How to get a data analyst job with no experience (data analyst roadmap)

Straight out of college, I had no idea what I wanted to do. I chose to major in sociology and business and landed my first job as a business consultant. I did that for five years before realizing that I wanted to become a data analyst and along that process, I made a lot of mistakes. I finally landed my data analyst role and eventually became a business intelligence engineer at Amazon, which is what I do today. So through my data journey, I get asked a lot. Is it possible to become a data analyst with no experience? And my answer is absolutely yes. And I say this because you don't need that computer science degree. You don't necessarily need the work experience. There is a path you can follow to become a data analyst and I will be explaining that in today's video along with the most common three mistakes that people make along the way throughout this video. The data analyst journey can be broken down into three steps. The first is learn the data analysis skills. The second is build a portfolio and then you'll want to start applying for data roles. Starting with learning data analysis skills. What is data analysis? It's a process of understanding data, being able to manipulate and analyze it and then presenting your findings. I have a video which goes over the workflow of a data analyst, which I'll link to this video if you'd like to learn more about what the workflow is. The easiest and most accessible tool to learn data analysis is Excel. Excel has a capability for you to be able to clean data, analyze it through VLOOKUPs, do presentations, creating charts and graphs with it and it is the first tool that I would recommend you start with because if you know the fundamentals of being able to analyze data, that is a skill that you're going to be able to translate into the other tools. If you're unfamiliar with what a database is, what SQL is, think of doing your laundry. When you do laundry, you put all your dark clothes with your white clothes in a hamper, which is your database and you'll basically want to separate the two, but how do you do it quickly? What you can do is you can run a query and that basically lets you take pieces of what you need and sort the data, which is sorting your laundry dark versus white. Now, once you get a handle of Excel and SQL, you'll want to move on to a visualization tool. The skills that you practiced in Excel building a chart, you can automate that through BI visualization tools such as Tableau and that is the tool that I would recommend you start with. There is no need to try to learn all the visualization tools out there because if you get a handle and sense of how to work one, that is a very transferable skill that you can move to another. My first visualization tool back in the day was SSRS using Microsoft tools, and I've been able to translate that skill set into QuickSight as well as Tableau, so don't feel like you have to know it all. Once you have data visualization now, you'll want to move on to a programming language like R or Python. I would recommend starting with Python because that is a skill set that will let you level up later in your career if you want to. Python is also used by software engineers for coding. That's a very transferable skill that I would recommend you start with. However, if you're a beginner, don't worry about trying to learn everything that Python can do because it can do a lot. You only want to focus on Python for data analytics specifically, and that includes learning libraries such as Pandas and being able to read the syntax. Now, why did I start with Excel, SQL, Tableau, and Python? Because I was able to land my first job with just Excel and SQL. Just those two skills alone will get you very far in the data analyst industry, and don't feel that you have to be the master at it to apply to roles. Once you're on the job, it's very common to Google how to query certain data sets, how to sort and find and merge data, and that is something that I did very commonly in my first role as well as my peers. Just get a handle of what data analysis is and work on Excel and SQL. You may be thinking, what about math and statistics? I've seen a lot of blogs mention that these are two skill sets you're really going to need, and for an entry-level data analyst role, I would say don't focus so much on these as they are skills you're definitely going to need to level up, but not necessary to get your foot in the door. Now, once you've learned some data analysis skills, you'll want to build a portfolio, and this is important for two reasons. The first is you want to be able to apply your learnings. You don't want to just practice it. You want to be able to actually apply it to a project, and secondly, if you are coming with no data experience on the job, it's going to be really important for you to be able to showcase your work, and this is where a portfolio will really help you. If you have opportunities in your role to practice data analytics, such as maybe there's a report your team frequently makes every week, every month, maybe you can consider creating that with data, or if you absolutely don't have access to data in your current role, you can go to Kaggle, which is a great website that has data sets and projects in there for you to practice and build up your portfolio. Two tips while you're working on the portfolio is don't stop working on the portfolio, and by that I mean continuously add to it because you are going to use this throughout your data analyst career. I still maintain my portfolio, which I use for promotion conversations to justify why I deserve a raise, as well as when I'm prepping for an interview, I already have my work that I can leverage and refer to to justify why I deserve the job. My second tip is as you're working on the portfolio, you want to focus on answering these five questions, which will really help prep you for the interview. The first is, what is the problem statement? What is it that you're trying to solve? How did you do it? What tools did you use? What did you do specifically? Are there any deliverables? As well as what is the impact of this project? When you have about three to four projects in your portfolio, you'll want to then get ready to apply for data analyst roles. Now, when you're working on your resume, you don't want to focus on just your technical skills. You also want to include your soft skills. If I was working on my resume, I would make sure if I had zero experience to include my technical skills such as SQL, Excel at the top of my resume, along with any portfolio projects that I have. But within my job experience, within my school experience, I would also make sure I include my soft skills. Having interviewed data analysts in tech, I noticed that soft skills make up a large part of whether you're hired or not. Yes, you have to pass the technical test, but if I'm debating between two candidates and one is okay technically, but has really strong leadership skills, communication skills, and the other candidate really lacked those soft skills, but maybe had better technical skills, I would choose the person with the stronger soft skills. You 100% have soft skills that you can include such as being curious, communicating, being able to present in front of an audience, and those are all skills you want to highlight. Let me know in the comments if you'd like to learn more interview tips because there are just so many more that I could include, but I will save that for a separate video. Now before I talk about the top three mistakes when transitioning into a data analyst, I'd like to ask you to like and subscribe this video if you really got anything out of it, and I'd love to hear in the comments if there's any other types of videos that you're interested in or if you're in that data analyst journey and how it's going. The top mistake I see is watching a whole bunch of tutorials without applying the skill. Data analyst is a skill that requires hands-on experience and it's just like if you're learning to play soccer for the first time. You wouldn't sit there and watch a whole bunch of soccer videos. You would actually want to go out there and kick a ball to turn that into a skill, and the same goes for a data analyst. Rather than sitting there and watching all these Udemy or LinkedIn videos, you want to be able to apply it and that is really where the portfolio comes in. Imposter syndrome. When I was first applying for data analyst role, I really felt that I wasn't qualified even after I got the job. I felt that I knew less than my peers and eventually as I leveled up my skill set, I became a manager of the data analytics team and after all this, I'm realizing that I should have been more confident in my skills from the start. If you get to the point where you're getting interviews for a data analyst role, don't think that you're not qualified. That means they already think you are and all you have to do is show them that you deserve this role. Letting industry knowledge limit you. When you're first applying for data analyst role, you may think that, oh, I have no experience in finance. I can't apply for this role or oh, I have no experience in tech. I can't apply for that either. But that's not true. I've been able to move industries starting with healthcare over to tech as well as a lot of my peers that I'm working with today. They came from various different industries and are now working in tech and the reason for that is because data analytics is a skill that is very transferable across industries. If you're considering a role in data analytics, I would say go for it. The most important lesson I have in this video is to take action. There are going to be a lot of people watching this video that have the idea of being a data analyst but never do anything because they either have doubt, fear, or are just lazy. Meanwhile, there are the people who take action and are going to make money as a data analyst not because they're smarter or more technically savvy but just because they took action. If you get anything out of today's video, it is to go for it. Don't let this just be an idea. Make it into something by taking action and I can't wait to see you on the next video.