 What's going on everybody welcome back to another video today We're gonna be discussing the data analyst career path more specifically We're gonna be talking about how to get the job So how to become a data analyst and then where do you go after that? What are the steps that you should be taking after you are a data analyst to advance your career even further now? Especially with number one of how to get a job I have already done a ton of videos on these subjects if I've done a video on that already I'll put a link right above my head so you can click on it That will go a lot more in depth into the subjects that we're gonna be talking about But let's begin with number one of how to become a data analyst before anybody can become a data analyst The first thing that they have to do on that career path is actually learn the skills And so the first thing that I want to talk about is the skills that you need in order to become a data analyst I think the three biggest skills that are must-haves are SQL, Excel and then Tableau or Power BI or a data visualization tool Some things that would really help but may be a little bit more challenging at first are things like Python or a Cloud platform like AWS or Azure But those things typically come with time and experience and so as you get further along in your career You typically do pick those things up as you go Learning these skills are typically the very first thing that you have to do in order to become a data analyst And the very next thing that you have to do is actually create a resume Your resume is basically a snapshot of who you are to an employer or to somebody who might hire you And so it is super important that you get it right You want to make sure that you portray yourself as somebody that they want to hire And so there are a few key things that you want to remember when creating your resume The very first thing is to highlight your best skills If you are super good at SQL, you should have SQL listed at least three times in your resume Probably in your summary in your skills then in your job experience or a portfolio project at the least Next we want to remove irrelevant jobs and skills Let's say for example, you were a chef the past five years and now you're trying to become a data analyst for whatever reason You probably don't want to showcase all of your skills that you've learned as a chef You want to now focus on all the data analyst skills that you've learned since then as you're making you that transition to becoming a data analyst One caveat to this is if you had a previous job that had a lot of domain knowledge So let's say for example, you were a nurse for five years a nurse doesn't have a lot of data analysts experience But if you were going to work at a healthcare analytics company, your nursing background may actually be very useful Lastly, we want to keep it neat and professional I see a lot of resumes and a lot of the feedback that I give is that their resumes are not very modern They're sometimes stuck in the 80s or 90s So having an updated resume will really help another big thing as I see people with either headshots or really loud colors on their resume And in general, I just recommend keeping it neat and tone down colors like black and white Next you're gonna want to create a portfolio a portfolio is basically going to show an employer What you are capable of the skills that you have the process that you take and what they will get if they decide to hire you And typically I recommend anywhere from two to five projects and a lot of people ask me how to actually create a project How do you create a portfolio in general here are the steps you're creating a portfolio project number one is actually getting a Day set or collecting your data so you can either scrape data from the web Or you can go and get a data set from something like Kaggle or Google next You want to clean and transform the data so that's usable later And you can either do that through pandas in Python or you can do that in sequel as well After you clean your data if it's not already in sequel I recommend putting it into sequels that you can build your views and show off your sequel abilities as well And then you're gonna connect your data visualization tool to your view and then you're gonna create your visualization now There are a lot of variations that you can do in there with collecting data the way you transform it the way you actually visualize it But in general that is kind of the basic outline of how you create a portfolio project And the very last thing is how do you actually show your employer that you have a portfolio? Well, you can host it either in GitHub or you can create a personal website And then I recommend just putting the link in your resume now the next thing that I personally recommend is working with recruiters I worked with a lot of recruiters to actually get jobs and now I'm actually working with recruiters in order to hire people And so I see how valuable recruiters actually are in the hiring process And so I think that if you haven't already should really think about working with a recruiter And there are really easy ways to do this The first thing that you can do is actually just set up a LinkedIn and LinkedIn is really good because a lot of recruiters look on there To hire people and to get people in for interviews And so what you can do on your LinkedIn profile is just say that you are looking for jobs as a data analyst or entry-level data analyst And have them reach out to you with opportunities Now if you don't feel like waiting you can always call and email recruiters I really recommend calling first and actually talking to the recruiter to let them know where you're at and what you're looking for And so when you send them your resume they can at least associate you with that resume Maybe help you find a job a little bit faster and lastly you're gonna work with recruiters to get interviews I really think that working with recruiters