Hello, hello, can anybody hear me? If you can hear me, let me know, because I have no idea if this audio is working or not. But cool, well, we're gonna get started. Oh, awesome, what's going on, Vincent? Cool, well, this is, I love being here, I love doing this, I love seeing everybody, looking forward to lots of good questions. As you can see, my house is about as festive as it can possibly be. I got my Christmas tree, got some Christmas presents down here. This is obviously something I just threw on cause I thought it'd be fun. And so just gonna keep it pretty chill. I pulled out this nice Christmas sweater out of my closet that I have not worn in a long time, but I fully plan on wearing it during the Christmas season. But cool. Well, as we get started, y'all start asking questions, start putting it in the chat. We'll keep it pretty chill, answer some questions, just so you know. Questions do not have to be data analyst focused. If you wanna ask me questions about, my time management, or what I like to, my favorite hobbies, I'm an open book, this is an AMA. So normally I do Q&As, which are typically really data analyst focused. So, what do I recommend here? What do I recommend there? But if you wanna ask personal things too, as long as they're within the realm of being reasonable, I will absolutely answer that. Cool. So hey everybody, I see some people joining, some people messaging in the chat. Very good to see you guys. But window, magic window starting it off, can we analyze the COVID data set? There's lots of COVID data sets out there. I've seen a lot. And all of them have a little bit of different data. So yeah, I mean, there's lots of people doing time series data, data analysis on the COVID stuff. Super cool. I haven't touched on that, that's not really, I didn't really jump on that bandwagon too much. But you can absolutely do the any type of COVID data set for sure. What's going on? I see more people joining. I see people putting in the chat. What's going on? Ask me questions. Oh, it's getting blurry. Let me see if we can focus. But yeah, start asking questions. Like I said, does not have to be data analyst focused if you wanna ask me something personal. Anything like that, we'll keep it cool. So can I suggest some projects on data analysis for absolute beginners? That's from Petham, Profam. I don't know if I pronounced that correctly, but I apologize if I didn't. Yeah, so some projects, I absolutely wanna come up with some videos for that because a lot of people ask me that. What I try to think about is, as a project as a whole, what are you trying to communicate? And something that I think a lot of people should be trying to communicate is not just that you know the skill, but you know the business reason for that skill. And so if you're doing a sequel, for example, sequel's a big one that a lot of people wanna do projects on, but they don't know how. And so one thing that I will say is try to do something where you're ingesting data, something like the ETL process. You show that you know how to clean the data and load that data into tables. That could be a whole project in and of itself. It could be as simple or as difficult as you want it to be. And trust me, it can get very, very difficult on that side. You can do also an entire project on exploratory data analysis where you're creating queries and you're looking into the data. And then, there's a lot that you can do with that. And so I don't have any specific projects at the moment because I'm actually coming up with ideas for videos for that. But just try to think along the lines of how can you can show the lifecycle of data within your queries and then you can show that and that'd be definitely help with the project creation. Some other questions from Yash, much love from India, much love from the States, man. Glad to have you on. Very cool. Required skills to become a good data analyst. I mean, there's a lot of skills. There's a lot of skills that you can have. I genuinely do think that the biggest staples that you should be focusing on at the right at the beginning are SQL, Excel, Tableau. And if you're able, and if you're willing to do that, Python, you don't have to do Python because it can be a little bit more difficult, a little bit more time-intensive. But trust me, Python to me has been the biggest thing that's gotten me to like the next level as a data analyst. Or you don't have to do Tableau, you can do Power BI or some other visualization tool. But those are like the staples. And there's a lot of other tools that you can use, a lot of other things that you can use. Those are just the ones that I really highly recommend. Did you learn everything just from open sources and online courses? The answer is mostly yes, but also I learned a lot of my job. So when I was first starting out, I learned everything through courses. I just looked up, I found Udemy. I didn't even know what Udemy was before I took my first SQL course. I just typed in SQL courses online and Udemy came up. I took a course. I became addicted to them. I started taking courses on everything data now. If it had data analysis in the title, I just took it. And I kind of figured it out. Once I got into an actual job, that's why I think I learned the most because hands-on learning is something that I really, really value. But before I got my first job, yes, it was only self-learning. I had no formal education, never did a boot camp or anything like that. So 100% online learning is how I kind of made my way, I guess you could say. Oh gosh, it's doing this thing where I skip down to the bottom.  So let me scroll back up real quick. So Magic wanted to say, can you please share some data sets also in your vlogs? I don't do vlogs. I guess mine is more like a podcast show style if that's what you're talking about. But yeah, data sets, I'll think about it. I'll see what I can do. Let's see, Archer asks, did you feel like you were treated differently when you first started your data analyst career because you didn't have a relevant degree? No, not really. Because honestly, nobody asked me what my degree was and I didn't openly like share that. I wasn't like, hey guys, this is my degree. I just kind of went about my business and did a good job. And so no, I don't think anyone ever treated me differently. I think I got treated very well. I've worked with a lot of good coworkers. So yeah, no, never been treated poorly because of that. Ideal pathway of a RIAd, Araya asked, what's the ideal pathway of a data analyst? I have an entire video on that. So I'm not gonna get too much into it, but learning the skills, create a good resume, work with a recruiter and then get a job. But I have a whole video on how to do all of those things. So check that out if you're really curious. Let's see. All right. So Christina says, I've been thinking about a career in data analysis. I'm two years into my math degree. Should I change to computer science? I can give advice on that, that's a super big question. I really think that computer science is probably the best degree to get if you're going into anything that's kind of technical, computer-wise. So if you're doing data science, data analysis, data engineering, data architecture, all those things you can do or you can pursue with a data science degree. Whereas a math degree might be a little bit more limited on the data side of things. So if you're really focused on going in the data side of things, computer science might be a fantastic choice for you. It's just, I don't wanna tell you to make a huge change in your degree and you're not like that down the road. Definitely a very personal decision. Magic asks, Magic Windows says, Tableau versus Power BI, what's your opinion? Tableau I think is better for beginners. And I also think it is better for people who are trying to learn. And so that's why I always recommend Tableau to people. I use Power BI at my job. So I mean, I like it. I think it's really good. I think it's a little bit more advanced. And I think it has a larger learning curve, in my opinion. It does almost a lot of the same things, maybe a little stuff extra. But Tableau is amazing and it's free. And so, can't really beat it, it's pretty awesome. Rahul, I see your questions, I don't really understand them if you want to try to type them out in a different way, I guess. We'll see. And your reg, I always say that wrong. I see you all the time, I just don't know how to pronounce your name. It says I'm getting trouble learning the logics and getting the answers in SQL and basics, maybe intermittent to logics, to answer the questions, how to practice that. Leak code has very problems. So I think what you're trying to say is you're trying to learn SQL, you're trying to learn the basics, you're having trouble, and then the leak code questions are really hard. I wouldn't go straight to leak code, leak code is pretty hard. The easy is intermediate in my mind, the medium is a little bit hard, and then the hard is like really hard for most people. And so I would not go straight to leak code, there's lots of other options out there, just type in like SQL interview question website, and there definitely will be some that come up. But it's just putting in time, effort, practice, and then finding those interview questions that you're looking for. So Brian asks, what advice can you give to a new developer having difficulty passing interviews and getting an offer? Well, I'm not a developer, I'm a data analyst, but my biggest tip on passing interviews, especially technical questions are practicing a ton, especially on the things that you know they're gonna ask about. So for me, I didn't realize that SQL was such an important thing to know for technical questions, but apparently it was, and so once I knew that, I just like studied, studied, studied to make sure that I knew everything about SQL. And so, make sure that you know what they're gonna be asking about and study those things. Again, I didn't really know SQL joins when I first started that kind of stuff. They're like the really basics, the basics that you have to know. And that's what a lot of technical questions are on, they're on problem solving skills