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Career Development, Data

How to Become a Data Analyst in 4 Steps (No Degree Required)

General Assembly
April 21, 2022

Making a career change can be scary, especially if self-doubt of “I’m not good enough” starts creeping in. However, there is no point in staying in a job or career that no longer brings you joy or fulfills you professionally. 

If you’re reconsidering your career, you’re not alone — over the last two years, over 50% of employed Americans have considered a total career revamp. Chances are, you know a relative or friend who is going through a similar career dilemma right now.

If you’re considering making a bold move to data analytics, we’ve got you covered. Understand if a career in Data Analytics is right for you in four easy steps.


To become a successful data analyst, you must ensure you possess some of the natural characteristics required for this career type. When speaking to the subject matter expert and GA instructor, Celia Fryer, she said successful data analysts are out of the box thinkers with a positive outlook, are curious and possess natural problem solving skills.

“Maybe you are a little bit of a “cup is half full” persona? If you’re a little bit of an out-of-the-box thinker who will see the whole picture, that’s a beautiful soul to encourage on a journey with data analysis”, said Celia Fryer, Advanced Analytics Immersive Lead at General Assembly. 

You might also be wondering about your past career and how this can impact your transition to data analytics. Some of the most successful data analysts have previously held careers in music, arts, real estate, sports analytics, the food industry, finance, engineering, and many more diverse backgrounds.

Remember, all experience is valuable. Your experience from past roles counts when it comes to building a substantial career in data analytics. If you’ve had to think on your feet in past roles a career in data analytics might be for you


Here are the key skills employers want to see on your resume: 

All the above skills are crucial. However, there is another skill sought after by employers that matters — project management. In this new era of remote work, where globally over 16% of companies hire fully remote candidates, project management is considered a necessity for your new data analyst job. 

At leading social media platform, LinkedIn, project management is a prerequisite. “You need to be able to prioritize your work tasks. In addition, most of us are working remotely from home, so having a basic level of project management to manage your own time and stay accountable is necessary”, said Farnaz Salehi, Insights Analyst at LinkedIn.

Here are the four steps to attract the attention of your future employer and get that dream data analyst job. 


You can start building your knowledge about data analytics right where you work today. Reach out to people who work in the business intelligence or data department, and see if you can chat with them for 15 minutes about their job. 

Don’t work in an office? Find your next mentor on LinkedIn. Reach out to someone in the field and ask if they’d be willing to chat about breaking into the industry.

When you begin to get a sense of what it’s like to be a data analyst, you’ll be more confident making a career pivot on this path.


Here are two day-to-day tasks you will be doing as a junior data analyst: 

  1. One of your first responsibilities would involve cleaning data, which means you would be sent an existing data set. You will need to get it ready for analysis, calculate a few missing fields, and communicate with the rest of your team the data areas for improvement. 
  2. Your second day-to-day responsibility would involve visualizing the data in a dashboard. This role is commonly known as the “dashboard jockey.” During this task, you might also be asked to communicate why you chose to represent the data in a certain way and explain the story behind the data. 


Six years ago, there was more demand for jobs than openings. You needed a degree to prove your knowledge to be even considered for a position. In a post-pandemic world, the tables have turned. 

In 2022 there are still more open positions than talent to fill them. Removing the university degree as a requirement to attract new talent has done the trick. As a result, college enrollments dropped by 6.8% in 2020. This is great news for anyone entering the workforce or changing careers. Not having a college degree will no longer eliminate you from securing your dream data analyst job.

Instead, professionals looking for a career change are using reskilling programs to do so. In fact, 12-week programs like our Data Analytics Immersive are designed with the sole purpose of getting program graduates that job. 

One of the common myths about changing careers is that a reskilling program isn’t “enough,” and companies won’t hire anyone without a degree. 

“We hear from students in our program who ask, ‘Do I need to do more schooling after this?’ No! You can make a full career change and get a job right out of bootcamp, and that’s what we’re here to help you do,” said Zoe M., General Assembly career coach.


Atlassian and LinkedIn are two innovative tech companies that often look for new data analysts to join their global teams. So when we asked them about the key skills they are looking for in a junior data analyst, they said:

“We are looking for two years of experience with SQL and Python and some evidence of communication skills”, said Geoffrey Pidcock, Senior Data Analyst at Atlassian. 

“At LinkedIn, we are looking for someone who can work with SQL and scripting language skills like Python. Plus, communication skills using Microsoft Power BI or Tableau. As well as consultancy and basic level project management skills”, added Farnaz Salehi, Insights Analyst at LinkedIn. 

Hear more from instructors at GA on why data skills are growing in demand: 


Data analytics is a very visual and hands-on role, this is why most companies require that you share your portfolio samples when applying. Here are some of the most important things you should include in your portfolio:

  • Real-world data samples that you can model up and present the problem you’ve solved for the business. 
  • Your understanding of how your data is echoing the business KPIs (key performance indicators). 
  • Your ability to clean large data sets and visualize them on a dashboard. 

A tip to get started: we recommend you check out some portfolio samples online and use real-world open-source data, which you can access from most government websites, or websites like Kaggle and MakoverMonday, that also offer a whole community of data analysts with whom you can collaborate on projects. 


Data analysts must be good communicators. Without storytelling, your findings will get lost amongst all the numbers. The presentation of your conclusion needs to be impactful and easy to understand to capture your audience’s attention. So how can you improve your communication skills today? Let’s take a look at these three strategies: 

  1. You need to understand your audience’s needs. To ensure you visualize the proper data findings, you will need to understand the core problem. Surveys and interviews are a great way to understand the root cause of your audience’s needs. 
  2. Gather, process, and visualize your data. Don’t be afraid to brainstorm and prototype your findings on paper before plotting the graph in a software tool. Making notes can help you communicate the final conclusion effectively. 
  3. Tell your story. Your data visualization needs to be accompanied by a description. Your audience won’t be able to draw out the conclusion themselves by just looking at graphs. People love a good story that’s easy to understand. Combine your notes and understanding of the core problem to communicate the results with your graphs. 


Our Data Analytics Immersive is designed for career changers like you, without prior data experience, who want to build a foundation skill set in data analytics with the possibility of advancing into more technical data science skills. 

Want to learn more? Attend an info session and find out: 

  • Who teaches GA Data Analytics Immersive courses? 
  • What’s it like inside the virtual classroom?
  • How does GA help you find your first data analyst role after graduation?

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