How to Become a Data Analyst With No Experience or Degree

Yes: it’s entirely possible to become a data analyst with no experience or degree—and yes, employers will be open to hiring you.

With the normalization of AI and machine learning, the demand for professionals with an understanding of data analytics is only increasing. Healthcare, retail, and finance industries in particular are leveraging these technologies.

Ready to get your hands dirty? A great way to see if the field is for you is by trying our free 5-day data analytics short course.

In brief, here are the six steps to becoming a data analyst:

1. Complete a project-based data analytics certification
2. Create a data analytics portfolio
3. Identify (and emphasize) your transferable skills
4. Network
5. Continuously learn the latest trends and tech
6. Prepare for job interviews

Now let’s go in more depth on the entire picture:

More of a visual learner? Well, we’ve made a video of the main parts of this article. Take it away, Will!

Ready to jump in? Let’s go.

What does a data analyst do?

As a data analyst, it’s your responsibility to turn raw data into meaningful insights. Following the data analysis process, you’ll solve specific problems or answer certain questions based on data and the insights it provides.

You’ll then take these insights and share them with key stakeholders and decision makers, who can take action or plan for the future accordingly. At the same time, data analysts may be responsible for overseeing the overall processes for collecting and storing data, as well as setting guidelines for data quality.

A great way to gauge what a data analyst actually does on a day-to-day basis is to look at the tasks and responsibilities that are typically listed in data analyst job descriptions. Based on actual job descriptions posted on, here’s what you can expect to do as a data analyst:

  • Develop and implement databases and data collection systems
  • Work closely with management to identify critical metrics and KPIs, and to prioritize business needs
  • Collect data from primary and / or secondary data sources
  • Filter and clean data
  • Identify, analyze, and interpret trends and patterns in complex data sets
  • Visualize and present findings to key stakeholders
  • Build and customize reports
  • Develop and maintain dashboards
  • Create and maintain documentation regarding data models, measures, and infrastructure as they are developed

Learn more here about what a data analyst actually does.

Data analysts vs. data scientists

While data analysts and data scientists at companies share a common goal—helping to make business decisions—they go about it in different ways. An analyst seeks answers to questions.

Meanwhile, a data scientist’s job is to ask very detailed, tactical questions to help inform an organization’s overall strategy. While a data analyst may work within a single division or department (and have detailed knowledge of that division) a data scientist needs to understand the processes, systems, and aims of the organization as a whole.

Learn more about the key differences between data science and data analysis here.

Skills required to become a data analyst

The good news: you probably already have a lot of these skills.

These skills vary widely by position and company, but they act as a good starting point to understand what you’ll learn in a data analytics bootcamp or prorgram.

Soft skills

  • Communication, collaboration, and presentation skills
  • Problem-solving
  • Research
  • Attention to detail
  • Analytical mindset
  • Affinity for numbers
  • Good organizational skills and an ability to meet deadlines
  • Some commercial knowledge or business acumen
  • Methodical and logical approach

If you want an example of someone who was able to put these transferable skills to use, look no further than CareerFoundry Data Analytics Program grad Nick Logan. A former teacher, Nick was able to leverage the research, communication, organization, and presentation skills which are part and parcel of being an educator in his his career as a business intelligence analyst.

Hard skills and tools

  • Proficiency in Microsoft Excel
  • Knowledge of programming and querying languages such as SQL, Oracle, and Python
  • Proficiency in business intelligence and analytics software, such as Tableau, SAS, and RapidMiner
  • Mine, analyze, model, and interpret data
  • Work with large, complex datasets
  • Solid understanding of data profiling and requirement gathering processes and principles
  • Expertise in data visualization
  • Communicate findings and to make actionable recommendations for the business
  • Deploy commercially viable statistical models

Is it possible to become a data analyst with no previous experience?

We’ll cut to the chase: It’s absolutely possible, even if you’re starting from the beginning and don’t have any industry experience.