and technical skills and stuff like that. So I'd focus on that. Quran says, I have no data and analyst degree, but work as data analyst in the big four companies in India, can I get opportunity outside of India on data analyst role? You know, a lot of people ask me questions like that and I'm not always sure, because I don't know too much about like the India market slash, can they get like outside of India? So like the only place that I really know well is the States. And right now I don't know what the hiring is like from the States to India like remote work or hiring them to come over. I just don't know that. And so wish I could give a better answer on that one, sorry. Christine asked, how did you learn those things on your own or in school? Yeah, so if you didn't know, I did not have a degree in anything related, anything to data analyst. It's like just complete opposite. It's called recreational therapy. So think of like physical therapy, occupational therapy, that's the kind of stuff kind of work that I was doing. And so I worked at a behavioral hospital. So no, I did not learn this in school. And I am very upfront about that. Oh, I'm not in focus, there we go. But yeah, I first started learning on Udemy. And so I'm a huge, I like to tell people to go to Udemy because that's where I learned everything, everything at the very beginning. Once I started like really becoming sorry, once I started really becoming like addicted to courses, Udemy actually was pretty expensive because I was doing like six, seven courses per month. And it was like, it ended up being like 80 bucks or something. So I started doing Coursera, which is a little bit more professional I found, from universities and things like that. And so, if you plan on doing lots of courses, which I hope you do, I would recommend Coursera and Udemy. Those are my two favorites. And that's how I learned to answer your question. Koa, you ask, or you ask, can you make a video on how we store a project like on GitHub? I'm just a beginner, so I don't know how to do a project and then show that on a resume. Yes, I will absolutely 100% be doing a video on that. If you haven't already on GitHub, there is something called github.io. And that basically is a way to present your portfolio or your personal projects. And that's what I use. That's what a lot of developers and data scientists use. And I have a big community of people who I talk to in that area. And that's what a lot of them use as well. GitHub is just really good to know, good to know how to use. So, yes, I will absolutely be making a video on that. Happy Vive says, which is the best online course available for Power BI for beginners? There was a really good one. There's a really good one on Udemy that I like. And I can't, he's a YouTuber, but he made a course on Udemy. And I really like his stuff. And I believe that's in my, I have a whole video on Udemy courses. That's the one I think I reference because he's really good. Any rags? Oh, nevermind. Was not even a question towards me. Christina, you have been asking some good questions. She says, how does SQL Tableau Excel Python, which one you recommend an absolute beginner should start with? All right, I'm gonna say it again. And so if you watch my channel, you know what I'm gonna say, it's SQL. SQL is, it's an absolute must. And a lot of people don't think about it. They think the visualization side is the most important. You know, they think Python is the most important. I think Python can wait. For the most people, Python can wait until you get like that first job or it can wait until, you know, you learn the other staples. SQL to me is the absolute must. You have to know how to use it. And if you can't, let me kind of justify why I say SQL first. Number one is SQL is gonna be asked for technical questions a lot. And so if you wanna pass the technical questions in an interview, you're probably gonna need to know SQL. And the second part of that is you need to know how to use databases to query your own data. It's because you don't wanna have to rely on somebody else to do that when you're a data analyst. You need to know how to manipulate, query, create all these things around, create tables like within databases. You need to know how to do it. So let's see, Joss, Joss, I don't eat. If you can tell me how to pronounce your name, I see you comment on every single video and I see Joss sing. That's what, that's not in my head, that's how it sounds. So if that's not correct, tell me how to pronounce that. He said, hey, Alex, happy Black Friday, going for shopping. No, I am not a Black Friday shopper. I stay home with my family. That's not, I don't think I've ever done that. That's not for me. Anush says, I am doing my undergrad on data analytics. What should I do my masters on? I like space, I like space. I think he's saying I like data science a lot. Is it a good career? For a master's, if you're gonna jump right into a master's, which I always recommend getting some experience first and then getting a master's, that's just my personal opinion, because it's way more valuable than jumping straight into a master's. You're able to get a job a lot easier, you make more money, I have a lot of reasons for that. But if you're gonna jump straight into a master's, look at computer science, look at statistics, look at analytics, things like that are always solid. You can't really go wrong with any of them. You can also get an MBA with a concentration in analytics that's really up to you. Just depends on where you wanna go with your career. Some of those are more tech heavy, some of those are more like, if you wanna go the managerial route, an MBA is obviously gonna be better. So let's see, let's see, let's see what's next. Deval says, as a data scientist or analyst, where should one go, MNC or a startup or a mid-level company? I don't know what MNC means, but I get your question. You know, I kind of lucked into, I started out a really small company, like 50 people or less. And because of that, excuse me, I don't know, I didn't put my water over here. I may need to run and grab my water really quick. But I lucked out, I started out a really small company. They trained me and mentored me and I got my hands in a lot of different stuff. I was doing user interface work, I was doing QA work. I was doing client-facing work. I was writing short procedures, really tough, really tough to me, SQL scripts that I had never done before. So it really pushed my boundaries, but I learned a ton. And so I look back now and I'm like, oh, I'm really glad that I got the small job first because it gave me a ton of experience so that I could land the job I have now, which is at a Fortune 500 company, you know, 20,000 plus people. And so I'm really glad that I didn't go big first because what I found is that a big company at a really well-established company, you have a very narrow focus on what you do. So I'm a data analyst and I work with people who do visualizations, but my job specifically is much more on the ETL side of things. And so I don't get to do visualizations that much anymore. I mean, I kind of help a little bit because we have BI developers who do all of our visualizations, but I really work mostly on the ETL side of things. And so I'm glad I got the small experience first and then the big experience. That's kind of, if I were anybody, I would kind of want to go down that path as well. Yeah. So let's see. Okay, so Riyad asked after a few years as a data analyst becoming, beside becoming a data scientist, what can you become in order to advance your career and what pathway would you personally follow? That's a really good question.  And so I think about these things a lot, like what do I want to do with my career? What do I want to do with this channel, a lot of things, but to answer your question, you can go down a lot of paths. You can go, you can continue down the data analyst path, senior data analyst, lead data analyst, and you could stay a data analyst. You can go down data engineering, which is more ETL side of things, and it's more database and working with sources to get the data in that kind of work. Then you, as you mentioned, there was data scientists, you know, you can very much go the managerial route.  And me personally, I have two kind of routes that I'm really thinking about that I've really, really, really been honing in on and just like, should I, do I pull the trigger? Do I, you know, do this master's degree? Do I focus in on this? What I've really determined is I want to do one of two things. I either want to go manager of analytics because at my company, we have a really good analytics department. I'm in the data science department. And so, you know, I work with data scientists, and engineers, data architects, all these things. So I've really considered just going the managerial route because I have a really good rapport. I think I could definitely pull that off. The second route is I really think I would go data engineering. And the reason I say that is I am already very ETL heavy focused. So I do data modeling, data augmentation. I do a lot of data mapping. I work with our database developers and our data engineers a ton. So I know that worked really well. I know it very in-depth. So I think I could very much pick up a lot of that, those skills pretty quickly. But honestly, I loved data analytics. As you can tell, I create a whole channel based on data analytics. So if I was going to become a data engineer, I might have to change the name of the channel or something. I don't think I will though. I think I will stay data analytics, but just an option. I like data engineering a lot. Reski asks, good morning from my place, Alex. Is it better to learn R or Python first and which one should I focus more on? Thank you. So that's a huge debate. It's a huge debate in the analytics community. Do you stick with R, which is very statistics heavy, very much, very, a little bit more technical a little bit. I think it's a little bit more difficult to learn personally. Or do you stick with Python, which is much more popular in my opinion, much more used between different jobs? I personally will say Python. I use Python all the time. I love Python. I think it's amazing you do so much from automation to you can do data analysis. You can create data frames. You can do visualizations. Whereas with R, which I have used R, I just don't find it as easily usable. I don't find it as fluid is how I'll say it. So personally, I'm not a huge fan of R and that's probably because I don't have a statistics background. So take that with a grain of salt. I just think I like Python better. Happy Vibe says, how are you going to celebrate Christmas amidst this pandemic? How's your preparation going on? Great question. As you can see, we've been preparing. I mean, maybe I'll turn the screen so you can see over there, we've got stockings hung and everything. And preparation, we've got all the gifts wrapped and bought and they're sitting under the tree for our kids to just stare at for another month to kind of torture them. And so we're just going to celebrate with my family here. We're not going to be seeing anybody or going anywhere or doing anything.  