 What's going on everybody? It is 2023 and in this video I'm gonna help you become a data analyst. We're gonna start at the very beginning assuming you haven't started this process at all of becoming a data analyst. If you already have, you can kind of fine identify where you are in this process and then go from there. Now before we dive into everything I want to warn you, I will be mentioning my own channel a lot in this video. I have videos and playlists on just about every single topic that we're going to be talking about today. I'll have all the links to those videos in the description so you can dive into those topics more in depth. So I hope that's okay and it's all completely free. I've been building this out for the past three years and honestly you can probably get 90% of the way to learning everything you need for data analytics just on my channel. So now that I've warned you, let's jump into number one and that is learn the data analyst skills. Now there are literally a hundred different things that you can learn for data analytics. You can learn things like Alteryx or a cloud platform or different programming languages but there are some core skills that I recommend you start out with before kind of branching into some of those other skills. The number one skill that I always recommend people start with is SQL. SQL is just one of those fundamental skills I think everybody should learn. Even if you don't use SQL, you'll use some variation of SQL if your company has a large enough data set. SQL is used to actually query and retrieve data from a database so if your company collects data which every company does, they're going to put it somewhere to store. It's usually stored in a database and SQL is how you get that data from the database. I think SQL is also fairly easy to learn which makes it really good when you're just starting out. I have several playlists dedicated to SQL starting from beginner all the way to advanced and you can learn all of that for free. One other reason why I think you should learn SQL first is that a lot of companies interview or have a technical interview during the interview process on SQL. That's something that really caught me off guard when I was first starting out because I thought it was going to be more behavioral. I didn't even know what a technical interview was so knowing SQL actually became a really important part of interviewing and getting a job as a data analyst. The second skill that I will learn is a business intelligence tool like Tableau or Power BI. Now there are a ton of different BI tools. I can literally name 10 off the top of my head that I've used throughout my career but what I will say is that learning something like Tableau or Power BI is pretty transferable to almost all those other BI tools. They're all fairly similar in how they do things and how they show and display the data. You most likely won't have a technical interview asking you about Tableau or Power BI like to build something for them. That usually does not happen but the combination of SQL where you can query your data and then taking that data to build something that is a really really great combination to learn right away. I have an entire series on both Tableau and Power BI with projects on my channel. The third skill that I would learn is Excel. Now most people have used Excel. They know what Excel is and how it's used but it can be used a little bit differently for a data analyst. For example in Excel a lot of people haven't cleaned data in Excel or built charts and graphs using Excel and those are things that data analysts would probably do. Excel is also just a fundamental skill that every company is going to expect you to know so I have an entire playlist dedicated to Excel to actually walk you through how to use it for data analysis. The fourth skill that I recommend you learn is Python. Now a lot of people will have Python higher up on their list. They only use Python. They don't use SQL or a BI tool. They just do everything in Python. Now Python is a fantastic tool. You can use it to manipulate your data to create data visualizations and a ton more like web scraping and regular expression and a hundred different other things but it can be kind of hard to learn. It took me a long time to really learn the basics very well. That's really the only reason why it is farther back. I feel like SQL and a BI tool are really easy to learn and really pack a big punch whereas Python can be quite tough to learn in my experience and you may not use it as often as you would something like SQL or a BI tool. If you're interested in learning Python I have an entire series dedicated to Python as well as projects that you can build. Again I warned you there's gonna be a lot of self promotion in this video. I have videos on just about every single one of these topics. The fifth and the last skill that I recommend you learning and this is the only one that I don't have a series on yet I will make those is learning a cloud platform like AWS Google cloud platform or Azure. There's no denying that these platforms have played a huge impact in how we use data as a whole in the data analyst industry. They can be kind of tough to learn though if you aren't using it hands-on in an actual job. I think that learning a cloud platform is already something that most people should start working towards because in the future it's only going to become more prevalent. Now where can you go and actually learn all of these skills that you need to become a data analyst? Well