my room, just the background on this side is darker because I like it, I like how it looks. Let's see, A.J. said, hey Alex, do we need to learn PySpark in order to be a good data analyst? No, although I use PySpark quite a bit when I was working in Databricks. So Databricks, and we had Databricks integrated with our Azure data lake and database that we were using in Azure. So part of my process is I would use a lot of PySpark with big data, like a lot of data and then we were working with some really unique data pipelines and file types and stuff like that. And so PySpark is awesome, I love PySpark, but you also don't need to know it. So no, I think that's a little bit more advanced too, it's a little bit more advanced. Let's see, can I become a data analyst by watching your series? I've been thinking about this a lot, I've taken a million courses, I legitimately like hundreds, like too many, I've taken way more than most people ever should, I just, it took me a while to really understand things when I was first starting out. So I've taken a thousand courses and my playlist that I have legitimately is like one of the more comprehensive, more hands-on, technically wise. You don't learn everything about the theory or the domain knowledge or a lot of other stuff, but you learn a lot of the technical stuff, like the nuts and bolts, the meat and potatoes and stuff that you can use every day. I think you can get like 80 to 90% of the way there with my free stuff or at least like, maybe like 75 over being conservative, right? There's obviously more stuff that I haven't taught in my data analyst boot camp, but I'll get there, I'll keep adding it. And just so you guys know, like I'm creating full courses that dive into all of these skills, like way more in-depth and way more data analyst focused and stuff. So eventually those will come out as well. I mean, those will be like a lot longer, a lot more in-depth, that'll be pretty interesting. Two, oh geez, guys, it did that thing. It did that thing where it skipped down and now I skipped like a thousand questions. Oh, what have I done? I apologize, I'm just gonna go down to where I can see it. Let's see, bum, bum, bum. I see a bunch of other people saying hi. I also finally saw Matthew saying present. Oh, Matthew said, not a question, but I got a promotion, Business Information Manager. That's what's up. Congrats, Matthew. That's fantastic. And then someone, someone just, I'm reading through comments, I skim the comments. Neptune Palace said your April Fool prank almost got me a heart attack. That was funny. The reactions I got was, I was dying laughing that whole day. It was hilarious. What is my favorite character from the office? Favorite character from Star Wars from the office? My favorite character would probably be Michael Scott. And from Star Wars, it would probably be, let's say Obi-Wan Kenobi. Are you adding more Excel or SQL YouTubes? Yes, I'm creating a whole MySQL playlist that's gonna replace my Microsoft SQL Server playlist because MySQL can be on any operating system, whereas Microsoft SQL Server is mostly just gonna be able to be on Linux or Microsoft and Mac people are not happy that I didn't have that. And so to appease all the Mac people, no, that's not really why, but it really does help that everyone will be able to use MySQL. So that's why I'm doing it. But yes, I will have a lot. I'm creating a ton more stuff, ton more content, more in-depth, more advanced. It's all coming up, but I have to get through what I'm making right now, which is web scraping, regular expression, and then my MySQL series from beginner to advanced. That's months of content right there. After that, I'm gonna be diving into some big projects as well as more advanced playlists and things like Tableau, Power BI, and then looking at some AI tools to integrate into those. So that's kind of some stuff we'll be doing in the near, excuse me, towards the end of the year. What do you think about, this is from Reinhard Van Astria. Hey, what do you think of the prospects of the field this year and what is the path to work that you recommend? So I talk a lot about that actually in the path in how to become a data analyst in 2023. I mentioned a lot of my own stuff because it's good, but you can take Coursera, Udemy, Educative, Udass. These are a ton of great platforms. But I think that this year is, we had a huge upswing in hiring in data analytics, like in 2022, just a huge upswing. Everyone was getting a lot higher salaries because there was this huge tech push. And then they, you know, we have this kind of not a, I wouldn't even call it a crash, it's just a correction because they overhired way too much. And so right now we're kind of in a little bit of a slump, at least at large tech companies, but I will say mid-level companies, Fortune 500 companies are still hiring almost the same. It was mostly the tech companies that kind of like screwed themselves over, if I'm being honest. So I think it's still a pretty good year, but in the tech world, looking at large tech companies, it's not that great, but it's still been an overall fairly good year for hiring. Let me keep reading. Yeah, I'm filtering through a ton of questions here, so let me just make sure I'm getting good ones. No, is it no or noe? Noe, that doesn't sound right. No Beriantos said, hey, Alex, I was able to, I wanted to thank you for everything. I was able to land a mid-level data analyst position at a technical college in Texas. Hey, awesome. This position is fully remote. I'll also graduate in May. Congratulations, that's huge. And fully remote, I just moved from Texas to South Carolina, so good luck with the heat down there, but that's fantastic, super awesome. Let me see, let me see. There's just so many questions. I'm just, some of them I've already answered. Okay, here's a good one. Atif Manzour, this says, do we need to learn both Tableau and Power BI to get our first entry-level data analyst job? I like Power BI more as compared to Tableau. No, and here's the logic behind it. Tableau and Power BI are actually somewhat similar. When I first started learning, I learned on Tableau. I didn't even know what Power BI was. Like, I kinda knew what it was. When I worked out, the last company I worked out, I used Power BI for like three years, but I actually found that a lot of the stuff that I learned in Tableau was pretty transferable. If you really know Tableau well, and you know how to build things, you understand a lot of the intricacies of it, you'll be able to bring like 80% of that over to Power BI. At least right now, right? There will be new functionalities and new things in both of those products in the future, but visualization is visualization. They're gonna be fairly similar. Now, if you're working for a company that uses Power BI, that's fantastic. You wanna put on your resume Power BI and Tableau, but you're really just good at Power BI, I still think that's pretty fair. Just because they're pretty similar. So, yeah, I don't think you need to learn. I don't think you need to learn one. Mary Anzo's just, she's hyped me up right now. I think it's a good, right? No, no, that was a good thing, right? But they said, couldn't have done it without you, member for life. That's so sweet, you know, it really means a lot. I'm just reading her stuff because it's like popping up with the green, so like I see it immediately, sorry guys. But thank you, that means a lot. McKayla Mellerson, Mellerson is a really cool last name. It's kinda like my very unique, like my last name's Freeburg, super unique last name. Mellerson seems unique. If SQL is new to an individual, just learning it, how much time would a person dedicate daily without becoming overwhelmed? Also, what syntax would you say to focus and get good at to start? Okay, super common question. When you're first getting started with SQL, like what type of SQL should you be learning? What are the differences? How much time should you be dedicating? You can be like me, and I was super, super, super slow at learning it. And it took me like four months to learn like the basics. I was just, I did not understand it at all. But if you're like, if you follow my tutorials, where they're like really make a lot of really good sense, if you follow my stuff and you dedicate like an hour a day, 30 minutes a day, you can learn it in like a month or two. Like do a good level or do a good degree. Do you guys wanna see Rosie? I'm gonna say yes. They wanna see Rosie. Hey, Rosie. Hey, Rosie. All right, Rosie, come here. Oh, that's Rosie. And they see, oh wait, there there. Hey, Rosie. Yeah, she's on the screen. Hi, everybody. I used to be a little nugget. Now I'm a big nugget. She wants to leave. All right, I got people to talk to. I get out of here. Thank you. That was Rosie. All right. But the syntax I would learn, sorry, I'll go right back into it. The syntax I would start with is MySQL. I personally like Microsoft SQL Server the best. I think that's the best syntax. You have TSQL, which has a lot of extra functionality, but not every company uses Microsoft SQL Server. I would say, MySQL is more ubiquitous in the community. And so I would start with MySQL. Almost everything in MySQL transfers to Microsoft SQL Server. It's slightly different syntax and a few things, but then not everything from Microsoft SQL Server transfers to MySQL. So that's my recommendation. Let's see. Oh, here we go. This one, Michelle