Let's see. I'm looking for more questions, looking for more questions. But again, I see there's lots of more comments, but again, you don't have to ask only analytics questions. Personal is all right too. This is in AMA today. So whatever you want to ask. Koa asked, do you have to learn data structures and algorithms as data analysts more like a problem solver like in software developer? I don't really know data structures and algorithms that well. I've studied it a bit. I don't think I've heavily used it in any part of my job ever. But again, that just might be my role. I just don't use it as much. When I think data, when I think data structures and algorithms, I think like software engineer, software developer, like you said. So that's not something that I, the first thing I think of. Justin says, actually, what's the major task for a Tableau developer? Can we do some web analytics with Tableau like Adobe Target? I am not a Tableau developer or even close to that level by any means. I am good in Tableau. I've used it in my job, but Tableau developers, I mean, they're just on another level. But it's a lot of dashboards and reports and stuff like that. I really can't go that in depth because that's really just not my forte, to be honest. Abij says, any YouTube channels you recommend? My channel's all right, it's decent. Another one I like is Kenji. He does a lot of stuff. I watched his channel for a long time. There's the data professor. I watched a lot of his stuff. I'm gonna discord with him and he does really good content. And I watched a lot of his videos. So those are two that off the top of my head that I definitely recommend. He also said SQL or PG admin. SQL. That's all I got to say. All right, let's see. Wilson, how's it going, man? I'm assuming, because the name's Wilson. I'm currently learning SQL in school and I like to develop my skills after the semester. What are your recommendations on how to continue to build my skills? I would probably try to do some, I keep saying some personal projects, but honestly, what you need to do is think of like, think of something difficult to do and try to accomplish it through SQL. Think of how can you use a database?  Are you going to try to do some web scraping and insert that data into SQL and create an automated process for that in SQL, which you can do. I know because I've done it. What are you gonna do? And you just gotta figure out a project that you think would be really interesting and quite difficult for your skill level and practice it and you will, I 100% guarantee you will learn a ton along the way and develop your skills 10 times faster than just taking courses. I always tell people, take courses, take courses, take courses and then once you reach that level of this course on taking seems like I've got it, you gotta start into projects. You can't get in that cycle of courses. You gotta start doing your own projects. Maria asks, what are your thoughts on R for data analysis? Maria, I kind of answered this earlier, but I think that R is a fantastic tool. I know it has a ton of use, my data science, colleagues use it and way more than I do and they love it. I am not a huge fan. I just, it's not my thing. I like Python a lot more. Maybe it's just because I have a huge bias and I completely admit that. So take that with a grain of salt. You know, I may not be the best advocate for R. There are channels dedicated to R who love it. Cool. So hey, Alex, thanks for this QA. Natalia, you are very welcome. Would you happen to know one of the most important skills specific for a clinical data analyst? You know, it's tough because look, I work in the healthcare field. I understand the healthcare industry what I would consider quite well. A lot of the skills that you're gonna need to learn are gonna be what you learn across the board like SQL, Python, Tableau, Excel. But here's the difference is you need to know a lot of domain specific stuff to become a clinical data analyst. And what I mean by that is I have a background in therapy, like therapeutic, like recreational therapy, occupational physical therapy, that kind of domain. So I understand healthcare in general terms or when I first started, now I know it very in depth. So I was able to specialize or kind of give myself a lot better chance of getting a job because I knew healthcare very well. Or I knew it pretty well and now I know it super well, like way too much. I know too much about healthcare. And so, you know, you need to know things like the types of coding that they have, like CPT codes, Loink, HixPix, ICD. You need to know all of those, how they're used, what they're used for, how they're used in an EMR system. That's the kind of thing that'll help you become a clinical data analyst. Mooney asks, or yeah, I'm gonna say Mooney. For DA, for data analysis, is Python basics, are they enough or along with Tableau and SQL? Yeah, yeah, I would say, okay, well, first off the basics. I kind of consider like the basics like understanding data types, understanding dictionaries and tuples and all that stuff. That's it, but I consider basic. What I would learn in Python, apart from the basics, is 100% pandas. Pandas and creating data frames is one of your, is gonna be something that you need to know. So I highly recommend learning pandas and then some type of visualization. So whether that's Seabourn, Matplot, Lib, there's a ton of other ones. I just recommend those things. And especially pandas, if you didn't catch that. Pandas is very important.  And no Excel, you should be all right. Let's see. So Christina says, I'm thinking of buying a Udemy course on SQL. Is there anything else I should know as sort of a prerequisite for taking this course? Well, it depends on the course you're taking. Most SQL courses are pretty beginner friendly. I know I've made a whole video on Udemy courses because I've taken so many. I was just looking at this yesterday. Udemy's contacted me to ask to create courses or for them to sponsor the channel. And so I've been talking with them and I was going back into my channel or into my account and I was like, holy crap, I've taken like 60 some courses on here. There's a lot of SQL courses. There's a lot of data animals courses. And so you just gotta know, look at the course, see if it's beginner friendly. But there shouldn't be any prerequisites. As long as you have a computer and you know how to like do basic stuff, like right clicking and downloading things off the internet, downloading files, changing file types, those like really simple stuff you gotta know. If you know how to do that, you can take this course on Udemy. Let's see. ABJ says, can you come again with the MBA with the analytics part? So some MBA programs have what they call specializations. You can just get an MBA and it's just a generic general MBA, masters of business administration. That's what it's called. But you can also get a specialization and in the specialization, you can do like data analytics or analytics, business analytics, things like that. Those are the typical things that you'll see in MBAs. And they could be really great. And so if you wanna go into this field and you wanna be on the kind of more managerial side of things, that might be for you. So look at MBAs. Radha says, hi Alex, as a data analyst should I concentrate more on statistics for scenario-based or focus more on visualization tools like Tableau or Power BI. That's really, that's a tough question because I think both are important in their own aspects and also it's very job specific because some jobs are very quantitative, very statistics heavy, whereas some are more visualization heavy. I made a whole video on this. These data analyst jobs vary so widely. Some are like way over on this side and they're like almost data science-y where they're super statistics, super programming heavy. Then on the other side, they could be just be like basically doing data visualization for the most part. And so there's a lot of gray area in what a data analyst is supposed to do. And so I know both well enough to get a job and then just figure it out from there. My advice, not didn't answer your question super well but that's my advice. Mark asks, what's ETL? ETL is extract transform load. Yes, Shubham, I probably butchered that name. I'm so sorry. Shubham Arl, so sorry. It's a fantastic name. I'm just so bad at pronouncing names. It's a well-known thing for me. And so I apologize if I mess up like everybody's name in here. I know Mark, M-A-R-C is pretty easy Mark. What's ETL? Extract transform load. And what that means is you're extracting the data from some type of source, whether that's somebody else, like whether that's a third party database or your client's database, you can pull it straight from SQL or you can take a SQL backup. You can also get it through Excel files where you import the Excel file from like an FTP or SFTP, which is a place where you can just drop files and you can pick them up. And so that's the extraction part. The transforming is transforming and creating business rules. You could be cleaning the data in some type of way and also formatting and pulling in the data that