the number one place I recommend of course is my channel. I have free tutorials on all of these skills and a lot of other topics and I think it's just a really great place to start. The next place that I recommend you looking at is Udemy. I recommend Udemy especially if you're just starting out because it's pretty cheap. You can buy an entire course entire sequel course for $10 or $15 and they have courses on every single one of these skills and I just recently made a video called DIY data analyst curriculum using Udemy for under $75. So you can create an entire curriculum to learn all of these skills for under $75 which is just amazing. The next place I'm going to recommend you look is Coursera. Now Udemy is fantastic. They have really good instructors and good courses but as a whole I find that sometimes Coursera just has more professional or better content. Coursera is a bit more expensive though. You're looking at $59 per month for all of their courses or you can pay upfront an annual fee of $399. So again it's just a lot more expensive. I moved to Coursera once I started having a data analyst job and had a bit more money but when I was first starting out I just couldn't afford it so I went to Udemy and it was a really great place to start. There's also places like Data Camp and Data Quest that kind of gamify learning and they're more text based so all these other platforms Udemy Coursera and me they're all video based but if you like reading Data Camp and Data Quest are a lot more of text where you can learn it by reading it and doing it. After you learn all of these skills the next thing that I recommend you do is actually build projects with those skills. Now what is building a project actually mean? It means taking a skill and then building something out of it that you can then show a potential employer. For example if you went through and learned Tableau you go and take a data set and you could build a visualization and a dashboard in Tableau and that would be a project. With these projects you can build something called a portfolio and I usually call it a portfolio website. A portfolio website is a website that you create where you store all of your projects and then you can share that with recruiters and hiring managers so that they can see all of your work. Now do you absolutely need a portfolio to show employers? No you don't but it does help in two different ways. The first thing that it may do is actually help you land the interview. If you have a link on your resume and they click on it they may see your skills and see your projects and be like man this person really knows what they're doing this is exactly what we need. The second reason that I recommend building projects is because most likely during your interview you're going to get asked questions like how have you used SQL how have you used Tableau and if you don't have any experience in that you're just going to say well you know I've taken courses to learn it but with a project you can be a lot more specific. You'll be able to say well I actually just built out this project in Tableau I took the data and cleaned it in Excel and then I put it in Tableau and built out this dashboard and here are the insights that I found from this data set. It's just a much better answer and as a hiring manager myself I can tell you that it is definitely beneficial to build out these projects. The next step that I recommend you take in becoming a data analyst is building a data analyst resume. The resume to say the least is extremely important it's what's going to actually allow you to land an interview to potentially get a job. Now if you were like me when I was first starting out I had a resume it just had nothing to do with data analytics so how do you make a data analyst resume if you don't have any experience as a data analyst? Well you are asking the perfect questions because the very first things that we talked about are what are going to go on your resume those skills and those projects. If you have no experience or degree like myself who has a recreational therapy degree if you have no background in this it can be really daunting to kind of display that you know what you're doing and that a company should hire you so what I usually recommend is right beneath your contact at the top you put your skills and your projects that you built out on your resume. Things like work experience and education should go on your resume as well but just a little bit lower. You want them to see those things before they see that your last work experience was at Domino's and you have a degree in marine biology it's just not relevant to data analysis and if you put those things at the top they're probably going to rule you out right away. The fourth step to become a data analyst is actually implying. You have the skills, you have the projects, you have the resume now you're ready to start applying for those data analyst jobs. Now there's a lot of different opinions on how you need to go about applying for data analyst jobs but I'll give you my take on it and this has been the most successful for me in my career. The first thing that I want to mention is actually what I would not do which is just blindly apply on Glassdoor, Monster, Zip Recruit and all these other platforms to just any data analyst job that you can find. Now I'm not against this I think you should do that but I don't think that's the only thing that you should do because the chances of you getting a call back or actually hearing something back are extremely