Bold said, my background is in medical coding. Could that experience transfer well to healthcare data analyst roles? I don't know much about medical coding. Unless you're talking about like HixPix codes, ICD codes, link codes, that kind of coding, that information actually is pretty useful. I kind of got one of my first jobs from knowing all that stuff because I worked in the nursing healthcare side for many years before that. So if you know all those codes, I would definitely could help. I need to know more about what that does exactly. I don't really know much about that, but it could help. Experience in healthcare can definitely, domain knowledge is very useful and helpful if you know it well. Let's see. Let's see, let's see, let's see. Oh, boom, boom, boom. Interesting. Badder Bensasi, that has got to be the worst pronunciation I've ever done on the show, on any of my live streams, but hey, like I'm trying. Thanks for the content, Alex question. Do you recommend starting as a data analyst than switching to data science? I'm 29 and just getting started with no background. This is again, a very common question. I think if you really want to be in data science, data analytics can be a great stepping stone. It really can. There's no doubt about it. Even myself, I had the opportunity, they wanted me to go and be like a junior data scientist. I didn't want to, it wasn't what I enjoyed. And so they're definitely our stepping stones, especially when you get into a company. It's a natural, it's a very good stepping stone in a lot of ways. But if your end goal is to become a data scientist and you're 29, it's hard for me to give really specific advice to you, but here's what I will say. If you're just getting started, it can be hard to just dive in to data science, right? It's pretty competitive. You kind of need to have some background and some domain knowledge at your age. And let me kind of take a small detour on this answer. I have a lot of people who are older, 30s, who want to change careers into data analytics. And it can be tough because you have to think about it like this. If you're 21 right out of college and or even younger right out of high school and you're trying to get a job as a data analyst, they can pay you pretty cheap, right? They can pay you 30 grand, 40 grand because they're like you're out of college, you don't know anything. So we're gonna pay you cheap and you'll be a data analyst for us for like a year or two. It's very possible and companies know that and they expect that and that's just how things work unfortunately. When you get into 29, 30s, sometimes even 40s, you already have work experience. So they understand that you're gonna have a certain expectations in terms of salary. You're also, they kind of expect with your age, there's this expectation that you have some type of domain knowledge or experience in the area. They don't want to hire someone who's 35 at a senior level role who's just starting out. It's also kind of can be weird having someone who's 35 in an entry level role working with people who are 21. So there's a lot of dynamics that go into play there. It is absolutely possible, 100% if you find the right company, 100% possible. It's just as the older you become, if you don't have any background, no experience in anything related, you don't have any healthcare experience or financial experience or something that would relate to data analytics like on a larger scale, it can be harder. I'm just prophesying that, it's a small detour. But yeah, I think going to data analytics can definitely be a great natural progression to data science, absolutely. That's what I'll say on that. Will chat GPT, this is a great question. Mahesh Babu, will chat GPT replace data analyst jobs? My honest opinion is no. And this is something I actually thought about the other day and really looked into because there's things like auto GPT, baby GPT, some autonomous agents going and doing stuff. And it's really impressive. Now I've looked into myself and even things like that, I'm just like they don't, it's doing, so okay, let me take a step back. Since I've been a data analyst in the past six years, even before that, there were companies that were doing this automated data analytics. This is not new, right? People think that this automation is new, it's not new. I've seen it. I've worked with tools that do it. And one second, my wife is not my wife, so I don't care. Automation and data analytics is not new and it's nothing groundbreaking. So what a lot of these companies, these startups, these even larger companies do is they'll get your data source, they'll take your data source in, they'll bring it over and they'll populate some basic dashboards inferring information from your data, right? Now, that's all fine and dandy, but then it took a lot of work because then you had to fine-tune everything. There's a lot of business rules, a lot of data cleaning, a ton of stuff that you had to do to really make it usable, a lot of business use cases. Then you didn't just want the data as it was, you wanted to transform the data into look like this and then you used it for your product, a ton of work. So on a small scale, a lot of companies are already doing this automated data analytics. From what I've seen already in ChatGbt is that, it's great, it is a little bit more specific, it's a little bit better, but it doesn't do anything that I would say is like crazy special, it's not gonna clean your data all the way, it just can't. Unless you're inputting all the business rules, all the variations, putting all these tasks and data quality checks in place which should not be automated, parts of it should, but not all of it. And then the visualizations are, they're spitting out these visualizations. That's not really what data analytics is, right? Data analytics is working with a company, working with a stakeholder, working with a business, understanding their business needs and then delivering that, whether it's a dashboard and a report, whether it's fine tuning the data for their product. It's a lot, lot, lot more than just creating visualizations. So these companies that used to do it, it was never really crazy impressive. ChatGbt, it's a little bit more impressive because now it understands a little bit of the context of the data. You can do a little bit of basic data cleaning, I've already seen it. You can also do a little bit of, or it can do a fairly good job at the data visualization. It can, but that's not really what data analytics is, right? It's hard for me to like really articulate just in this small way exactly the differences, but I've worked with these data pipelines, these types of clients for a lot of different companies and now I've been consulting with these different companies. I just don't see how it's gonna happen. And it granted, in five years I could be eating these words, it's possible. I just knowing how customers are, knowing how those workflows happen, understanding the background in data cleaning, transformation, data pipelines, all these things that I've experienced in, I don't see a data analyst being automated anytime soon. I see these tools being very helpful, but there's so much more work than just goes into these small automations that even chat GVT can do right now. It's gonna take a long time. It's gonna take a long time. Honestly, there have to be like something that's like fine-tuned just for data analytics in my opinion that can go way more in depth than what it currently can do. Now that's my two cents. So, no, I don't think it's gonna replace data analytics even probably within the next 15 years, 10 to 15 years. Again, I preface all that by saying, I'm trying to imagine what they could do to automate that entire process to the extent that it actually needs to be in order to be productionalized and have no outside help. That's like, that's a long ways away in my opinion. It's just, there's so much more than just like creating visualizations. I mean, I can create a pipeline with a visualization and AI can do it. It's not crazy hard, but there's so many more nuances and like things that really need a person in my opinion. How important, oh, this is a good one, Allie Perron. How important is data infrastructure and data governance to a data analyst role? What aspects of infrastructure and governance are necessities? Small companies, you may be working this as, let me reset this. Small companies, you may be working with this quite a bit more. I don't know why. I'm being like really serious right now. Let me look at myself. I'm being really serious right now. I need to be more happy. When I get, you guys may not know this about me, but this is like my face when I'm working. I just have this like scowl. I don't know why, because I'm a very happy person. So like I'm really focused on these questions, like really trying to give answers like this is how I look. But on the inside, I'm like this. Data governance is a wonderful part of data analyst roles, especially at smaller companies. So at smaller companies, you're typically going to be doing more data infrastructure and more data governance. Usually that involves things like quality assurance, you're making sure that the data is coming through. You can create triggers and warnings for certain things. Sometimes that's what data governance does. But a lot of it is like managing databases, right? Typically, excuse me. Typically at larger companies, data