How to become a data analyst: Your 5-step plan

How can I become a data analyst?

  • Get familiar with the fundamentals
  • Commit to the process with a structured course
  • Hone your soft skills
  • Start networking
  • Refine your portfolio and prepare for the job market

We understand that changing careers can be a daunting proposition, so we've simplified the process as much as possible. You may move from wannabe data analyst to fully-fledged professional in just five steps. You might also be interested in this type of workshop on how to become a data analyst that we hosted. For the time being, here's your step-by-step action plan!

Step 1: Get familiar with the fundamentals

This first step is all about immersing yourself in the world of data analytics and getting familiar with some of the key tools and principles. There are two components to this step:

  • Embracing the theory behind data analytics
  • Getting hands-on with some key data analytics tools

Before you do anything else, learn everything you can about data analytics theory. Read about how data analytics is used in the real world and get a sense of the kind of analysis that a data analyst might conduct. We recommend researching the different types of data analysis—descriptive, diagnostic, predictive, and prescriptive—and becoming familiar with data analytics techniques like regression analysis, factor analysis, cohort analysis, cluster analysis, and time-series analysis as a starting point for your reading. This will provide you with a solid theoretical foundation upon which you may build those crucial practical abilities. Start with our ultimate introduction to data analytics for a comprehensive and approachable starting point.

Step 2: Commit to the process with a structured course

Now it’s time to get serious about your career change. While the internet is full of wonderful and free resources, it won’t give you the structured approach or the hands-on practice that you need. If you want to become an employable data analyst, the most effective (and rewarding) way to do so is through a specialized program or data analytics course.

The good news is, there are lots of courses to choose from. With the rising demand for skilled data analysts, we’ve seen a surge in courses and boot camps that promise to take you from data newbie to job-ready professional. However, not all data analytics courses are created equal, so this step requires extensive research. When choosing a program, it’s crucial to find a structure that complements your schedule (especially if you plan on working and studying at the same time) and fits your budget.

Step 3: Practice your soft skills

In addition to your chosen data analytics course, there’s plenty you can do to enhance your learning experience. While the course takes care of those all-important hard skills, it’s a good idea to start honing your soft skills.

If you need a quick refresher on the most important soft skills a data analyst should demonstrate, refer back to our list in section three. Armed with this list, think about the soft skills you’ve already perfected and identify those that might need more work. Perhaps you’re excellent at conducting research and solving problems as part of your current role but haven’t had much experience in giving presentations. If there’s an opportunity for this kind of development within your current workplace, grab it with both hands. Offer to run a small research project and present your findings to the team, or put your analytical mindset to work by offering to tackle a specific business problem.

This phase will necessitate some ingenuity, especially if your current position does not instantly offer itself to such possibilities. If you don't think you'll be able to improve particular soft skills in your current employment, look for other options. Informal gatherings, for example, are a great opportunity to hone your presentation abilities. Although it may appear insignificant, this stage is critical in your quest to become a data analyst. When looking for jobs, you want to be able to list as many of the required talents as possible on your CV—and having the correct soft skills can often give you a significant edge.

Step 4: Start networking

It’s the golden rule for every industry: establishing a good network and making connections is absolutely essential if you want to get your foot in the door. While many of us dread the idea of “networking”, it doesn’t have to be as uncomfortable as it might sound. In fact, there are many different types of networking, ranging from a friendly message on LinkedIn to a full-on conference circuit.

If you’re not a natural-born networker, it might be tempting to skip this step. However, it’s important to surround yourself with people who you can learn and share experiences with—not to mention the possibility of a good connection leading to a future job opportunity. If you’d like some tips, check out this guide on how to network like a pro.

Step 5: Refine your portfolio and prepare for the job market

The fifth and final step towards becoming a data analyst is to refine your portfolio and prepare for the job market.

Your portfolio is arguably the most important asset you’ll have when it comes to applying for jobs; it showcases how you work and demonstrates to employers that you’ve not only mastered the right practical skills but that you know how to apply them in the real world. As already mentioned, the right data analytics course will have you working on practical projects and guide you in the creation of a professional portfolio. Your mentor can also help you to polish up your portfolio and give you tips on how to present it. You can learn how to create a data analytics portfolio in this guide. And, if you’re not sure what to include in your portfolio, check out these nine data analytics project ideas.

Aside from your portfolio, you’ll want to make sure that your online presence is optimized for your new career as a data analyst. This includes updating your LinkedIn profile to highlight all the relevant skills and tools you’ve mastered and including a summary of the kind of role you’re looking for. Again, a good data analytics course will help you optimize your online presence and devise an effective job-search strategy.

Once you start applying for jobs or data analyst internships, it’s a good idea to prepare for the interview process. Although every company will have its own interviewing techniques, there are some common questions you can expect to be asked when interviewing for a data analyst position. To help you prepare, we’ve put together some of the most common data analytics interview questions (and how to answer them) in this guide.

It’s also worth getting familiar with some common data buzzwords.

6. Key takeaways and next steps

That just about concludes our guide on how to become a data analyst. You now have a clear, step-by-step plan to follow in order to learn the necessary skills and break into the industry. Before we go, let’s recap your plan of action:

Get familiar with the fundamentals: Learn about the different types of analysis and practice using some formulas in Excel.

Sign up for a data analytics course: Opt for a certification program that offers expert mentorship, career coaching, help to build your portfolio, and a job guarantee.

Hone your soft skills: Refer back to our list in section three and make sure you can demonstrate all of the soft skills needed to become a data analyst.

Start networking: Join data analytics groups on LinkedIn, get involved in your student community, and consider attending local meetups.

Refine your portfolio and prepare for the job market: Work with your mentor and your careers coach to get your professional portfolio ready, optimize your online presence, and start practicing for interviews.

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