How to Become a Data Analyst in 5 Steps

Are you good with data visualizations? Does finding trends excite you? A career in data analytics may be right for you.

Daya analysis is the process of collecting, categorizing, analyzing, and visualizing data patterns and trends. Data analysts use these techniques to gather insights and make informed business decisions.

Data analysis professionals earn $79,113 on average in the United States. They work across all industries, including healthcare, ecommerce, and education, as well as small, medium, and large businesses. The job outlook is promising, with the profession expecting 36% growth between 2023 and 2033.

In this article, we’ll explain how you can become a data analyst, including how to acquire data analysis skills and find a job.

📌 Related Reading: A Beginner’s Guide to Data Analytics

How Do I Become a Data Analyst? 5 Steps

1. Invest in Skills

Data analysts are highly skilled professionals. Often, data science professionals earn master’s and doctoral degrees in mathematics, statistics, computer science, and engineering.

Pause. We understand that higher education has barriers to entry. A four-year degree, while a tremendous accomplishment, is an expensive endeavor. (The average cost of college in the U.S. is $38,270 per year.) Throw in financial, emotional, and social obligations, and understandably, some may conclude that becoming a data analyst is out of their reach.

Before you move on to the next endeavor, let us make our case.

Data analysis is a skills-based career. Skills-based hiring is a progressive hiring tactic focusing on an individual’s competencies rather than formal education.

Many pursue higher education to become data analysts. However, you can become a data analyst through college alternatives, including:

• Job training programs
• Bootcamps
• Certificates

Each alternative has its perks. For example, job training programs are all-inclusive learning methods that guide you through knowledge acquisition, networking, and job hunting. Bootcamps are full-time accelerators designed to launch your career in months.

You have options—college, job training, bootcamp. Choose the education plan that is right for your goals and lifestyle.

2. Apply Your Technical Skills to Gain Experience

It’s seldom that people become topical experts without practice. If you are part of the .001%, feel free to move on to the next section. If not, stick around as we explain how you can gain data science experience.

As a budding data analyst, you should regularly expose yourself to datasets to exercise practical skills like problem-solving and creative and analytical thinking. You can also gain valuable experience interacting with database querying languages, SQL databases, and Excel.

The Integrate Postsecondary Education Data System (IPEDS) publishes higher education enrollment data annually. The U.S. Census Bureau conducts a census decennially. Dive into the data and make inferences based on personal analysis.

📌 Do you have a niche interest? The Google Dataset Search connects you with open-source datasets. 

3. Develop Your Portfolio

As you practice your technical skills, document your progress in a portfolio. A portfolio demonstrates your capabilities to recruiters and hiring managers—essential, especially in skills-based hiring.

Here are projects you should consider including in your data analyst portfolio:

• Projects using Python
• Data analysis demonstrating SQL knowledge
• Tableau projects

You should also consider tailoring your portfolio to your desired industry. For example, if you want to work in ecommerce, your projects may include a sales dashboard using SQL or showcase a churn analysis using Python.

Your applications are as strong as your portfolio. 

4. Update Your Current Resume

Picture this: You go to the library for a book on SQL databases. The librarian instead brings you a vegan cookbook. You’d probably be dissatisfied because it does not meet your request. Now, place yourself in the recruiter’s shoes.

Recruiters have specific requirements. They understand every candidate won’t tick all the boxes, but the closer you get, the more satisfied they’ll be.

Take a look at your resume. Does your resume still have your high school? Do previous positions highlight transferable skills? Have you used statistics to demonstrate your value? Do you use keywords from the job description?

The bottom line is your resume should align with the industry and job you’re after. A resume for a previous sales clerk position will not suffice. 

5. Network Your Way to a New Job

Job searching is sometimes a long and arduous affair. It often takes job hunters 2.5 months to find a job. So, how do you expedite the job-hunting process? Networking.

You’ve probably heard it before, but your network opens doors that job hunting can not. Colleagues can connect you to the hidden job market, recommend you to recruiters in their market, and vouch for you.

If data analysis is new to you, consider connecting to a professional network.

Data analysis and science professional networks:

• American Statistical Association
• International Institute for Analytics
• Digital Analytics Association
• Institute of Analytics

Keep in mind that networking is more than a job-searching tactic. You can build community, stay current on trends, and learn new skills. Continuously engage your network to advance your career even after you land an entry-level data analyst job.

📌 Related Reading: How to Network When Starting Fresh

Bonus: Consider Advanced Certifications

Becoming a data analyst does not stop at your first entry-level data analytics job. In fact, it’s just the start.

You should continue developing your data analytics skills to achieve higher levels of employment, from entry-level to senior analyst. You can also specialize in focusing your career, including financial, product, and operations analysis.

You can progress your career with increasingly advanced projects, self-study, or certifications.

There are plenty of certifications that can help you demonstrate your expertise and excel in your career, including:

• CompTIA Data+
• MIT Sloan School of Management Applied Business Analytics Certificate
• Cornell Data Analytics Certificate Program

Don’t stop at entry level. Continue progressing your skills to leverage the active and competitive job market.

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