analysts won't do any of this work. When you'll have data architects, you'll have database DBAs, database administrators, and those people will be working mostly with the data infrastructure, data governance. Those are like those two main roles. But sometimes at smaller companies, you are gonna do it. With that being said, is it the most important thing to learn right away? No, not the most important thing to learn. Shabazz said it's hard to find a data analyst job. Can you give me tips? I have a ton of tips on my channel, but I'll give you a few tips right away, which is most people don't put in the effort in the extra effort to create a data analyst portfolio. I always liked it. It always helped me land my jobs. It always did. It always came up in conversation. It always came up in second, third round interviews. Cause they're like, what is this? And I'm like, well, this is a project that I created. It automatically does this and this and this so you know, whatever tool it was. And they always found it interesting and useful. And I always recommend people doing it. So that's always helpful. Next biggest, biggest, biggest thing to work with a recruiter. I have so many people messaging me and they're like, hey, I've applied to 2,000 jobs with the same resume and I've gotten zero callbacks. I'm like, that's your fault. That's on you, my friend. That has nothing to do, don't blame anybody else but yourself. I'm more kind about it, but it's you and me. Okay, it's just you and us here. You and me here and 300 and some other people. Right, you have nobody to blame but yourself. If you're not getting interviews, it's a resume problem. If you are not getting callbacks, it's or you know, you interview and you're not getting callbacks. That's an interview problem. If you're not landing the job at the end, that's an interview and problem. These are all, it's either an interview problem or a recruiting problem or you know, a resume problem. So work with a recruiter. Have a really great resume. Have your friend look at it. Go in the Alexandria Discord community. There's a lot of places that you can get feedback. And then you need to be working with a recruiter, applying to jobs, messaging recruiters on LinkedIn, cold calling, cold email. This is, you got to hustle, man. You got to hustle. That's my recommendation, you know. I remember when I was first doing, I was hustling like crazy. I applied to a thousand jobs because I didn't know what I was doing and then I found recruiters and my whole life changed. So, that's what I got. I'm way behind on questions. Harry in data, what are three most important attributes to foster to become a great data analyst? I would also like to know. I'm just kidding. I'll try to answer this. Genuinely, I think, having an interest, that is probably one of the biggest things. I've worked with a lot of people who just don't show an interest in their work and it shows. So, being interested in data analytics, I mean, that's probably been one of my great selling points and interviews. I just love it. I'm just super interested in it. I love learning. I love finding these patterns like a curiosity, curiosity and like a passion. Those are big ones to have. Just an interest in your work. That's a big one. The next one really is communication and everybody says that but I've seen, I've worked with people who are not good at communication and it makes your whole life miserable. Being a good communicator, knowing how to present information, knowing how to work with clients, creating realistic expectations. When you don't meet those expectations, how to relay that to your program manager or your boss or whoever and how to follow up on that, how to write good emails. Communication is like massively important and I was not good at it when I first started. I had to work really hard at it. I really did. So, those are some of the more important things I would say. I'm gonna, I'm keeping, I'm reading through some more questions trying to find some good ones. Give me a second. I'm still looking. Some of these are too generalized. Okay. It's an interesting one. Jordan Rand. Hi Alex. I've recently discovered your channel. I'm very interested in getting started in data analysis but I do not have any experience with coding. Any thoughts on how to dive into coding? Now, when you say coding, I'm typically thinking of something like R or Python. SQL is a query language. You can call it programming. And honestly, there is, I think when you get to a certain level in SQL, it does become more like programming, like more database engineer stuff. That becomes like legit coding. So, if you're talking about like, how do you learn coding? I, when I first learned Python, it was like teaching a parrot to like do water skiing. It was tough to watch because I was just so bad at it. And I didn't understand it. If I were you, and this is not a self, it is a self plug, but it's not a self plug. I would start with my stuff because I remember what it's like to be like the entriest of level in Python. And now I try to understand, I try to come about it from like a super beginner, like where I was and build you up into the more advanced topic. So I'd start with my stuff, but really it's about building things. Like people, you can take tutorials all you want, but until you build something with it, you're not gonna learn. That's why like when I do tutorials, I do projects along the way because that's how you really get it. Like you visualize, oh, when I did these things, I got this output and I built a calculator. I built an automated process where I built something. So build things. Think of something small that you wanna build and go build it with Python. That's where I would start if I were restarting. Sarah McBroom. Broom, we got some really cool last names in the house tonight. I don't know why I said tonight. It's morning my time. Okay. Can you please more and go in more in depth into working with recruiters, reaching out to agencies, finding recruiters and companies you wanna work for, the initial message or when to ask or ask when connecting. So I think this is really relevant to everybody, so I'm gonna answer it. And I'm gonna make a whole video on this, which I'll talk a lot about the things I'm about to tell you. So recruiters are hired from a company, typically hired from the company to go find people and bring them back. They don't wanna do all the grunt work themselves. They wanna just pay somebody to do it for them. So these recruiters are literally there to help you find a job. They don't take any of your, they don't take a cut from you, from your salary. It's not how it works. So how I would go about it is I would first reach out to all the local ones, hey, or just Google, local recruiters. If you live in the middle of nowhere and it happens, you're not near a metropolitan area, it's a lot of people, right? You may wanna look at remote opportunities and try to find recruiters for those companies. You can do that through LinkedIn. I have a video, how to get a job using LinkedIn. I show you how to find recruiters on LinkedIn for companies. Whether they're internal, which means they are on staff for that company and they're a recruiter, or they are external, which is they are working for a recruiting company for that company. You can find them on LinkedIn. You can personally message them. And I would just say something like, hey, I saw this position, you can include the link. I thought it'd be a really good fit. I have three years experience here and this. You know, I'd love to chat with you more about this position. Keep it super simple, include your resume, include a link. And then I would also see if you could find their email. I would follow up with an email. And if they have a phone number, call them. Now, this is what I did. And you don't have to do this. I'm not even gonna say I recommend it. I personally was on top of it. Like I was working with six or seven recruiters at any time and I was emailing them at least at a minimum once a week. At a minimum. That's what I was doing. I was relentless. I was ruthless. I had no experience. I didn't know what I was doing. So I just like, I was like, I know this is the path for me. I gotta get after it. So I was calling them once a week. I was emailing them once a week. Hey, do you have any new opportunities come in for data analyst positions? Hey, any new positions come in or at this company? They would often say no, but I would just every single week I had a reminder of my phone. I would email them or I'd call them every single week. So I was kind of relentless and probably annoying. I was probably annoying legitimately. But eventually somebody gave me a chance and I got a job and now I'm here, right? So like, you just gotta go for it. So the next thing you said, so that's reaching out to agencies cold call, cold email. Once you get that connection, once you have their number in their email, stay on top of them. You just have to, unless they're like, hey, we don't, there's nothing we can do for you. Don't keep hounding them. But if they're like, yeah, let's work together, then you stay on top, because they're working with 20, 30, 40 other people, right? You have to reach out to them. It's unfortunate, but you have to. And then, yeah, so you said, finding recruiters and companies you're gonna work for, that's on LinkedIn. Highly recommend LinkedIn. I've gotten jobs through LinkedIn just doing