you actually want into a database. And then that's the load part. Then you're loading it into a database, usually like a staging database. And then you clean it up from there and you put it into an actual table or an actual database that you're using like a development or production or a testing environment, something like that. And there's more on that. Let's see. Faker said, hi, can you please advise on what Python libraries we need to know for data analysts? There's a ton. And not just, I mean, when you say data analysts, I genuinely think, I always think of things like pandas. I always think of Matplotlib, NumPy. You can also learn Seaborn. Those are like the four or five really data analysts, heavy ones that I'm like, I recommend to everybody. There's a ton of other ones. If you wanna go into a little bit of machine learning, you can do second learn. If you wanna go into some automation, there's ones for that. It's really hard to like, because I do a lot of automation in my job, a lot of Python automation in Azure and Databricks and stuff like that. And so kind of hard to just narrow it down to data analytics specific, but yeah. So that's my thoughts on it. My CMark commented, oh, that's what I've been doing. So yeah, maybe you've been doing that work all along. A lot of people will say, when they watch my video, I think it was on what does a data analyst do or something like that. They're like, I don't get paid like a data analyst. I don't have a data analyst job title, but I swear I'm doing all the work of a data analyst. And I'm like, you probably are and you're probably being underpaid for it. Karan just said, your video on top 10 Udemy courses of data analysts was really helpful. You're most welcome. Let's see, let's see, let's see. Just scrolling through some questions, trying to see, okay, we got JD, hey there data analysts from Texas as well. Hey, how's it going? Very, very cool. I guess I am a data analyst in Dallas. Maybe you're in Dallas, maybe you're in Houston, San Antonio or yet, but it says down south. So pay isn't that great doing my masters this year in business analytics. Congratulations, that's very cool. What do you think the pay rate would be for two years experience and a masters? Depends on where you are. If you're in the rural area, for masters and two years of experience, it could be as low as like the 50s. But if you're living in a major city, specifically I'm gonna talk about Dallas because that's where I live and I know the market way too well. If you have two years of experience and you have a master's degree in analytics, you should be making probably at least 75. And take that with a grain of salt because it depends on the industry. If you're in a really tough industry right now, you might be making a little less, maybe like 65, but I would not take anything less than 65 with your experience and your education. That's just my opinion. Wilson asked, I'm majoring in data analytics, minoring in business analytics with SAS, very cool. I'll be getting my minor this coming semester in certification and SAP. What are your thoughts on SAS or SAS and SAP? I think they're both extremely useful. I think they absolutely have their place in the market. I have a friend who uses both of those a ton and tells me how much he loves them all the time. And I always tell him, I'm like, hey, look, I just don't use them. I don't, then that's not true. I've used them. I personally don't think that's what I would focus my time on for my industry because some industries use SAS and SAP a lot more than my industry specifically because my, I guess maybe it's just my department or my company, we don't use it a lot. And so for me specifically, I'm not gonna learn it in depth. I know it, I just, I don't know it in depth. So I think it definitely has this market though. And if you're getting a minor in it, I'm sure it will be helpful, I guarantee it. Okay, Mark asked another question. I don't have any experience in Power BI and Tableau, but I've been using Google Data Studio at work. Do you think that's a good way to start? Anything where you're making any data visualizations at all is absolutely a good way to start. I think a lot of people think, this is not a reflection on you, I'm going off on a tangent, so don't take this personally in any way. A lot of people think that Tableau and Power BI are like super unique, you need to learn only those ones. That's really not true. Data visualization is getting a lot easier and so many other companies are starting to do it. And if you find a different tool that you like that is not one of those, it's totally okay. And I'm trying to, there's one specific, one that I'm thinking, I'm trying to think of, but not a lot of people have heard of. And I think it's a great tool and it helps you understand the fundamentals of how to create visualizations, what you're doing. And so anything that you can do to do that is fantastic. Eventually I would stick over to the Power BI Tableau because it makes you a lot more marketable, makes you a lot more easily hired and so I would recommend learning that, but it's a great place to start. Wherever you're at, it's a good place to start. Valoram says, I'm not into coding, but there's more salary on software data engineers than data analysts.  Okay, here's my thing. So software or SDEs or software engineers are all those things which are super tech heavy, you need to know coding very well. Those jobs, of course, they're gonna pay more. They're very technical. You need to know a lot of things.  If you have something unrelated, it's gonna be extremely hard to get into that field because it's not really domain specific. If you have healthcare knowledge, they don't really care that much, whereas data analysts can do that because it definitely is, you need to know the data. You're not just building software, you're genuinely using the data, working with the data. And so if you wanna go that route, go for it. But data analysts is gonna be a little bit more achievable for most people, especially if they have some type of domain experience. That's just my thoughts on it. Elk, Cardian, seeing Alex answer and reply to literally every single comment shows just how truly you care about the community around you. That's amazing, Alex, thank you. I do, I care about you guys way more. Maybe it's too much. Maybe I care about you guys too much.  Every time someone messages me and is like, Alex, this video changed the way I looked at data analytics. This helped me so much because genuinely, four years ago when I was first starting out, I didn't have anybody. Nobody who was creating videos like I'm trying to create. Nobody who would do key ways like this or who that I could find. I just didn't have anybody. I just did this all by myself. I felt very alone. I had that a lot of imposter syndrome because of that. And so with this channel, I just wanna help you guys as much as I possibly can and it means a lot that I can honestly just help it anyway. Happy vibes, all right, here's a good question. Which one would you like to have? Radish or Vegemite or pineapple on pizza?  I think it's UK-based. I think it's also an Australian thing, but I've had it before and it's terrible. I also hate radishes. Those are my worst thing. And truth be told, I actually don't mind pineapples on pizza. I kind of like the sweet flavor a little bit. So I would absolutely try to choose pineapples over any of those other options. Akili says, hello, is MongoDB used much in the industry? It's used a ton in the industry but not really our jobs focus. Our jobs specifically. I have coworkers who use MongoDB. I just, I don't use it personally. I don't know a lot of people that use it, to be honest. Koa asks, if you wanna work in healthcare as a data analyst but I only have a degree in data analysis, is that possible? Of course, you don't. It's not impossible to do it if you don't have the domain knowledge. Sometimes they want someone more technical. And so if you wanna go, if you have a general data analyst acumen and knowledge and skills, you have a lot of area to look into and grow. So find an industry that you like and stick with it. And that's kind of my advice. Let's see, let's see, let's see. I'm scrolling through. I'm scrolling through. Mark says, I'm already 33 and just started working as a data analyst. I've been working as a data analyst for around 10 months. Do you think it's too light? No, absolutely not. Absolutely not. And I answered this in an Alex the analyst show I'm gonna call it because I don't like saying my own name. I answered it in an ATA show one time. Somebody had commented saying they were 40. Is it possible to turn their career into data analytics? And I was like, absolutely. And here's why. And it's not for everybody. Not everybody can do this. But if you have certain things, you can. The first thing being, if you were older and you've worked in a specific industry that has any type of domain knowledge that could be transferable or has anything data heavy, you can absolutely do it. Healthcare, you can do if you're like a nurse or you used to be a doctor or you used to be a therapist or any of those jobs, a social worker, you have a healthcare background and you learn the skills. And I guess this is with the assumption that you have all the skills that a data analyst has. You can then transfer that domain knowledge to become a data analyst and it's very possible. I've seen it a ton. Like in my job, I have seen so many people who were like, yeah, I just became a data analyst like a couple of years ago.  And they're like, oh yeah, well now I'm a clinical data analyst. I used to be a nurse. And I was like, oh, of course. So anything financial related, healthcare, construction, e-commerce, like there's so many domains that, marketing, analytics, stuff, anything like that. You can absolutely become a data analyst from that. I just, with the caveat is I think the domain knowledge part, especially as you're older and you've already kind of set yourself in a career, if you have the domain knowledge, you can do that. That's my thoughts on it. Let's see, let's see, let's see. Abhij says, I know basics of Python for analytics are Tableau SQL PG admin. It's like I'm the jack of all trades master of none. Yep, I feel that. I reckon projects are the most important part. So where do we find these projects or do we create it out of thin air? Projects is such, it's a difficult thing to think about for a data analyst sometimes. And I think everybody's been there.  