How to Become a Data Analyst

Data analysts gather, clean, and study data to help guide business decisions. Occupations in data are expected to see significant growth between over the coming years, according to the US Bureau of Labor Statistics [1]. If you're interested in this in-demand career, there are a few ways to get started.

In this article, we'll go over the different ways you can become a data analyst—with or without a degree. Afterward, if you want to get started building job-ready skills, consider enrolling in the IBM Data Analyst Professional Certificate. Over 11 courses, you'll develop a working knowledge of the Python language as well as how to visualize data and present your findings. All you need is basic computer literacy, high school math, and comfort with numbers.

How do I become a data analyst? A step-by-step guide

You can find data analytics jobs in all sorts of industries, and there’s more than one path toward securing your first job in this high-demand field. Whether you’re just getting started in the professional world or pivoting to a new career, here are some steps toward becoming a data analyst.

Learn more: What Does a Data Analyst Do? A Career Guide

1. Get a foundational education.

If you’re new to the world of data analysis, you’ll want to start by developing some foundational knowledge in the field. Getting a broad overview of data analytics can help you decide whether this career is a good fit while equipping you with job-ready skills.

It used to be that most entry-level data analyst positions required a bachelor’s degree. While many positions still do require a degree, that’s beginning to change. You can develop foundational knowledge and enhance your resume with a degree in math, computer science, or another related field—or you can also learn what you need through alternative programs, like professional certificates, bootcamps, or self-study courses.

In this video, practicing data professionals offer their best advice for aspiring data analysts.

2. Build your technical skills.

Getting a job in data analysis typically requires having a set of specific technical skills. Whether you’re learning through a degree program, professional certificate, or on your own, these are some essential skills you’ll likely need to get hired.

• Statistics

• R or Python programming

• SQL (Structured Query Language)

• Data visualization

• Data cleaning and preparation

Take a look at some job listings for roles you’d like to apply for, and focus your learning on the specific programming languages or visualization tools listed as requirements.

In addition to these hard skills, hiring managers also look for workplace skills, like solid communication skills—you may be asked to present your findings to those without as much technical knowledge—problem-solving ability, and domain knowledge in the industry you’d like to work.

Learn how to perform data analysis, including data preparation, statistical analysis, and predictive modeling, using R, R Studio, and Jupyter with the IBM Data Analytics with Excel and R Professional Certificate.

3. Work on projects with real data.

The best way to learn how to find value in data is to work with it in real-world settings. Look for degree programs or courses that include hands-on projects using real data sets. You can also find a variety of free public data sets you can use to design your own projects. 

Dig into climate data from the National Centers for Environmental Information, delve deeper into the news with data from BuzzFeed, or come up with solutions to looming challenges on Earth and beyond with NASA open data. These are just a few examples of the data out there. Pick a topic you’re interested in and find some data to practice on.

If you’re looking to build job-ready data analyst skills without committing to a degree, consider the Google Data Analytics Professional Certificate through Coursera. You'll learn how to clean and organize data with SQL and R, visualize with Tableau, and complete a case study for your portfolio.

When you complete the program, you'll get access to hiring resources through Google’s Employer Consortium.

4. Develop a portfolio of your work.

As you play around with data sets on the internet or complete hands-on assignments in your classes, be sure to save your best work for your portfolio. A portfolio demonstrates your skills to hiring managers. A strong portfolio can go a long way toward getting the job.  

As you start to curate work for your portfolio, choose projects that demonstrate your ability to:

• Scrape data from different sources

• Clean and normalize raw data

• Visualize your findings through graphs, charts, maps, and other visualizations

• Draw actionable insights from data

If you’ve worked on any group projects through the course of your learning, consider including one of those as well. This shows that you’re able to work as part of a team.

If you’re not sure what to include in your portfolio (or need some inspiration for project ideas), spend some time browsing through other people’s portfolios to see what they’ve chosen to include.

Tip: Sign up for a GitHub account and start posting your projects and code to the site. It’s an excellent spot to network with a community of data analysts, show off your work, and possibly catch the eye of recruiters.

5. Practice presenting your findings.

It can be easy to focus only on the technical aspects of data analysis, but don’t neglect your communication skills. A significant element of working as a data analyst is presenting your findings to decision makers and other stakeholders in the company. When you’re able to tell a story with the data, you can help your organization make data-driven decisions. 

As you complete projects for your portfolio, practice presenting your findings. Think about what message you want to convey and what visuals you’ll use to support your message. Practice speaking slowly and making eye contact. Practice in front of the mirror or your classmates. Try recording yourself as you present so you can watch it back and look for areas to improve.

6. Get an entry-level data analyst job.

After gaining some experience working with data and presenting your findings, it’s time to polish your resume and begin applying for entry-level data analyst jobs. Don’t be afraid to apply for positions that feel like a stretch. Your skills, portfolio, and enthusiasm for a role can often matter more than if you check every bullet item in the qualifications list.

If you’re still in school, ask your university’s career services office about any internship opportunities. With an internship, you can start gaining real-world experience for your resume and apply what you’re learning on the job.

7. Consider certification or an advanced degree.

As you move through your career as a data analyst, consider how you’d like to advance and what other qualifications can help you get there. Certifications, like the Certified Analytics Professional or Cloudera Certified Associate Data Analyst, may help qualify you for more advanced positions at higher pay grades.  

If you’re considering advancing into a role as a data scientist, you may need to earn a master’s degree in data science or a related field. Advanced degrees are not always required, but having one can open up more opportunities.

Learn more: Data Analyst vs. Data Scientist: What’s the Difference?

Begin your data analyst career on Coursera

Develop job-ready skills to pursue a career as a junior or entry-level data analyst on Coursera with the IBM Data Analyst Professional Certificate. Gain technical experience through hands-on labs and projects that culminates in a portfolio you can use to showcase your work.

Frequently asked questions (FAQ)