that. Yeah, so that's it. Julius, you can ask questions about data science. I'm not a data science expert, but I know enough. So I'll try to answer if I know anything. When are you gonna be posting your MySQL tutorial series, Michelle Boulds? That is, so I'm about to finish the pandas series in the next few weeks. Then we'll do the Python regular expression, Python web scraping, and then I'll start the MySQL. So, I don't know, probably two months. I'm sorry. Yeah, it's probably like two months away, because I do one video a week. But I will, I will get to it. For sure, by like the end of the year. We'll have most of that done. I'm sorry that you guys have to wait, but I just can't release like 30 videos at one time. Otherwise, then I'd be scrambling to get more videos, make more videos. Ashley Honda, this is a great question, because this is something I went through myself. I've been making Power BI dashboards for my job, but I can't add it to my portfolio due to client privacy. Is there a way I can add it to my portfolio now? I'm going to say this, and I do not want any legal repercussions of any kind. Anyone's watching this in the future. You cannot blame me for anything. This is purely your choice. Here's what I may have done or may not have done, potentially. I plead the fifth, but here's what may have occurred. I had dashboard, potentially. I may have had dashboards for clients that had personal data in it. I then took that data and put in Excel and de-identified it, which is taking away any personal information. So if they had an ID, home address, anything, I've replaced it with a placeholder, a randomized thing may have, and then rebuilt those dashboards with that fake data that's real, but de-identified, so you could never trace it back to a person, and then rebuilt them and then put them on a portfolio, potentially, maybe. I say all this because I don't know if that's legal or not, so it may or may not have happened. I don't know. I may or may not have done this, but most certainly, probably could have. That's what I would do, maybe. I don't know what I'm supposed to say in this situation. I don't know if that's legal, but I may have de-identified all the data and rebuilt the dashboards on my personal computer. I may have done that. Maybe. I plead the fifth. Vizid, I don't know. That was real, I was real sketchy on that one. I did my best answer the question. Vizid Shaikh, which one is good? Business analyst or data analyst? Both. Very good. Business analyst is just more business focused. You'll still use some SQL Excel, may most likely know visualization, whereas the data analysts will work more with data cleaning, transforming the data and product, but can still work with clients. But business analysts usually do more of the business side of things. Nguyen Du, do I? And a relevant question, how can you stream in high video quality? I'm using my Canon camera. So I have a Canon camera. I have a road mic up here. I have my lighting over here, and then obviously this stuff. This is a Canon camera. I use a Cam Link 4. And I use OBS as an open broadcast system. Then I connect it to my YouTube. Took me a long time to learn it. I used to do these with my webcam. They were garbage, but I did them because I love you guys. But now I'm trying to up my quality a little bit because I love you even more now. So yeah, that's how I do it. Let's see. Reading through more questions. Axel Alvardo, did Alex, what are the characteristics of your computer? Excel always freezes in my computer. I've worked with a ton of different computers. Tun-tun-tun. Usually it just has to do with the processing power or the memory. So if you have a really bad processor, like mine has, what is this one? A Ryzen 4000 Series 7. So it's a Ryzen 7. It's a pretty good processor. And then I have like a terabyte of hard drive, 16 gigabytes of RAM. I mean, that's really all you need to know. But yeah, it's the processor. But honestly though, if you're using Excel, if you don't even have a lot, if you have a massive amount of data, even my computer can be slow. Mine's a pretty good computer. It's like a gaming laptop. That's an HPM in 15 if you're curious. So I just, if you're just working with a crazy amount of data that can do it on almost any computer. But if you're working with a regular size, if you have even eight gigabytes of RAM and you're working with a regular size data that you should be fine. It's hard to say, you could just have like, there could be other things going on with your laptop other than that. Most computers should be able to handle Excel. Let's see. Christos, really glad to hear a man. He's studying, he's working hard. He's doing a great job. Keep it up. LuluSky, can you do a video on GitHub for portfolio? I already have. Go ahead and check that out. How to create a data analyst portfolio website for free. Yeah, I'm just looking. Looking for more questions. There's a lot of comments, but there's so many comments that I'm like, can't answer everyone. I'm sorry. Mahesh Babu said, I've completed your bootcamp. Also learned pandas, matplotlib, numpy, is it enough to get an entry level job? Now, what I'm about to say is somewhat controversial. I understand this. And people, you can clip this, put it on the TikToks, put it on the Twitters, whatever you want to do. If you have taken my entire bootcamp, you know enough to get an entry level job. In fact, if you have taken just my SQL stuff and Excel stuff, that's enough to get, and should be enough to get an entry level job. Here's the controversial part. Most companies, most companies, they just want more and they wanna pay you less. And most companies aren't doing you any favors. But for most entry level analyst jobs, if you know those things, you will be able to do your job well, right? You'll be able to get in there, learn their business practices. Honestly, a lot of these companies, they want you to hit the ground running, but they haven't created an onboarding system to help you hit the ground running. And most companies aren't ready to hear that, if I'm being honest. Most companies, they're just gonna plop you down and be like, all right, let's look at our database architecture. Here's where our database is. Here's our clients. And they're gonna teach you all this stuff anyways. You don't need to hit the ground running because they don't allow you to hit the ground running. It's like near impossible. They don't have an onboarding system. It's just not, most companies don't. So the fact that they are like, we want you to have all these things, every Python, all these things, like most likely they don't even use all of them. Most likely they're just using like basic SQL, or basic Excel. I'm getting on by my soapbox right here because I all of a sudden got angry about it. All right, most companies want, try to get down to the bottom. They want this, but they only use this. So realistically, you can get an entry level job. You can do an entry level job for a lot of companies with just my bootcamp, legitimately, 100% for real, on the real, real. So I don't know why I said that. But genuinely, most companies, they just want more even though they don't use it. It's ridiculous. I don't like that. I really don't like that. Thank you for listening to me on my soapbox here. I could, I can go off sometimes because some of these companies make me angry. They just make me angry. Is data now, Prem Shankar, is data analysis and data analytics the same? Yeah, they're basically the same. I don't really know what the difference would be. Data analysis is the process of doing data analysis where data analytics is like, is data analytics? I don't know how to just, I need to like look up definitions, but I'm pretty sure they're the same thing. I mean, I don't, another person's asking about my data analyst bootcamp. Is it useful to become a data analyst in India? I don't know if it's region specific, but those tools are pretty widespread. I've worked with data analysts in India, like through consulting companies who use these things. So I'm assuming yes, but I can't like for sure be like 100% yes. You learn this in India, you can get a job. But I'm just gonna assume yes. I really, I really do think so. I'm looking for more questions. Give me a second. Amit Verma, I wanna ask you one thing though. I'm aspiring to become a Power BI developer, very cool. I've learned Power BI and I'm making projects and learning Excel and SQL as well, that's good. What should be my next, what should be my next move should be? What should be your next move? The next move should be to be building really great, especially with a developer, really great data pipelines. Now you may not have thought I was gonna say that. You probably thought I was gonna say dashboards, didn't you? Power BI developers, and I've worked with many myself, they actually usually work with the flow of data as well. So making connections from Power BI to data sources, automating that process. You need to start looking at automation. That is actually a very key skill rather than just building the dashboard, that's important. But automating that is even more important. In my manager position that I left in December, that's what I had just implemented. It was a self-service Power BI system that we were using in all of our IT, or for a lot of our IT places. That's what I'd be learning, how to automate things in Power BI. I got this thing on my list, really annoying