I kind of built my portfolio from things I actually did in my job. I didn't have a portfolio when I first started out. I just had SQL scripts that I put on a Word document that I thought were pretty good and I sent that to employers. That was my portfolio at the time. Projects, and I talk a lot about, I'm going to create an entire series and videos on how to create projects. I just recorded like six SQL videos on intermediate and I'm starting my advanced SQL series. So I'm finishing up one, starting another. And after that's done, I'm going to go into creating projects and all these things. Here's what I'll say really quick because I just went off on the right there. At this time, I have not found personally a ton of great videos or content on projects for data analysts. But here's what I'll say. Try to do something ETL where you're importing data into a database specifically SQL, transforming it to data cleaning. Show you know how to clean data, set up views. Then take that data and put it into a visualization in Tableau, create a dashboard. That in and of itself can be like three projects and you don't need more than that. They just need to be really good projects. And so that's, I just kind of went off on a tangent there, but that's some of my thoughts on it. Bonutasia, Chitty Bethany, I butcher that. And I think that is a really cool last name but I can't say that properly, I apologize. But they said, for data analysts rolled you need machine learning. No, you really don't. That's very much a data scientist thing. I work with a bunch of data scientists. So I had to learn a lot of that talk, a lot of the speak about models and just things that data scientists would talk about. I had to learn that stuff to kind of keep up with the jargon. And so I've learned quite a bit and I don't, again, now that I know a lot more about it, I'm even more convinced that you really don't need to know it that much. Again, that's just my two cents. I keep saying that because I don't want you to be like, I'm not learning machine learning. Alex said I don't have to learn machine learning because then you get into a job and they're like, hey, you need to know machine learning. And you're like, ah, so, yeah. So that's just what I think. Eriko Lim Lim. I'm currently a senior studying human biology and looking into data science. What programming language and skills should I develop before looking into masters in computer science? Thank you. So you're gonna go right into a masters in computer science. You need to know databases really well in computer science. You need to know, normally you need to know Java. You need to know Python. Sometimes they might even have you learn C++. I personally know Java pretty well. I don't know C++ that well. I am not gonna be getting a masters in computer science at by any means anytime soon. So I think that learning SQL really well, starting to learn Azure or Amazon web services really well in those services is probably gonna be really beneficial these days. So those are some programming language that you might look into. Interag said, thank you, Alex. You're great. Once again, the job will give you some of the salary. You don't have to do that, man. Don't do that, man. But love from India. Love back from the States. Thank you. I appreciate you. Let's see, let's see. So Faker Saab says, hi, Alex, I need some details on people analytics. Could you please provide how we need to gain knowledge on people analytics and is there any job in future? Please talk on people analysts. I've never heard of that. I had somebody else ask me that the other day and I was like, I don't know what a people analyst is. Maybe someone in the chat can help you on that. I've just never heard of it. Yiwen Zhao, let's go with that. I hope I pronounced that right. Oh, I just skipped it. Give me a second, I'm going back up. You said, is there any good way to get a job without any experience? I just got a data analyst co-op in the government from Ontario, it's only for four months. So from my experience, yeah, you can absolutely get a job. The best way to do that is to create personal projects to try to get an internship and then just really, really like create a fantastic resume to get into interviews. This is what, then generally, this is what I did. It's had no experience. Is really, really make a good resume. Really highlight your skills, your hard skills instead of your job experience. And then when you get an interview, after you worked with recruiters and you've done all the stuff in all the videos that I've created, once you get in an actual interview, you just sell yourself so hard, you're like, I got you. Hire me and I've got you. And just get experience. It's hard to get experience without experience and that's kind of the irony. And so you just really have to sell yourself and you really gotta push yourself and apply to jobs and work with 20 recruiters at a time. It's tough when you're first starting out with no experience. I've been there, I know how hard it is. Vinoth asks, how many hours did you learn when you started and what is your source? So I was, I had a full-time job when I first started out. I wasn't in anything data analytics related. And I was spending about four hours a night-ish after my job. So I'd come home, spend some time with the family, the family would go to sleep and then I would stay up for at least four to five hours studying mostly SQL. And I did that for about two months until I felt pretty comfortable and then I started applying for jobs. I also was studying Tableau a little bit and it was just a little bit confusing to me at the time. But I was studying about four hours a day and I mostly during those first two months was on Udemy. So Udemy was like my super go-to place to get courses. As I advanced a little bit and I started taking too many courses I switched over to Corsair because it was a little bit cheaper. Sariel said, what are we talking about? I just joined randomly. We're talking about data analytics stuff. If you've ever seen my channel, I'm a data analyst. So thanks for joining. Let's see. JD said, so to expand, I'm in a city near the border of Mexico. My field is healthcare and I'm currently at a manager level sitting at 44K yearly. I really am hoping to get up to 50 to 60 with my masters. I think you can do that. I absolutely think that's reasonable and attainable. Let's see, let's see, let's see. Elena asked, I'm curious what your work in the healthcare industry is as a data analyst. Would you mind sharing more about your work? If you can of course, I of course I can. I just won't go into too much but I'll try to give you some information on what I actually do, what kind of data I work with. So I work for a, in the pharmaceutical space. So drugs, drug distribution, that kind of stuff. If you go over to my LinkedIn, you can find out more about who I am and what kind of my job history is. So I work in pharmaceuticals. I work a lot with drug data. So a ton with medications. I know if you take a medication, I probably know about it because I've looked at so many drugs. You would be, you'd blow your mind. So I know a lot about drugs, really a lot of cancer and oncology data, hematology, which is like the study of blood and stuff like that. I work a lot with that data. A lot of my work persists, contains of, I'm confusing words, pertains of working with sources. Let me take a step back. When I first was hired on, we needed somebody who could work with clients to help work with them and get their data in and do the data mapping, data augmentation, data of anything that they needed in order to work with the developers and all these people to get the data, you know, create business results. Yeah, I'm rambling. Now that we hired on two people, besides, slash underneath, I don't really do any of the client facing work anymore. I'm much heavier on the technical side. I work with, I work super heavily with our database developers, data engineers, data architects to help plan and design and transform this data to be usable for our clients. And so that's the kind of work that I do. And it's mostly centered around oncology, drug data, CPT codes, Hix-Fix codes, ICD codes, all that stuff. So in a really nutshell, that's kind of what it is. Maxwell says, I'm a senior in high school, planning for college and looking for an undergrad degree undergrad degree in data science, probably to Iowa State, very cool. I have my brother-in-law with Iowa State. Is that the best way to get in since I have no experience? Yeah, a bachelor's is, it's not impossible to get a job without a bachelor's, but it is much more difficult, much, much, much more difficult. So if you get a bachelor's degree in data science, it will definitely set you up a lot better than not doing that. Eric said, can I get into the data analytics, get into data analytics with certifications rather than an MBA? It depends if you have a bachelor's degree and what's your bachelor's degree, I guess it doesn't super matter, but you probably need a bachelor's degree. And then yeah, you can do it by self-learning and getting certifications and doing personal projects and creating a portfolio. Absolutely can. I did it. I know it's possible. It's just, how much time do you have? What are your career goals? There's a lot of other things that go into it. Chioma says, thank you for your time with the Q and A. You always show up at the right time. Super glad to hear it. That's what I'm here for. I'm super glad that it's helpful. It's almost up to an hour. I'm gonna run a little late. I'm just hanging out. My kids are all asleep. My wife's asleep. I got three kids asleep upstairs. I'm just hanging out by the fire, enjoying the Christmas lights. I'm just hanging out. So I might just hang out with you guys. I don't know if I'm gonna keep going or if I will stop or keep