How to become a data analyst

BY Jenna DutcherNovember 11, 2022, 1:49 PM
Illustration by Martin Laksman

With the wealth of data in our modern world, there will always be a need for someone to interpret it. And that’s where data analysts come in.

Data analysts are employed in every industry, in every sector. You may have heard of them working in business intelligence, competitive intel, marketing analysis, or even strategy. They need to know how to query data and visualize it, which is the definition of both a science and an art. And, above all else, data analysts need to be able to share their findings with stakeholders.

Strong communication skills are really important when working with data, says Rachel Townsley, a lead scientist in the chief technology office at Booz Allen Hamilton. “Being able to communicate well is invaluable in almost all workplace roles—not only is good communication critical to team functioning and productivity, sometimes really good work can be rendered irrelevant if it isn’t communicated well to the client.”

Data analysts must possess a delicate mix of hard and soft skills, and their ability to mine data is just as critical as their ability to share their findings. And all of these are skill sets for which they are rewarded. Here’s a step-by-step guide if you’re considering a career as a data analyst:

  1. Decide if the data analyst role is right for you
  2. Pursue a degree in a data-oriented field
  3. Hone technical skills and soft skills, while remaining curious
  4. Research career resources
  5. Be multifaceted to ace your interview

1. Decide if the data analyst role is right for you

There are many data-related roles with similar-sounding titles, but very different functions—and that’s why it’s important to decide which role you really want. Take data analysts and their close counterparts, data scientists, for example. People in both functions spend their days immersed in datasets, running queries, and drawing conclusions, but they differ in how they apply that information. 

Generally speaking, the data analyst is tasked with presenting those findings in a way that can be understood by others. Data analysis helps “digest what customers think they want and then provide what would be the most valuable in the least amount of time,” says Yatish Nerur, a client insights analyst at Vimeo.

Data scientists, on the other hand, seek new and innovative ways of accessing, analyzing, and breaking down data. Put even more simply, data scientists help capture and query data and insights for data analysts, who then map data findings to business goals and communicate them out to those who need to know. 

One thing the two roles have in common is they’re in high demand. The U.S. Bureau of Labor Statistics projects a 31% growth outlook for the broader category of data science occupations between 2021 and 2031. And data analysts draw in a median wage of nearly $101,000 nationwide.

2. Pursue a degree in a data-oriented field

With a solid understanding of what a career as a data analyst may entail, it’s time to hit the books. A bachelor’s degree in computer science, mathematics, finance, statistics, business, information systems, or economics is a common education credential for a data analyst. Certification programs from the likes of Coursera or Google can also help candidates get their foot on the door. 

For those people interested in pursuing further graduate education, master’s degree programs in analytics also abound.

Formal education isn’t for everyone, nor is it a requirement for a successful data science career, Townsley notes. “But for me, the time I spent in a doctoral program really gave me the space to indulge curiosity in an academic way, to be creative in a field that often isn’t thought of as particularly creative, and to hone critical thinking and strategic skills in a data oriented way,” she adds.

3. Hone technical skills and soft skills, while remaining curious

The most important traits for a data analyst, according to Nerur, are an analytical mindset so you ask the right questions to assess the problem being solved, along with hard skills to query the data and actually visualize it in a way that your end customer will understand.

When it comes to soft skills, having an analytical mindset is key for a would-be data analyst. This is not to discount hard skills; a mastery of programming languages like SQL, data visualization tools like Tableau or Looker, and even the ability to use pivot tables in Microsoft Excel can help demonstrate technical competence to a would-be employer. 

And there are basic foundational skills everyone working in data should have, Townsley says: “Learn how to write queries in SQL, become comfortable with R or Python, have a good grasp on how to explore and summarize data to get useful insights.” 

However, she cautions, technical skills will open doors but passion is what will sustain you. “To do well and make it a sustainable career, it’s important to either find some particular type of methodology that’s exciting or interesting to you, and/or a particular application area that’s compelling.”

For those people who don’t uncover this level of passion in their early educational experiences, don’t lose heart, and don’t undervalue the benefits of self-instruction. Nerur, for example, taught himself both SQL and Python, the latter a more technical skill that can help if a candidate is interested in data science in addition to data analysis. 

4. Research career resources

As with any data-oriented role, it’s important to consider what type of work you will find most interesting. For example, do you want your work to focus on analysis of information within a company or of data supplied by customers, be it consumers or other businesses? 

You’ll also want to consider what industry or topic appeals to your interests. From public to private sectors, data analysts are employed in nearly every field, so there are plenty of career options to choose from. 

Once you’ve determined these key factors, it’s time to prove your value to employers. The field of data analysis has a lot to offer its practitioners, from certification to best practices to formal education:

5. Be multifaceted to ace your interview

Finally, there’s the hiring process. When it comes to data analyst interviews, hard skills will always be critical. “SQL has definitely been the first thing that any analyst role hiring process has asked about,” Nerur says.

A lot of interviewing, he continues, is a test of whether you can think in the right way and then whether you can do what needs to be done on a daily basis in order to get the data to a point where you can make decisions or propose decisions.

However, while these common interview questions tend to be about experience, interests, and style of work, Townsley says, as a hiring manager, she’s often looking for a more holistic picture from interview candidates. 

“I think about three aspects of skill and/or competence: analytic ability, technical ability, and ‘personability,’” she says. “Analytic ability is about how you think about problems, technical ability is about how well you can execute methodology, and personability is how well you work with others and how well you communicate findings. A good hire in my mind is good at each of these things, and ideally, really good at one or two.”

Check out all of Fortune’rankings of degree programs, and learn more about specific career paths.