me. Hey, Alex, where are you from? I'm from Charleston, South Carolina. Right on the beautiful, beautiful beaches, the Atlantic Ocean. Don't fact check me on that. Hi, did you see the Atlantic? I'm gonna sound real dumb if I'm wrong. Yeah, yeah, the North Atlantic, right guys? We all knew that. I was about to feel real dumb. I was like, is it the Pacific? No, the Atlantic. Is it? Pretty sure that map was accurate. Don't fact check me on these things. All right, I'm a data analyst. I'm not a geographist. Anywho, yes, South Carolina. I was living in Dallas, Texas, but the man, it was too hot there for me. Sonny Ahmed said, what topics of SQL do I need to get a data analyst job? I would know everything up until joins really well. Like select, from, where, group by, order by, joins. Need to know those really good. Those are like the nuts and bolts of getting a technical interview. Then if you wanna go above and beyond, which I recommend is learning things like window functions, really good to know. Case statements, you can even go more advanced. There's a lot more advanced things out there. But if you know that, really good. Like you practice with it, you know it. That's good. That's what you should know. Let me see. What time is it? Am I? 1130. All right guys, we've been going for almost an hour. I'm gonna go a little longer. And we'll just see if there's a natural stopping point. Oh, this is an interesting question. Nobody ever asked me about me. Suki. Suki, Suki? Hey Alex, tell us about your new company. Sure, I'll tell you about my new company. My company is Alex Analytics LLC. And basically what I do is I consult with companies for a lot of different things. Sometimes I'm helping integrate tools. Sometimes I'm doing product. You know, for example, there's no company in specific but there's a company that wants to create this new data analytics product. Maybe it's on the data visualization side, could be. And they're like, hey, we're launching this product. We wanna know about market fits. Any recommendations you have with the UX UI? Because I've worked with a lot of these products. Functionality, any functionality that they should be adding for their initial product. I come in, I look at all these things and I help with that. Sometimes I'm helping do real data analyst work so that I'm doing, you know, they're like, hey, we, and I mostly do it with healthcare companies. So that's my specialty. Is a healthcare company be like, hey, we're not understanding this. And I'm like, okay, I know that data really well. Let me come in, let me take a look at it. And then I make recommendations on what they should be doing. I do a little bit of analysis and then I give that back to them. Now I have another part of the company that's gonna be launching soon, just called Analyst Builder. Where I'm building a website that is gonna be, in my opinion, phenomenal. It's gonna be one of the best data analytics websites to learn to become a data analyst out there. It's gonna start small and it's gonna build big. And I'm massively excited about it. Like it's been like a year in the making, it's gonna be really good. So that's my company. But it's gone really well right now, really well so far. It's been great. Let me see. Hmm. Oh, I was not even on my keypad. Let me see. Oh, this is a great question. Battle of Benassi, Ben-Sassi. Ben-Sassi? I'm sorry, I keep trying to pronounce your name, but I get it wrong, I'm sure of it. How long does it take to move from a junior data analyst to a senior data analyst and what needed qualifications generally to move upwards? Great question. I haven't answered that one in many streams actually. That's a really good question. So you start as a junior data analyst like you're just learning the basics, right? You're starting to understand how the company works. You're understanding their databases and how they're doing their visualizations, what their clients, who their clients are and what they need. You're getting introduced to the clients. That's what a junior data analyst does. That can last for about a year, two years tops. You should not be a junior, that's like a junior data analyst like a year to a year and a half typically. Then you ask, I'd like a raise because you're no longer a junior data analyst. That's like junior stuff. Now you're like, you've taken on your own clients, you've taken on your own stakeholders and you're working with them a lot. Then after two years, if you're not being promoted, you go to a different company. If you ask and they say, no, you're still a junior data analyst, that's bogus. You go to a different company, two years tops. Two years to about four years is like mid-level. It can be longer depending on your skill level. Now what gets you to that next level? What gets you there is your technical abilities and your business acumen and your domain knowledge. So how well are you working with clients? Are you solving their problems well? Are you understanding the technical side of things? Are you working with their databases well? Are you working with their visualization software well? Like, are you learning these things? Like, do you know them now? Then business acumen, are you working with the business and you're understanding their domain knowledge and their needs and you're understanding it? Once you know those basics, if you've got those down, you're no longer entry level. Now you're starting to get into the mid-level. Mid-level is where you started having all these things, your own clients, you're working with the stuff better and you're mid-level. That can last for a while. That can be two years to five years of experience, right? Or maybe even a little longer depending on the industry or industry standards for that industry. But I progressed extremely quickly. I'll tell you how I did that. And what I think people should do are just helpful advice. Because I went from a junior data analyst to a data analytics manager within five years. So that's like a crazy fast career trajectory, much faster than anybody I've seen. Not trying to pat myself on the back, it's just that I tried to do that, but I went like, I'm doing some funky stuff today. Not trying to pat myself on the back here. It was a crazy fast trajectory. Now really what I think it was was I really socialized well, so office politics. I really socialized well. I also did a phenomenal... Again, not trying to pat myself on the back. This is feedback that I got from my bosses or other people. I did a phenomenal job working with clients, managing expectations, getting the work I needed done. And then I really went above and beyond. I was thinking of ways to automate. I was creating SQL scripts, Python scripts that would automate some of our work so I could be done faster. And they had never done that before. So I was doing things and trying things and working harder than I... I don't wanna say I was working even harder. That's not true. Everyone was working hard. But I was doing things that would save the company time and money. And that made an impact. And I was... I also had some domain knowledge that other people didn't have, which came in handy, which led to my first promotion. But I think it's just making an impact, helping your clients or your stakeholders really well, getting to know the people you're working with, the bosses, the managers. That really helped me progress quickly. I would say that really, really helped. You're right. My screen is kind of not super bright. That was just a offshoot. Let's see. Looking for more questions. Matthew Alderman, what is this? It says, member for seven months, ATA superfan, that's what's up. But then it says, I got a promotion, business info manager. Yeah, I read that earlier. I'm confused. I mean, congratulations. I just, I thought I read that earlier. And now it's big and green on here. Holy mackerel. I am so far behind in questions. I just looked ahead. Oh my gosh. I mean, there's like two... There's gotta be like 500 questions here, or like comments and questions I haven't even seen. I am so sorry. Geez, what am I doing? I'm so sorry, guys. That just blew my mind. I'm way behind. I'm so sorry. Okay, this is Patrick. I see it in green, so it popped out to me. He said, is there real value in learning one type of product, such as Salesforce, or is it just better to focus on the underlying skills? That's a great question. I haven't answered that one before, I don't think. There definitely is value to that. And let me give you an example. In the last company I worked, the company I quit to start my own stuff, we use something called, not Salesforce, ServiceNow, a Microsoft product called ServiceNow. There's a whole ecosystem around ServiceNow, ServiceNow analysts, ServiceNow developers, ServiceNow engineers, whole ecosystem. Salesforce is the exact same way. So you can build an entire career on just Salesforce, 100%. You become a Salesforce consultant for data analytics. Legitimately, there's a bunch of products like that. So yeah, you can do it, but I mean, it really puts all your eggs in one basket, right? Because if Salesforce makes a change, or if Salesforce does something, goes out of business, they're not, but imagine that they did, you're putting all your eggs in one basket, it's just a little risky. Dr. Majeed asked a good question. How to choose the business domain to work as a data analyst? A business domain that helps me to be more of an expert in the field. So I worked