going, but L. Cardian, let's see if that pronounced that right. Alex, do you think for an entry-level data analyst, do you think for an entry-level data analyst? But only use Excel, but you only use Excel only, i.e. without, so it is, we're still worth it. I think what you're trying to say, and maybe if I get this wrong, correct me, but you're basically saying, if there's an analyst job and you only use Excel, should you take it? I would take any job where I was doing anything analytics related with any tools at all when I was first starting out. My very first job was only Excel. So I would say, yes, use that because you can leverage that as experience in a next job. So yeah, I would definitely do that. Chioma also asks, what do you think about Kaggle? I like Kaggle a lot. I think it is very data science heavy, but I've done a lot of competitions and I've done tons of stuff on, because that's how I learned a lot of the machine learning stuff. They have a really good data analyst course on there. It's a little bit advanced. It's not very beginner friendly. It was difficult for me when I took it like two years ago or whenever they opened it. I don't remember exactly, but Kaggle can be a pretty big leap into the water if you don't know what you're doing. But it can be a great resource if you're looking for other people who know the industry and are willing to share their thoughts on things and you can look at their code and all that stuff. So it's a great resource. I just, it wouldn't be the first place I go. Let's see. Michael says, I just want to stop in and say, hey, what's going on, Michael? What's going on? I hope your Thanksgiving went well and I look forward to watching more videos. Thank you. My Thanksgiving went fantastic. We had turkey, we had ham, we had gravy. I ate my fair share of mashed potatoes. And it was just, it was super chill. Yeah, had a great, had a great Thanksgiving. I hope you did as well. Shan Guan says, Kaggle, good place to start. I kind of answered that earlier, but I don't think it's a great place to start. I think it's a good place that you can go to later on. But if you don't know the basics of like, mostly like Python, because they use a lot of Python in on Kaggle, it'd be kind of a difficult time. Let's see. Do you use tools or methods to keep track of your work day to day? This is by gtam1289. Do you use tools such as a physical or digital calendar and methods such as Pomodoro method? If you do, what are they? No, don't use the Pomodoro method. What we use, we follow a different methodology called, oh gosh, it's gonna slip my mind, Agile. So we use Agile methodology. And if you don't know what Agile methodology is, it's a way of breaking up your work so that you create it in, well, there's a few different types of Agile. We use something called, we don't use Kanban anymore or Kanban. Maybe Scrum. But we break it into two-week increments. So every two weeks is a different called Sprint. That's how we organize our work and we do that on, we do have a software I'm blanking on the name. That's not my job. So we have project managers who manage all of our work. So I don't have to manage my own work. Thank goodness, because I am, that's not my forte, I'm not my thing. So we have project managers who organize all my work for me. Tell me what I need to get things done. Some, in a way, if you know what a project manager does, you understand that. They help organize our work so that I can better go onto my board, see what I need to work on, see when the deadlines are, et cetera. So we use, we do use software for that. And we use Teams, Microsoft Teams for meetings and all that stuff. Akshay said, at the very beginning of data analyst course, how should I plan my journey of learning Python, Excel, machine learning, Power BI? I noticed you don't have SQL on there. I will start with SQL. I would then move to Tableau or Power BI. I then move to Excel. Then I would move to Python. Then I would move to machine learning, machine learning last, because it's not as important. Natalia says, should I learn how to clean data using SQL, or do you normally use Python for it? It really depends on where the data is being stored. If it's stored in SQL server on an on-prem database, I use SQL. And if it's stored in a SQL server in Azure on the cloud, I use either SQL or Python. Just depends on the project, depends on what I'm working with, but I've used both. And I will say that data cleaning is extremely important to know. So that is a fantastic question, but you can use both. And so if you know how to use both, all the better. And that, again, if you're looking for projects, data cleaning is something that a lot of data analysts do not know how to do. And if you can show in a project that you know how to clean data, very, very good. And again, I will be making videos on that. I'll be making a whole video on how to clean data, how to format data, all that good stuff. That's just probably early next year. I have a lot of videos already recorded, and I only post two a week. So that could be early next year when I do that video. AZ says, there seem to be much fewer data analysts and data scientists jobs compared to software engineering jobs. Would it be easier or safer to get a job in software engineering than data analysis slash science? You know, I don't know too much about the software engineering jobs, that market, because I just, I'm not in it. But what I will say is there are a lot, at least in the United States, I'm not sure where you're from. In the United States, there's lots of data analysts jobs. And I know even in my industry, health care, health care is still hiring a lot of data analysts. And even more so now that COVID has impacted hospital data and all these things, any more people. So some industries are hiring more data analysts. In terms of software engineering, I can't really comment on that. I think that if there are a lot of software engineering jobs and you have that skill set, go for it. That might be the way for you. I just, it's hard to say. Hearth asks, do you know about supply chain analysts related roles? What skills are common with data analysts?  I just don't know much about it. I would assume it's very much the same stuff. But again, I just don't know supply chain, analytics related things. So I'm sorry about that. Wish I could be more helpful. Riyad is asking a really interesting question and this needs to be addressed. And this is kind of a tough question to be honest. Do you think data field will last for decades? Like hopefully it doesn't get automated. So data has, okay, and I have lots of thoughts on this. And I don't know if I've even, I may have not have made a video on this or not, but I will 100% make a video on this. Data in and of itself is growing at an exponential rate. So data in and of itself is not going anywhere. We are collecting more and more and more and more and more of it every single day. So it's not going anywhere. But I think what you're kind of asking or alluding to are data jobs going to be here or are they gonna be automated? Here's what I'll say around this is almost everything will be automated eventually. But they won't be automated to the point where you don't need manual people. You don't need physical humans to do the work. Like, when I think about like Tableau, certain things in online and Azure and all these things, a lot of these things are getting automated, but it doesn't mean that people are losing their jobs because of it, although it might on a small scale. But people aren't just like, oh, we automated this one thing, now there's no data analysts anymore. It's just not really how that works. Things get automated incrementally. It's not all at once. It'll be over the course of 10, 20 years, but in 10, 20 years that data analyst job may look a little bit different. Data analyst jobs won't go away. And I am willing to bet my career on that because I plan on being in this career for a while. And so I don't think it'll be automated like you think it's gonna be automated or you might fear that it's gonna be automated. I look at it very much like the automation and cars. You know, factory line workers, they used to do it in a very inefficient way and now they do it in a much more efficient way and it's created millions of jobs. But they've automated a lot of that work. There are robots doing work, but there are still millions of jobs in the auto making industry. And so it's just a really, maybe a bad example, but think of it like they're just enhancing features. They're making things better for data analysts instead of replacing them all together. It'd be extremely hard to replace a data analyst. Colzan says, hi Alex, how are you? I'm doing fantastic. I'm chilling, I'm doing good, living life, can't complain. I'm a thankful student. I think that's a bootcamp, is that correct? Let me know if that's wrong. And hoping to change my career to be a data analyst from a call center representative, I like how open you are about the whole process. It's something that I need. Oh, I thought you were gonna ask a question. I read that as I thought you were gonna ask a question. Yeah, no, I'm super glad that it's helpful. Thanks for saying that. But I definitely hope you can make that switch. I believe Thinkful is a bootcamp. I'm pretty sure I've looked into that before. So correct me if I'm wrong, but if you've done a bootcamp, that's fantastic. And I hope that that works out for you and I hope you're able to make the switch. That'd be amazing. Definitely let me know how that goes. Tyler says I graduate in two weeks, congratulations. I still haven't found a job yet. Do you recommend looking into grad school for analytics to stand out in the job market? A master's degree can only help you. It really is, it'd be really tough or you'd have to choose a really bad program for a master's to hurt you. What I will say is if you can't get a job or you aren't able to get a job because of the market, a master's degree might be the way to go. Before all of this happened, my recommendation was for people to get out of a bachelor's, do their best to get a job. If you can get a job and get experience, it is worth more than a