low. To really increase your chances of becoming a data analyst I highly highly highly recommend working with a recruiter. A recruiter is literally someone who is there to help you find a job. Now when I first started out I didn't understand what a technical recruiter was at all and I was kind of nervous or scared to work with him but it's actually pretty simple. A company has a position that they want to fill and they don't want to spend hours and hours and hours to find someone to fill that position so they hire a recruiter. A recruiter is going to go out and try to find someone to fill that position aka you and so if you go and talk to that recruiter and they have a position that opens up they will help you get that interview and then if you get a job let's say for $50,000 the company is going to pay that recruiter let's say 10% of your salary so they'll give them $5,000. So you don't actually lose or have anything to lose using a recruiter. You can reach out to recruiters in several ways and I've done every variation but I'll tell you my most successful way which was using LinkedIn. There are tens of thousands of recruiters on LinkedIn. I made an entire video of how you can reach out to recruiters and what to say to recruiters on LinkedIn to help you land a job so be sure to check out that video when you actually get to that point but you can also just cold email and cold call these recruiting companies but to me it's just not as effective as reaching out directly on LinkedIn. And this is just a bonus one the last thing that you need to do is accept a job offer. So in step number four after you apply to those jobs you do actually have to go in interview and then get a job offer which you will accept. I just thought I mentioned that just in case that was not super clear. Now that was a lot of stuff let's talk about time frames to actually complete all of these things. Now doing all of these things from scratch is going to take a while but let's break it down by each step and see how long I generally think it's going to take. Let's start with step number one which is actually learning the skills. Now just to be upfront this one probably is going to take the longest for most people. For most people to learn all of these skills it's going to take around three to four months. Now if you don't learn a cloud platform and Python which are the last ones that I recommend and you just focus on SQL, ABI tool and Excel. I think you can do that in under three months. That is very dependent though on how much time you have to study. That time frame is more for someone who has several hours per day maybe three hours in the end of the night after you go to work. That is someone who has quite a bit of time to dedicate to learning during their week. Of course that time frame is going to take longer if you don't have as much time to dedicate to learning. Now let's look at number two which was creating projects and a portfolio of projects. From my experience when you're first starting out it takes a lot longer to actually create these projects. It can take one or two weeks per project. I usually recommend people doing three to five projects in their portfolio before they start applying and since they can take anywhere from one to two weeks you're looking at anywhere from three to six weeks. The next step was to create a data analyst resume. Now in my opinion this one should take the shortest out of every single step here because you're really just kind of reformatting a resume or creating a resume. You're just adding skills, you're adding your projects and then kind of reformatting it to make it look nice. This should hopefully take under a week but if you use something like a professional service where they help you build a resume it can take one to two weeks. The two last steps which kind of go hand in hand or step four and five which is actually applying for jobs and then landing a job. Now this process can take as little as a month or it can take as long as six months or a year. It really depends on how you're applying, where you're applying and just the kind of luck that you're having with actually landing interviews. I've seen people who have never had any experience land a job within a month of starting to apply and it's incredible, it's amazing, but it doesn't happen too often. You're usually looking at around two to four months on average to land your first data analyst job. If you put all of those together and kind of average everything out you're looking at around six months total for the entire process. Now I don't want that to discourage you okay 2023 is a long year, you have a lot of time and it doesn't have to take six months you could do it faster you could do it in three months and just prove me wrong. But if you are really focused and you are really driven to become a data analyst this year I know that you can do it. Now to maybe boost your spirits and make you feel a little bit better I didn't know any of these things when I first started out. I didn't have anyone telling me kind of a plan on what to do. I had to go out and figure all these things out by myself and it took me almost a year to land my first real data analyst job. So with all that being said I hope that this video is helpful. I hope you now have a path on how to become a data analyst this year and that my channel can be a big part of that. So thank you guys so much for watching. I really appreciate it. If you liked this video be sure to like and subscribe below and I'll see you in the next video.