with someone, they were a mentee of mine, and really quickly, I'm not offering mentorships at the moment, since I started my company, I had to stop doing that so I could build my company. I'm gonna start doing mentorships, hopefully in 2024. That is my goal, okay? I'm gonna try to do that again, so I really loved it, I really loved it. But one of my mentees, he had no domain experience and no nothing, and he's like, what do I do? And so here's what I told him and then he'll tell you what he did. I said, what you really need to do is like, just get some experience, it doesn't matter where, or what industry, you need experience, somewhere. Because then once you have like a year's experience, then your options, it's like a flower, it goes from this little tiny, little nugget of opportunity to just this huge range of opportunity. Once you even have one year experience of a data analyst, it's 10 times a year to get a job, 10 times. It's just that initial barrier is tough to crack. And I said, just get experience. So that's what he did, he went for a year, got experience. And then I was like, what do you wanna do? He's like, I don't know, I still don't know. He's like, I was working with like supply chain and I was like, okay, did you enjoy it? He's like, no, not really. I said, well, try something else. So he goes and he tries something else, which was in manufacturing. And he's like, did you like that? He's like, no. I was like, okay. So you have experience now, but now you have to, I was like, here's the dilemma. And this is very real, 100% real. I want people to be thinking about this as they progress in their data analyst career. I don't think I've talked about this a lot, but think about it like this. If you have domain experience and if you don't have domain experience, let me give you these two examples. Let's say you have no domain experience, you get an entry level job at some industry, then you hop around for a year, a different industry, then a different industry, different industry, different industry, different industry. You're 10 years into your job and you have been in 10 different industries, that hyperbole, right? It's a dramatization. It's not a real, most people won't do that. You have 10 years where you have different industries. Then you have this guy over here, this is Joe Bob, Joe Bob. And he gets into one industry and he stays in, let's say healthcare for 10 years. Now both of them has 10 years experience, one in healthcare, one roundabout. Both of them wants to be making a lot of money and both of them want a good solid job, senior level or above. Here's the problem with the guy, try to make sure I'm on screen. Here's the problem with the guy who got 10 years of experience. A company wanting to hire a senior level data analyst is not just looking at technical skills, which this guy may have. They want business acumen and domain experience because they are expecting a certain quality of a certain level of expertise for their domain. So then they're gonna be like, hey, we're not looking for that. You only have a year's experience in our area. We need somebody who's been doing this for a long time, knows the ins and the outs and everything. This guy over here, he is more narrow in healthcare, but he is gonna get a job 10 times faster and he's gonna get paid twice as much because he has a domain. Now, how do you choose a domain? That's really what you were asking, but I'll get back to that in a second. But choosing a domain, at least within the first, after about three years, you need to start choosing a domain because once you start getting mid-level senior level roles, they expect certain levels of experience in their domain. Now, some companies don't care about that, like consulting, sometimes they don't care about that. That's just my experience. I have seen it, it's tough to get out of. Then you're kind of in this whole, like nobody really wants to hire you at a senior level. They're like, well, hire you at a mid-level, but you don't have the domain experience. So domain is important. How do you choose? You kind of do what my mentee did, which is you try different things. What interests you? What's interesting? Eventually, he found what he liked and now he's been doing it for over a year now and he just messaged me a couple months ago and he's like, I'm doing great. I love it. I think I'm gonna stay in this industry. And so now I'm hoping he stays on that for three, four, five years. He gets paid double what he's getting paid now. Very, very possible. So I went off on a tangent, but there you go. All right, it's 11.40. I'm gonna do about maybe 10 more minutes. And then I'll stop and I need to grab lunch because it's almost lunchtime here. Let's see. Where's my data analyst mug? It's right over here. I'm wearing pants. I'm not one of those streamers that like, only wears a shirt and then they get up and they're like wearing underwear. How awkward. This says, trust me, I'm an analyst. Now I used to sell these. These are now a collector's item. I used to sell these and now I just drink out of this. But I didn't really like the idea of selling those like physical products, like t-shirts and stuff. They were super cool. So if you have it, you're like some of the few people. But I did that when I was like first starting out. I didn't really know exactly what I was doing with the channel. And so I was like, let me try doing coffee mugs. And I actually really love this mug. It's super cool. And I sold a bunch of them. Then I was like, it's really on brand for me. I was like, I don't really wanna be pushing like coffee mugs and t-shirts. When I launched my full, my website with, that'll have full courses on, those I can like recommend. And I won't feel bad about selling. That's where the analyst mug is. That's a real fan right there. Cause that's a real fan. How'd you know about this mug? That's an OG right there. That's a batter of Ben Sassi. You know, Ben Sassi is an OG over here. How can you connect with me? You can connect with me on a lot of different places. LinkedIn is the best place. I respond almost every, all those messages most of the time, but I get a lot. Sometimes it takes me a while. Twitter, Instagram, email. Those are like the best ways to connect with me. Let's see. Is Excel important as a data analyst? Yes. Kego, Kego, Kago, Kego. Yes, it is important. I don't care what anybody tells you. Excel is not even remotely close to dead and every single business use it in a lot of ways. Yes, very important. Green Coyote Bay, excuse me, I was burping. How important is linear regression in your day-to-day work? It wasn't at all. In fact, I didn't almost, I did a little bit of linear regression. I was working on my data science team, but the data scientists that I was working with mostly used that. They mostly worked with the linear regression. So I didn't use that a ton. I did work with them. So like, I understand it pretty well and I'll probably do some lessons on that in the future, but I didn't do a ton of it, if I'm being honest. I worked more heavily in like the data collection side. So creating the data pipelines, data cleaning, stuff like that. And then a little bit visualization as well. Benji or Benji said market seems rough currently. Have you heard about when things might clear up for us new analysts? No, not really. I keep pretty close ties. I got my fingers kind of in the market, at least in the US at least. At least in the US at least, that was redundant. But I haven't heard much about it picking up. Mostly in the tech companies, it's like, just kind of, it's its normal thing. Some companies are hiring. Some companies aren't. They have like hiring freezes. It's kind of weird in the tech space right now. I never base hiring based off of that. Almost every other company that I know that I've worked with are hiring exactly as normal. So data analysts are hiring as normal. There's nothing changed for them. But at tech companies, it's slowed down. But most people aren't gonna start at tech companies. We're 12 hours apart. Oh geez, it's like midnight there. Get some rest. Goodness gracious. Have I used VBAs and macros? Yes. And they're good to know. I don't think they're a must have like right away. But I think it's definitely worth knowing like when you start getting into it. Oh, this is, I mean, this is something that a lot of people ask, which is a good question. Arendam Naha. Hey Alex, is it possible to be a data analyst without learning Python? Absolutely. In fact, I put Python, you guys may not know this. I almost started a Python only channel. Instead of an Alex the Analyst channel, where I was focusing on analytics as a whole. I almost started a channel called like Python Masters or something, something stupid. Because I love Python. With that being said, I only knew SQL and Excel when I first became a data analyst. Then I learned SQL, Tableau and Excel in my first job. Then in my next job, I learned Power BI. Then when I, and Azure in the big company. Then I taught myself Python and I started using Python in my job and they never even used Python in that job. I just asked, can I use Python? Cause I have this idea to automate some stuff. Can I use it? And they were like, yeah, go ahead. So they didn't ever use Python. So Python is not a requirement by any means. In fact, I would focus mostly on SQL, Excel and like Tableau or Power BI right initially. That can get you a job just by itself. Python