helps you get a lot more interviews than just applying on your own A lot of times these recruiters have inside information or are working directly with companies And so the jobs that they're looking for are ones that they specifically know about and know if you'd be a good fit for that position The next thing is actually get the interview and then eventually hopefully get a job And so in order to do that I highly recommend preparing for your technical questions typically for entry-level data analysts The technical questions are mostly gonna be on sequel at least that's what I found then as you get a little bit further Along it might be on Python as well And you should also prepare for those common questions that are gonna come up in any interview One of the questions that people mess up the most is what is my greatest weakness? It's just something that apparently stumps everyone, but it's asked in every single interview So I highly recommend just writing down a script So when you get asked that question you have a really good response and lastly you want to dress professionally and be confident Now it's easier said than done for a lot of people to be confident Sometimes people are nervous, but I promise you confidence goes a long way So just fake it for the 30 to 45 minutes that you're in that interview So you've got the job you're a data analyst and you've been a data analyst for a few years now Now what's next? What are the things that you should be doing to advance your career after that? There are a few different paths and we'll talk about each one after this But something that every single person should be doing is actually advancing their skills And some of the things that I highly recommend learning are things like Python or R or you could learn ETL Which is extract transform and load and that's how you actually get the data from the source into your warehouses or into your databases And have listed some options like SSIS, Azure Data Factory and AWS Glue, which are some popular ETL tools You could also learn data modeling You can learn predictive modeling and analysis You could learn data warehousing or you can venture into the data scientist skills Which is some of the machine learning stuff and NLP which are used a lot for data scientists Now once you've been a data analyst for a while There are a few different paths that you can take and one of these paths is going back to school And this is a really good option Especially if you're going back for a master's degree a master's degree can really be beneficial in your career long term And there are a lot of degrees that are very relevant to data analysts the first one being computer science I think that is probably the most popular one of the most beneficial one that somebody can get Another degree is something like information systems statistics There are even data analyst degrees or data science degrees now that you can get that are very specifically geared towards data analysts or data scientists And so going back to school is a very real option You can even do that while you work a lot of people are doing online Especially during COVID a lot of people are doing online master's these days And so it's becoming a lot less of a stigma to actually get your master's while you're working And so I highly recommend that especially if your company does tuition reimbursement or they'll basically pay for your college The next path is to just get promoted and continue being a data analyst You typically start out at an entry level position And then some positions that you can get as you grow in your career are things like a mid-level and senior level data analyst Which basically means you're a data analyst but much more skilled than a typical person just starting out in the career The way that that differs from a manager is a manager is typically organizing the way people do work in the most efficient way Where a lead or a principal data analyst is typically doing all the work of a data analyst But they have data analysts under them that they help guide and mentor But they also help them get their work done so there's any blockers or technical issues The lead data analysts can help them get through those things And as we mentioned earlier there's a data analytics manager And typically that person is not doing the grant work They're more on the managerial level where they help decide what projects are the most important And the ones that'll have the biggest impact on their company And if you keep getting promoted you might even be the director or the VP of analytics Which for a lot of people is a huge goal and something that a lot of people aspire to And basically this is just a rundown of some of the jobs that you might get If you continue to get promoted as a data analyst And the last path is actually pivot jobs As a data analyst we work with a lot of tools and a lot of softwares And so what we do overlaps with a lot of different jobs that you might be interested in So take for example, you really like the ETL side of things Maybe you'll go and become a data engineer But here are a few of the jobs that you might pivot to as a data analyst Something like a data scientist, a BI analyst, a data engineer, a data architect, a DBA Or a database developer I plan on making a full video about all these jobs and how you can transition to them From a data analyst to that position Because as much as you love being a data analyst There might be a better job for you and for your career long term Now we will say that the path of getting a higher education May actually overlap with these other paths Because as you're getting an education you can pivot jobs Or use that degree to pivot jobs Or you can use that degree to actually get promoted And make it all the way up to that VP level But that is all I've got for you today Thank you guys so much for watching I really appreciate it If you haven't already, be sure to like and subscribe below And I'll see you in the next video