The fastest way to become a data analyst in 2024 (my experience)
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Hello, everyone! In this video, I will share my perspective and experience on how to quickly become a data analyst, how to learn data analytics for free, and get a job. My name is Maria. I am a data analyst. I did not receive any university education in the field of analytics. I learned through various free courses, internships, and later worked in a marketing agency and an IT company. Now, I am pursuing my own projects.
First, I recommend researching the job market. It's important to understand the skills and knowledge that the data analytics job market demands. This is useful not only at the beginning of your career but also regularly at every stage of your development to stay in trend. In my Telegram channel, I often get asked, "What skills are needed for a beginner data analyst?" You can read about it online, or you can ask working data analysts. But the most reliable way is to independently analyze the market because materials become outdated, and many analysts only know what their specific company requires.
Open a job search website. Look at job listings. Analyze job postings in small companies, medium-sized companies, and market leaders. See what skills are predominantly in demand, and which tools are most commonly required. Look at a minimum of 50 job listings to gain a good understanding. Here, it's important to note that in the field of data analytics, there are many different specializations: product analyst, web analyst, marketing analyst, SQL analyst, Power BI analyst, and so on. There are numerous options, and it's essential to determine what you want to focus on.
The next recommendation is to find an internship, even if you currently have no knowledge or experience. In this case, you won't need to pay for training; instead, you'll get paid for learning and performing tasks. However, there is a downside - there are very few internships that accept applicants with zero experience. Some internships require people with some prior knowledge, often involving a foundation in mathematics, SQL, or Python. But there's a life hack to expand your options: consider switching to an analyst role within your current company, if they encourage such transitions. In reputable modern companies, they usually respond well to this because they don't want to lose a talented employee.
Next, whether you've found an internship or not, you'll still need some form of education. Your market analysis will help you find a suitable course that teaches the skills in demand. It's important to distinguish between basic courses that provide fundamental data handling principles and introduce you to some analytical tools. For example, a course like Google Data Analytics, which I discussed in my video, is suitable for all data analysts, regardless of their specialization. There are also specialized courses that focus on specific analytical skills, such as Power BI and others. These courses are beneficial if you want to enhance a specific skill and can be taken after completing basic courses.
There are many free courses available, and I've mentioned some of them in this video. I often share these resources in my Analytics Telegram channel. In any case, the course should align with the market's requirements and be suitable for your preferred learning format. By "suitable format," I mean that courses that consist of 10-hour videos in which an instructor talks about various topics without practical exercises might not be suitable for everyone. Personally, I prefer courses in the format of Kaggle, where there's a short block of information (10-15 minutes), and then you practice in a cloud development environment.
The next piece of advice - Pay attention to how you learn. If you learn only by studying theory, you won't learn anything. The most important thing is to work on real tasks. If you've found an internship, that's great. You'll be working on real tasks one way or another, and in this case, you'll need theory.
If you haven't found an internship or job yet, what can you do in this case? The simplest solution is to use various simulators for some skills. For example, for practicing SQL and Python, there's an excellent simulator called Hackerrank. For Power BI, you can use DataCamp. For practicing Google Analytics, there's a test account available.