How to Become a Data Analyst

Companies in every industry need to back up their big decisions with numbers, and it all comes down to data visualization and prediction. If you like the challenge of telling a story through variables and algorithms, now is the time to build a career in data analysis.

Curious how to build on your math skills and start a long-term career? Here are the 5 key steps to becoming a data analyst, followed by some tips that will help you showcase your skills (even without previous experience).

Do your research.

There are a variety of data-heavy roles that all have promising job outlooks, including:

• Business analyst
• Financial analyst
• Data scientist
• Data engineer

You don’t have to decide on a specialty just yet, but a general understanding of the different career paths within data could help you focus your job search, as well as the skills you learn. If you see yourself as a business analyst, you’ll need to know all the data basics, plus how to calculate compound interest. If you’re fascinated by machine learning, consider taking your math knowledge to an even higher level as a data scientist.  

Read some job descriptions, explore the skills involved in each specialty, or even reach out to local data professionals to hear first-hand what their job looks like day to day.

Get the education and skills you need to become a Data Analyst

Many start out with a Bachelor’s degree, which could make you a more competitive applicant for most jobs, but isn’t required. There are now specialized data degree programs, but you can also enter the field with a related degree like math or economics.

With or without a degree, there are some necessary skills every data analyst needs in their arsenal, including:

• Math (especially statistics)
• Data management and advanced Excel functions
• Programming knowledge (SQL, Python and C++ are all valuable for data analysis)

Some of these can be self-taught, at least on a basic level. But we recommend partnering with a seasoned data mentor and working through a structured data analytics course. Having an expert resource at your side as you learn will help you make sense of the underlying concepts, and how they apply in real-world scenarios.

Create your portfolio.

A strong data analysis portfolio shows hiring managers what you can do, and helps them see the value you’ll bring to their team. It’s just as important as your resume, if not moreso. So invest some time into it, and create a portfolio that demonstrates all of your skills.

• Prove that you can research, analyze and visualize. Just about any data analyst position you apply to will require all three of these skills, so show off all of them. Draw attention to all the different data sources you referenced, why you chose SQL to run your analysis, and how you pulled it all together in a crystal-clear dashboard.
• Show your full range of hard and soft skills. Showcase projects that display your technical abilities, and also highlight your soft skills like communication and collaboration. Data analysts often partner with engineering, marketing, finance, and sales teams; hiring managers appreciate candidates who seek out other perspectives.
• Choose work that’s relevant to the job. If you’re in the early stages of pivoting to data analysis, then you might not have enough projects to tailor every single application. But if possible, try to tailor your portfolio to the job by using projects with the most relevant types of datasets. If the open position is expected to partner with Sales, then you’ll want to include any projects that used SalesForce reporting.
• Use a format that appeals to recruiters. Post examples of your work online using tools like GitHub or a personal website. Typically, you’ll want to share 3-5 projects: enough to show a diverse skillset, without overwhelming the hiring manager with too much information.

Build a professional network.

Face-to-face interaction is valuable, but it’s not the only way to meet other data nerds. It’s easier than ever to introduce yourself remotely, so don’t sweat it if you can’t make it to every data meetup.

Set weekly goals for yourself to actively build a professional network throughout your job search. Introduce yourself to local analysts through LinkedIn and ask for a quick informational phone interview. And talk to friends and family about your career goals - you may have more connections than you think.

Whenever you meet someone who’s made a career out of their data skills, ask all your questions. Youtube tutorials are great, but you need to make personal connections to get a true picture of your new career - from data collection blunders to epic revelations. (Plus, every connection could be a potential job offer down the line.)

Find a Data Analyst Mentor.

One-on-one mentorship is proven to be the most effective way of learning. That’s one of the most important reasons why we dedicate a personal mentor for each of our students.

You might already know someone whose career you admire, or maybe you’ll meet someone who’s especially helpful during your networking efforts. A great mentor will serve as a second set of eyes to look over your resume and portfolio, and help you understand the purpose of your skills in a business context. Most importantly, they’ll support you and your career goals.

Once you’ve met one or two people who fit the bill, keep in touch. Dropping a line now and then, even when you don’t need help or have a specific question, will help you keep a strong working relationship.

Prep for the data analyst interview.

All of that research, course-work and virtual networking will lead to interviews. Give yourself every chance at turning those conversations into job offers.

Companies hiring data analysts are looking for a specific set of skills, so be prepared to answer some technical questions. You may have to talk about your preferred method of cleaning data, or describe how you’ve answered complex questions with data in the past.

Above all else, your potential employer will want to know that you’re excited to keep learning. Technologies will evolve, and a successful data analyst must be willing to adapt.  

Tips for becoming a data analyst, even with no prior work experience

It’s that age-old riddle of switching careers: how to get hired with no previous experience in the industry. If you’re serious about breaking into data full-time, you can get hired with no experience, even without a degree in analytics. But you’ll have to work a little harder to learn specific skills, use the tools of the trade, and find creative ways to show off your ability. There are a few different ways you can do that.

• Find yourself an internship. You can go the traditional route of searching job boards for internship opportunities. But you might also be able to generate your own position, before it ever gets listed. Reach out to analysts with local companies; be brief and to the point, but let them know why you’re interested in speaking with them. If they know you’re willing to learn and you happen to catch them at the right time, you could end up creating an internship opportunity for yourself.
• Take an online course. If you’ve never held an analyst title, you need to find other ways to make it clear that you can meet the needs of the role. In a data analysis course, you’ll learn the specific skills you need, and see how they’re applied in real life. And an online, part-time course gives you the ability to transition careers without having to leave your current job.
• Stay relevant (and inspired). Follow some of the best data leaders like FiveThirtyEight on Twitter and LinkedIn. Keep tabs on data analysis blogs. Even if it’s a small part of your day, you’ll have sources for new inspiration and something to chat about during the small-talk portion of your next interview.
• Find your own challenges. Give yourself projects that get you researching and manipulating data. Research a topic you’re interested in, and ask yourself what types of questions you could answer by diving into the data. You can use tools like data.gov or dataportals.org to find datasets to work with.
  
  Over time, you’ll build a portfolio of work while keeping your skills sharp - and making it clear to recruiters that you’re self-motivated. Even if your topic area isn’t perfectly aligned with the jobs to which you’re applying, your portfolio will demonstrate a genuine interest in the field and commitment to honing your craft.
• Incorporate data into your current position. If you’re researching how to be a data analyst, you may have overlooked the simplest answer: just get started. Look for ways to flex your data brain in your current role. Even if analyzing spreadsheets isn’t part of your job description, do some of your own market research, or take a stab at improving how your department reports results. It gives you a chance to practice your skills, and maybe even prove to your company that you’ve got analyst potential.

Turn your skills into a career.

It’s daunting to embark on a whole new career path. Your killer Excel skills are a great place to start, but there’s more to it: you’ll have to combine math and coding knowledge with a compelling portfolio in order to land a rewarding job.

That’s why we give every student maximum support throughout their course and job hunt. Enthusiastic instructors, personal mentors, career coaches, and the rest of your cohort will all be rooting for you. If you’re ready to take the next step in your career, let’s chat about your future in data.