is not a requirement. Definitely not. I just love Python. I love making tutorials on them. I love making projects on them. Love it. So no, not needed. Is exploratory data, Nasir Sudhir said is exploratory data analysis and data wrangling more than enough to become a data analyst? I can be. Exploratory data analysis is useful, very helpful. You need to do it. I would say data cleaning is actually more useful cause it's just much more complex. It's so complex data cleaning. But data wrangling can be also complex. Exploratory data analysis is not like crazy hard in my opinion. I always thought that to be the easier part of the job. That's just my opinion now. Let me answer a few more questions. We're gonna do like maybe four to five questions. And then I'm gonna have to sign off cause I gotta eat. I've just been drinking water. I don't even know how I had breakfast. All right, do you prefer Power BI or Tableau? Personally, I think Power BI is far better. I personally like Power BI better, but Tableau is more widespread and I think easier to learn. That's why I usually tell people to learn Tableau. They also have Tableau Public, which is just fantastic to learn on. And you can share your portfolio projects easier. So that's usually why I recommend Tableau first. But I personally like Power BI better, if that makes sense. This is a good topic. Fish regulator, I've been a data analyst for two years now and all I do is SQL and Excel reports. Is this normal? You know, every company is very different. It's actually pretty funny how different they can be. What they do as a for a data analyst or what they're supposed to do. Here's what I'll say. Smaller companies typically, and then much larger companies. Have you doing very different work? Large companies have you doing a very specific thing. So looking at what you're talking about, maybe you're working at a big company and all they want you to do, as for your role as a data analyst, is work on reports and SQL and Excel. But another data analyst next to you, they're working on the data cleaning and another data analyst, they're working on the visualizations, who knows. Every company is very different. So in terms of normal, that's actually can be normal at a lot of companies. We're just working on SQL and Excel reports. Maybe a little client work and stuff like that. But yeah, it can be normal. I can't say I've worked on a job exactly like that, but yeah, definitely can be normal. Have lunch with us. Alicia, I would love to, but I'd rather not eat on camera if I'm being honest. I don't, my wife has been very honest with me in that. I eat very loud and aggressive. I'm just kidding, I'm just messing with you. I just eat loud apparently. So I'm like, I don't want to do that. Let me see. I'm gonna answer just a few more questions. Aditya Jane, she probably did what, I'm guessing you weren't here before. I guess Aditya, sounds like a girl's name but I can't. So I'm not trying to make fun of anybody. But that person asked, what are your thoughts on how data slash finance analyst jobs will change as AI slash chat GPT comes more mainstream. I said it earlier, I'm gonna give you a super condensed version for people who weren't there at the very beginning, which is probably a lot of people. I think AI is making some huge advancements. I've been, I've kept my hand very close to like the latest advancements in AI because of how much I care about this community. Like I don't want to lead you astray. If I see like data analysts being automated, I'm going to tell you because I think it's really important. I don't want people to get into this field if it was going to be automated. I have deep dived into AI and data analytics. And again, I'm going to try to give you a condensed version. Data analytics has been tried to be automated for a long time and pieces of it has. And this is even before I became a data analyst six years ago, there's certain parts being automated where we take the data and for information, create dashboards based off what you thought, then you had to go and tweak it, change it, yada, yada, yada. With ChatGPT, it's different, right? It's more advanced, can give you more customized stuff. But with that being said, I have seen, I've been looking at all the latest stuff with auto GPT, baby GPT, seeing what it can do, seeing the presentations that Greg and Sam and all the people at Open and Air putting on that even have highlighted some data analyst stuff like creating a dashboard in Python. And it's great, but I, working as a data analyst, I have, I know the intricacies of it very well. How complex it can be, how much you have to work with the customer and the client, work with data engineering teams to really get things right. Business, understanding the business issues, how you're going to clean the data for a specific issue or for specific products, for specific report, et cetera. AI I think is going to help with those things. I think it's going to be a great tool. I think there are actually too many intricacies and too much human level needed intervention to ever fully automate. That being said, 10 years down the road, we could be looking at a totally different chat GPT. I'm sure we will. That would make, need to make huge advancements in a lot of different areas in my opinion, right? I will be following this closely as it progresses. I really will. But right now I just see it as a tool and it's not even like, the more I use it, it's not like, yeah, the more I use it, the more I'm like, okay, there's a lot of limitations to this because I keep using it and I keep running into a lot of issues. And so I think the more we use it, the more we'll realize there's a lot more limitations than we think. There's also a lot of ethical concerns with using AI and companies, legal concerns with using AI and companies with data privacy and all these things. And there's a lot more that's taking place than just can it do your job. There's already programs besides chat GPT can do parts of data analytics. It already can do that stuff. But data analysts aren't automated just because there's so many nuances to data analytics. I ended up going longer on that question than I was hoping, but no, my overall thoughts is it's not gonna, there need to be some crazy, much more complex, very specific to data analytics advancements or auto GPT or baby GPT in creating these agents to do this work. I just, I think it's too complex as of right now. There's so many issues that I already have worked through myself or can see it working through for it needed to be to happen, in my opinion. My opinion. All right, last question, let's see. Well, this isn't my last question actually because this is a really quick one. Diana Valencia said, when will you start your mentorships again? How long will the mentorship be? I had done mentorships for the past two years. I stopped in December. Oh no, I did like two and a half years. I stopped in December when I started my company to devote all my time to building the company. I'm hoping to do mentorships again in 2024 or even changing it to doing some type of cohort where I take on like 20 at a time. Let me tell you, I absolutely love the mentor and keep it really cheap. My goal is to keep it really cheap. I never felt good about trying to make a lot of money for mentoring. I just thought it was like me giving back but I couldn't justify 10 hours a week for free when I'm already doing YouTube business and everything. So I'm hoping to maybe do something like a cohort where I'm taking like 20 people in for a six week time and doing that and really making that work and trying to keep it pretty cheap. I am never gonna create a data analyst bootcamp where it's like 10 grand or even $1,000. That's way too much money. When I was first starting out, now I'm going off on a tangent. When I was first starting out, I had no money. I had like 500 bucks to my name and I just took courses on like you to me. And so like when I think back, I was like, I don't, I could not imagine myself even paying like $500 for a mentorship for six weeks. I just couldn't justify it. I didn't have the money. I am going to try, I have a ton of ideas for the future. And my website that I'm launching in maybe like two months is going to be a big hub for that. Like it's gonna be what I believe is a fantastic website for data analysts. I think it's gonna be amazing. And I'm gonna add to it. And the cohort idea is gonna be part of that I believe. And so yeah, I hope to do mentorships or some type of cohort in 2024. So in like six months time, eight months time. That's April. That's my idea right now. We'll see how it transforms over the next time. All right, one more question. I went way too far on that. Whoa, whoa, whoa. Then Saasi, hold yourself. He said, don't forget the vegetable of the week or the live before leaving for lunch. That is not part of my live stream, my friend. That is part of my podcast series, my Alex the Analyst show. Then Saasi's mixing things up over here. Now I'm really questioning his devotion to the channel. Just messing. No, I won't do it for the live streams. I'll do that for like my long podcast which I'm gonna have one coming up on my thoughts on AI, data analytics, everything that we've talked about going a lot more in depth into it. Cause I've done way too much research on this. More than anybody should have had to. But I did it for you guys. Let me, I'm trying to find one more. One more, very