master's degree. But then if you want to, you will hit a cap. You'll hit a ceiling without a master's for the most part for a lot, the vast majority of people. You'll hit a cap and then in order to progress further than that, you'll need a master's. And I'm starting to get to that point where I kind of need a master's degree now. If I want to pursue more, I want to go higher. And so I've been looking into master's programs a lot. And so, you know, I recommend looking for a job. If you can't find one, a master's degree would be great. Let's see, let's see. Kaiser says, hi Alex for an entry level analyst. Is it sufficient if I focus on one programming language? What I have to eventually write multiple programming languages when would that be many thanks? So it's an interesting question because I think if you're a data analyst you don't need a programming language. You can be a data analyst without knowing Python. It's very much possible. But if you want to progress to a higher level programming languages are kind of a way to go. It just shows you're more technical. You have the skills. You can make more money with doing that way. That's what happened with me. I don't think you need a multiple programming language. I think stick to one, specialize in it, get really good at it. And market yourself like that. Market yourself as the Python data analyst. That's a valuable, very valuable thing to do. And so when would that be? If you want to learn like both Python and R, go for it. You don't have to do that though. That's not my recommendation. Diego, I think I've talked to you before. What's going on? Hi Alex, I'm working for eight years as a data analyst for a retailer. And the most difficult thing I found is how to understand the business itself. Did you have the same problem? Yes, absolutely. 100%. When I first got into healthcare analytics, the small startup company that I worked for, I didn't understand their business at all. I was like, why are people paying this company to store their data? What are they doing with it? I don't understand it at all. It took me a good two to maybe three months until I really understood the business model of the company, what the clients got out of it, what we got out of it. The data, everything. Took a while. RL said, hi, any idea on how to find a project to work on? No, not really. I'm gonna create a whole series of videos on this. I just don't have them ready. Look into ETL stuff, do a cleaning, a data cleaning project, do a data visualization project. Look at github.io, all things I would be doing. Bum, bum, bum, just some people asking questions. Not to me, though. I don't ask questions to other people. This is my live stream, get out of here. I'm just kidding, you guys can do that. I'm just, I'm kind of, I like to talk when I am not sure what to talk about and so I'm looking for questions. Okay, is it necessary to learn how to clean data in SQL and create SysTables, views or reports in SQL? I mostly use SQL for pulling data out of databases for data cleaning, I prefer Python. You don't need to know how to do data cleaning in SQL but I really like it and I like Python, too. So if you wanna only do Python, go for it. You can do Python in the transformation cleaning process and then load it into a database, absolutely fine. It's just whatever you prefer.  You asked about SysTables. I recently, I was working with one of the developers, I learned how to do some really cool loops in SQL. This isn't something I'd ever done before, it was kind of a use case issue that we were having and they tasked me to figure out how to solve it. I ran through kind of some problems automating the process. So I contacted one of my developer friends and he was like, who I work with and he was like, hey, try this with the SysTables and I was like, that's a really good idea. The SysTables are just kind of a huge view of all your tables on the backend. And I have started to use them more and more and more and I've used it a lot for automation. And so yes, I think you should. I think you should learn how to use SysTables and views, know how to use views and how to create reports, absolutely. I create a lot of reports in SQL with sort of procedures and jobs and all that stuff. Yeah, I would definitely recommend that. Your brand or your brand, however you pronounce that, sorry. Is you and me the best way to learn SQL? It seems quite simple to me. What does the level of difficulty come from and how can you become acquainted with high-level SQL are their projects? So let me, this is a great question because people, I feel, this is me personally, I feel like people think SQL is easy. And I used to think that too. And so I would take a course and I'm like, man, this is easy. I know how to use like the between. I know how to use like. I know how to use this stuff. SQL, the basics of SQL are they're easy and I always recommend people learning it because it's easy, huge confidence boost, really gets you like, yes, I can do this. Advanced SQL is a whole another beast and I've only started to really dive into it within the past year really heavily since I've worked on the ETL side a lot. You can do a lot in SQL that I had no idea you could do. I mean, I'm basically doing more programming. I'm writing almost like Python stuff within SQL. I'm using a lot of store, I'm creating store procedures, I'm automating reports, I'm automating sending emails. I can, I can send, you know, you probably already know this, but I can send, I can create a report, I can automate it to refresh the data and send a fresh report to a client at the beginning of every single month. And I've done that tons of times. And so it's like, when I first started out, I was like, I thought this was just querying data. I thought SQL was just how to get data out of a database, but now I'm realizing I can do so much with it. I can do loops, I can automate tons of things and create views, I can do, I can clean data. A lot of these things are just not things that are really taught in courses, to be honest. Which is, I guess it makes sense because it's hard. It might be job specific, so it might not be as broad as a course might imply. But you're right, some of these courses are really generic, really broad. They teach you the fundamentals of how to query data, but they don't go 100th into what you can do with SQL, and it's actually really, it's really, really advanced. I think on a scale of one to, I used to think I was like a seven or eight in SQL. And I think for a data analyst, I'm probably like pretty high up there. But now that I'm working with data engineers, data architects, all these things, I think my SQL abilities are like a four. And that's sometimes, on some days, that's being generous. Because SQL gets really, really advanced. And so take those courses with a grain of salt, understand that's the basics. Once you get into a job, you'll come across a lot of use cases where you've never encountered them before.  When I was first starting out, easy was super hard for me. The intermediate are actually pretty difficult if you've ever tried those. And the hard are super hard, but those are focused for data engineers. So you have to think, you know, these data engineers need to know how to do those hard level problems, and they are extremely difficult. They're just very, very challenging. It's much more coding. It's much more heavily, almost closer to programming than it is SQL. And so when people ask me, is programming a language? And I say, it's a programming language after a certain point. But at the beginning, it's not a programming language, it's just querying the data. But SQL is just, I know, I've gone off on a huge change on this, I'm sorry. But SQL gets very tough.  It's almost like it becomes programming at a point and it does become quite difficult. Okay, so I'm back into the questions. Got off on a huge change, and I hope that was useful in some way. I just started talking, I don't know. I have no idea. Sean, you are most welcome. Thank you so much for joining, being part of this. I love doing this stuff. It's been an hour of 15. I don't even want to stop. I just want to keep going, but I will have to stop eventually. DeVita says, do you plan on posting videos on the types of Tableau and Python projects analysts actually use at work, learning a lot from your videos? Thank you. I'm super glad you're learning stuff from my videos. That's the whole point, just for you guys to learn. I will be doing a whole series on projects. And I think this is gonna be early next year. And I said this earlier is that I, going into the holiday season, I have already recorded like six SQL tutorial videos. So I have a lot of those that I'm gonna be doing. So I probably won't start picking up like new ideas or new videos until like early next year. And so I think that I will absolutely do those videos. It's just, it's gonna take a little bit. And then I have to actually plan it out and create it. And it's a lot, it's quite a bit of work. So 100%, I'll get to it though. I promise you, you can hold me to this. Bum bum bum, Excel can't believe how much I need to know. Yeah, Excel isn't that hard. Isn't that hard, come on, it's not that hard, just Excel. Just kidding, Excel can get tough, Excel can get tough. Marshall says, do you think we can get air our first job as a data analyst with no experience at all? Yeah, I definitely think you do, I did it. I can do it, anybody can do it. Because I think I am probably out of everyone in this chat, you guys are probably all on some level smarter than I am. I'm just being honest. I don't, I talk about my wife with this a lot. I'm like, my wife is so much smarter than me, but she somehow, just because I've done well in my career does not make me super smart. And so I think a lot of the people out there do not give themselves enough credit for how intelligent they really are. Like a lot of you guys are way ahead of where I was four years ago. Like way ahead of where I was. And so I think you need to give yourself more credit. If you, even if you don't have experience, you can absolutely work your way to get a job. Do projects, try to get a job at like a nonprofit or some really small company that's willing to take a risk on somebody. Hustle, work with recruiters. I mean, it just takes a ton of hard work. I mean, I think that's the one thing that really makes me, has made me, I don't wanna say successful, it's made me a good data analyst. Is I just working nonstop. Which means, I don't mean that I work like 24 seven. I just mean I work super hard. I have a good work ethic. So I think that's the only thing that has made me be a good data analyst really. Daniel said I skipped your question at 1013. Sorry about that. I was not trying to skip any questions, but yeah, I don't know, may have graded out or something. There are, I do get things that say message retracted and I see some right now. I don't know what they were said before that. So sorry about that. Gerbrand commented back on what I said. Let me see what he said. I haven't read this yet. Trying to get this thing to focus really quick. It said, good, I'm excited. I hear so much about the importance of data cleaning and wrangling, but it's hard to see what they're actually talking about. Would be a great vid on it. Yes, I think it would be a great video. I don't think I have, I don't think I've, I don't think I had ever written that down. I should write that one down because I have a whole list of videos on like basically how advanced SQL gets, why SQL's important, stuff like that. That might be a good video. I don't know. Could be. We'll see. Maybe I'll make a video on that. Ooh, I accidentally just skipped around. I don't know where I am. Let's see. I'm trying to, some of these questions I've already answered, so I'm kind of skipping through some of these. So Riyad asks, for your masters, what would you go for, a degree title? You can list a few options if you aren't 100% sure. So, excuse me. I've thought a lot about it. And there's a few different degrees that I'm interested in. They're actually, I know I said earlier I wasn't gonna get a computer science degree. I know I said that, but you can't just take it face value. I say things all the time. I really am interested in computer science and if I can find a program that is much more catered towards beginners or people who are switching in a computer science degree because there are programs out there like that and I have found them. I'm just trying to find one that's a little bit more affordable. I might do that because I know how important a computer science degree can be and how much I can market that for myself. I've also looked into analytics like Georgia Tech's analytics program. Again, that's an online program really well. I've also really looked into MBA. And MBA would not just be for data analysts. It would also be for my YouTube stuff because my YouTube stuff is like trying to manage it's not really a business, but it's managing my time and creating videos and learning everything about money and stuff like that, which I'm just not that much about to be honest. So I think I've also thought about an MBA. So those are kind of the main three. I don't really think I'm gonna do a data science degree. It doesn't really peak my interest that much. Data science in general, I don't think is where I'm gonna go with my career, even though you didn't ask. Although Colzan did ask that in a question. I don't know if that was the next question, but it says, what is your next goal towards the career? I literally was talking about this like the other day with my wife and I said, my goal is to become the lead data analyst on my team. I wanna do that by next year and I'm gonna set that expectation with my boss. Honestly, I feel the people on my team are amazing. They're fantastic at what they do. I feel personally like I take a much more, a very big leadership role on my team and they come to me with a lot of questions and a lot of advice and things like that. I feel like I take a big leadership role and that may just be me. I'm gonna talk to my boss about it and be like, hey, here's what I think. I'd like to be here by next year. Let's count how can we make that happen? What do I need to do? So I'll probably be doing that at the beginning of this next year. So that's kind of my goal, short-term goal. That's my next short-term goal. Koa said, is the job market for data analysts in the next five years saturated? I'm afraid I'm not gonna be able to find a job if I don't have a major in computer science. It is saturated in certain fields. Certain fields have been impacted like, like hospitality, some jobs in like, look at like we work, you know, things like that where they used to have analysts and stuff that they don't have any, that that industry or certain industries are having a tough time.  Healthcare is not over saturated right now. And I keep going back to healthcare it's just because that's what I know best. I'm in healthcare, I know it the best. So healthcare and other fields like healthcare that are doing well, they're not over saturated. And if you don't have a degree in computer science, you know, that's okay. So yes, there are absolutely jobs out there to be had. I see new jobs postings all the time. I'm doing videos on job postings now. I'm sure you may have seen them. So yeah, there are absolutely jobs out there, I promise. It's just finding the right one in the place that you're looking for in the kind of job that you want. It's tough. Okay. Looking for questions that I haven't already answered. I'm gonna probably wrap up in the next couple of minutes, maybe 10 minutes, five, 10 minutes just because I do have some stuff I gotta do tonight besides this. Sorry guys. So I'm gonna go through and look at some questions. I'm almost caught up with the questions to be honest. I feel like I'm doing all right. Although I may not be able to get to all of them. Sorry guys. I'm seeing if there's any really big questions I think would be interesting. And I'm sorry, I am skipping some questions. I normally don't do that, but I've already gone like 30 minutes past when I thought I was gonna go. So now I'm just kind of cherry picking the ones I want to talk about. Hey, okay, this is a plug for myself. So this guy, Jtam said, could you recommend any good online communities to join for data analysts? That's data science communities. I have a Discord channel. And if you haven't joined it, it's Alex the Analyst Discord. If you go to my YouTube channel and click on the banner, there's these links. There's a Discord button. There's like 300 of us and we just chat about data analytics. We share personal projects. We share resumes. A lot of people, I do voice chat where I'll talk to people and just hang out with them at night. And I love doing it. And so if you wanna be part of like a data analyst community, go check that out because honestly, I have learned a ton from these people. I hope they've learned something from me. I'm not super helpful to be honest sometimes. So that's what I would say in terms of data analyst community. I think it's a really good one. And it is growing. We have people join up every day. And so I would join that to be honest. Christina asked, how old are you when you got into data analytics? I was 22. I had just graduated from college. I had gotten a job at, I had done an internship at a behavioral health hospital. Then I got a job at a non-profit as a caretaker. And I was just like doing basic stuff. And then I got a job as a data collection specialist and an analyst. And then that kind of changed my whole life. And so that was around when I was 22, I think. I think I was 23, if you remember. So many years ago. So long ago. Let's see. I know I'm skipping questions, guys. I hate doing it, but I'm doing it. I'm so sorry. Christina asked, what's my college degree is recreational therapy. At my college, recreational therapy degree was a stepping stone degree to go to a master's in occupational and physical therapy. And I wasn't sure what I was gonna do yet. But I had my degree. I did my internship. I could have gone back and got my masters. I kind of had everything set up to go do that. I just didn't. I fell in love with a girl, stayed in Dallas instead of moving back to North Carolina, which was where I was from. And yeah, the rest is history. All right. I think I caught up. I think I caught up well. Guys, I gotta be honest. I skipped some questions. I'm sorry.  I went 30 minutes over. I gave you everything you wanted. Just don't hate me for this. All right, that is gonna be all for today. I hope you enjoyed the ambiance. I should have, I actually could have turned this up. It's making noise in the background. You could have heard the fireplace going. I don't know. But I appreciate you guys joining. Tons of good questions. Lots of really good conversation, I think. I hope I helped. Honestly, I get so much joy genuine joy just from like answering your questions and being helpful. It really, it just makes me, it really just makes me happy. So I'm super glad to do this. I hope you guys have a fantastic Thanksgiving, Thanksgiving weekend going into the holidays. Be safe, be healthy. Please wear masks. I believe in that. If you don't, it's okay. You know, I'm an advocate for staying healthy. I want you guys to be healthy, to be good data analysts, to get a job, to be successful. And to write me and say, Alex, you helped me get a job and I will put you on my YouTube community board saying, you know, these people, these people made it and you guys did it. And I want to do that for you. For you. So when you get a job, please email me. Let me know. I'll put it on there. People need to know. So I see all you guys saying thank you in the chat. Thank you to you guys as well. You guys are awesome. It's not a squeaky chair. It's the fireplace. Fireplace. All right. Thank you guys so much. I appreciate you. I am signing off. I gotta go do some work or something. I gotta be productive tonight. This was productive, but I gotta be even more productive. All right. Bye, y'all. Thank you so much. See you maybe next month. Maybe or next year. We'll see. The next time we do a Q and A might be next year, which just blows my mind because 2020 has been a blur and has been insane. So yeah, to be said, I'm actually signing off now. All right. Goodbye, guys.