last question. Oh, this is an interesting one. I'll kind of take it in a few different directions. Leanna Youssef said, would you suggest starting working at a small company or a big one where there are mentors to help us? This is very biased because this is what I did. But now I've worked at a very small company with under 50 people and I worked there for over a year and then I worked at a very big company. That was like, oh, tens of thousands. It was like 40,000 people worked at the company. So I've worked at both. In my opinion, I would prefer working at a smaller, like if I were to start over, I would rather work at a small company because I learned so much there. I learned how to really do everything out of the whole spectrum of data analytics stuff. When I worked at the large company, I was solely working on data collection. That became like my specialty. I branched out when I worked in there a little bit, but that was what I was hired for. Now, as I had got different skills, different stuff, I branched out, but I didn't learn as much, I would say, than when that first year as a data analyst at a small company, I learned so, so much and I had a mentor there as my boss. So if you can get a small company and a boss, I think that's amazing. If you can get a big company and a good boss, that's amazing too. There's no one right answer. I just personally learned more from the small company because I had to do so much more. Like I had a lot more responsibilities just on me, whereas when I was on a larger team at a bigger company, you could kind of offload. Everyone kind of had their thing they did and I didn't have to do everything. So it was easier, but I didn't learn as much. That's my opinion. Noe Berientos, hey Alex, did you partner with Apprentice? I saw a video about it on TikTok. Yeah, I did. I made a Python course for them, but then they charged more than what we agreed on. I wasn't happy about that. So I don't promote it. But I did create a course as a fantastic course. It's one of the best things I've ever made, but I'm not promoting it because of that. I still like the company, nothing against them. I don't want to get sued. But I just, I'm not promoting the product because they are charging way more than I wanted them to and what we agreed on when we first started. But I'm gonna release my own Python course. That's gonna be like a fourth of the cost and it's gonna be better than the one I created for them. And that's gonna come out in like two months. So if you're wanting to learn Python, I'm gonna, I have a better course coming out that's gonna be four data analysts. It's legitimately really good. So don't go and get that one for like, it was like, they charged like 200 bucks. I wasn't happy about that. I was not happy about that. Because initially we agreed on 50. I was like, I can justify 50. 200, I cannot justify, not from my audience. So I ended up not pushing it hard. All right, yeah, that's, I don't wanna land on that one. Jeff, what's the podcast name again? Jeff is asking that, I don't have a different podcast. It's a playlist on my channel called Alex the Analyst Show where it's long form and I talk, where not a lot of my other videos are long form. But it's long form when I talk. I have a lot of really great topics that I just, I give my opinions on and I dive really deep into them. And I like doing that because then I can just talk and I don't have to like cut it all down into like 10 minutes. I can keep it like 15 minutes. So go check it out if you want. I see a lot of other stuff in, okay. Oh, this is the last question I'll answer. And it's related to a career foundry. It says, hi, Alex, would you please give me your honest opinion about career foundry, please? Now, you see those. Let's think about this annoying. Now I've been doing webinars with this company called Career Foundry. They do data analysts, boot camps, UX UI boot camps. They do boot camps. Typically I'm against boot camps. They're very, very, very few that I even slightly endorse or even slightly think are good. Career Foundry is one of them. And I reviewed their product, I actually liked it. They have mentorships, they have a job guarantee and they have a good curriculum. And the kicker is it's one of the most affordable boot camps on the market. So I prefaced this by saying, I'm not a huge boot camp fan. There are very few or very, there's a narrow reasons why you should be taking a boot camp. But if you are looking for a boot camp, Career Foundry is actually a fairly good one. And I like their mentorship aspect the most. They have two mentors. You get a mentor for when you're learning the curriculum, when you're learning the skills and then you get a mentor for applying jobs to help you find jobs. Because again, they have a job guarantee. If you don't get a job, you get your money back. So they have a big incentive. And of course they're like, you have to apply to a certain amount of jobs. You have to be willing to take a job if offered, et cetera. There are stipulations of course, there are like a business. But Career Foundry is one of the few that I actually like somewhat endorse. That's what I'll say. But as a whole, I don't love the idea of boot camps because most are fairly predatory. They'll charge like 15 grand. They offer you some mentorship. They teach you the basics. Like, last thing, what I teach you in my boot camp for free is what a lot of boot camps charge like 10 grand for. And then you get to see a mentor like once a week. So you're paying like 10 grand for a mentor essentially. And it's predatory. I don't like it. It's mostly a scam. But Career Foundry is not like that. They charge like, it's like $5,000, which is still a lot of money. It really is. But if you don't get a job, you get your money back. And that's what I like. If they don't have a job guarantee, I would never do a boot camp. So that's my honest opinion on it. I'm not endorsed by them. They're not paying me to say that. One other thing, I'm going to go on a tiny tangent at the very end. I only take sponsors on the channel if I like their product. I get sponsors, like I have gotten three emails today this morning of people wanting me to push some of their products. I say no to like 99.9% of them because I'm like, I don't like it. It's too expensive. My audience wouldn't like it. I am extremely selective. So like, if I have any, like Coursera is one that I recommend. Udemy is one that I recommend. And I only partner with Career Foundry because they offer a good price, a job guarantee, they have a good curriculum. I looked at myself, they do mentorship. One of the few that I actually liked, one of the few. So yeah, that's my review. With that being said, thank you guys so much for joining. I absolutely love doing these. Thank you so much to everyone who has joined the channel to become a member. You know, that like really means a lot to me. Like your support means a lot to me. I have some absolutely huge, huge, huge stuff coming out. Like in the next two months, Analyst Builder, in my opinion, is gonna become one of the biggest things in analytics as we build it out. At the beginning, it's gonna be amazing. Crazy excited for it. So I have some huge stuff coming and your support like really makes all the difference. Like I get energized from you guys and doing stuff like this and like you guys are why I do this. And so thank you guys so much for joining. I'm gonna leave it at that. We get a little sip here. But thank you guys so much for joining. There's a lot of people today. This is more, this may be one of the larger live streams that we've done. Usually I have like 200 people. There's like 370 at one point. So thank you guys so much for joining. If you have any other questions, hit me up on LinkedIn. That's probably the best place to reach me if I'm being honest. Twitter, if you tweet at me, I'll respond but I don't respond to DMs because I just get like way too many. Like I have like a thousand in my inbox that I haven't looked at because it's so overwhelming. I get so many. So Twitter, don't DM me at me and I'll try to respond. Instagram is also pretty good for reaching me. Email, my email is getting a huge backlog. I have like 1200 emails in my backlog. So email is starting to become not a great place to reach me. The LinkedIn is. All right guys, I am out of here. I gotta go get some lunch. I'm probably having leftovers. We have some leftover quesadillas. They were beef and cheese quesadillas and I'm gonna put some jalapenos on them. Maybe some grapes on the side if Christine bought some grapes. Not important, but I thought you'd like to know what I was leaving you guys for. But thank you guys. All right, I am heading out of here. You guys are wonderful, fantastic questions today. Really great questions. I'll be doing more, I have one each month. I do that for my members and for all of you but my members are like, how am I able to do this? But thank you guys, genuinely. And I appreciate you. I really, really, really do appreciate you guys. You guys have changed my life, for real. Just search Alex Freeberg on LinkedIn. I see someone asking how to find me. Alex Freeberg, Alex the Analyst, you'll find me. You'll find me, I'm on there. What do I think about the Mandalorian season finale? Haven't watched it yet. I'll be watching that tonight, no spoilers. All right guys, I'm out of here, bye guys. All right, where am I going? What am I doing? I gotta stop.