How can we be so sure?

There are several factors that make the data job market relatively accessible for newcomers:

  • The significant and rapid growth of the data market
  • The global data skills gap
  • The value of transferable skills within the data analytics field

Let’s take a look at these in more detail.

The job market for data analysts is booming

According to a report by Precedence Research in 2022, the global data analytics market was valued at $41.39 billion USD. That’s more than double what it was worth in 2015.

In their Jobs of Tomorrow Report (2020), the World Economic Forum highlights seven high-growth emerging professions, with data and artificial intelligence (AI) showing the highest growth rate at 41% per year.

AI is accelerating demand for data analysts

Knowing which AI data analytics tools to use will become a prerequisite for many firms, which levels the playing field for those looking to become a data analyst with no experience. It’s no wonder that courses and bootcamps have started making learning these tools and skills part of their curriculums.

In their 2024 Predictions Report, research group Forester put it best:

So who’s going to make the most of genAI in 2024? Data and analytics pros who invest in the right people, practices, and data strategies.

There is a global shortage for data talent

The data market is growing at a rapid pace, and businesses are desperately trying to keep up.

Data-driven organizations consistently outperform their competitors, so it makes sense that hiring data experts will be an increasing priority across all industries.

At the moment, though, we’re seeing something of a data skills gap. In a study conducted by NTUC LearningHub, 93% of working professionals said that their workforce is not achieving optimal productivity due to a lack of data skills.

Miro Kazakoff, a senior lecturer at MIT Sloan sums up the issue of data literacy nicely:

“Data literacy has always been a requirement in successful organizations. It’s just that data illiteracy is more obvious now—or data illiteracy just causes more damage now than it used to.”

Data analysts rely on a vast array of transferable skills from other industries

Aside from the fact that data analysts are in high demand, the role itself requires a vast array of skills—many of which you’ll bring with you from other work and life experiences.

Some key transferable skills that will help you as a data analyst include:

  • Curiosity and an inquisitive nature
  • Problem-solving
  • Excellent communication skills (e.g. being good at explaining things)
  • Research
  • Attention to detail
  • Collaboration and teamwork

And, with employers placing increasing importance on soft skills, it’s certainly worth highlighting these in your applications. We’ll show you how to do this in the next section.

Related watching: Video: Is working in data analytics a good career fit for you?

Case study: Chad

CareerFoundry graduate Chad Stacey is a great example of this. He studied History and worked as a tech recruiter until he decided to take the CareerFoundry Data Analytics Program.

Despite having no prior experience in the industry, he got a job as a data analyst for British newspaper The Telegraph! It’s a fascinating story, and not uncommon these days.

How to become a data analyst: Step-by-step guide

1. Complete a project-based data analytics certification

You don’t need a full-blown degree to become a data analyst, but you do need a structured and formal approach to learning the necessary skills. The best (and most flexible) way to do so is through a project-based course. Some key things to look for when choosing a course are:

  • A hands-on, up-to-date, AI-inclusive curriculum that contributes to your portfolio
  • Some form of mentorship
  • A certificate of completion
  • A focus on job preparation and career advice
  • A job guarantee

For help finding the right course, take a look at this comparison of the best data analytics certification programs.

Here at CareerFoundry we offer a top-rated data analytics program that includes mentorship, tutoring, career guidance, and a job guarantee. Get a taste of it with our free 6-day data course.

2. Create a data analytics portfolio

Data analytics is a hands-on field, and employers want to see proof that you can apply what you know to real projects.

Here are some ideas:

Learn more more about how to build a professional data analytics portfolio in this guide.

3. Identify (and emphasize) your transferable skills

If you’re brand new to the field of data, it’s especially important to draw parallels between your previous experience and your new career. Spend some time identifying your core hard and soft skills, and think about how they might be transferred to data analytics.

Perhaps you have a marketing background and are already familiar with some basic analytics tools. Maybe you’re a teacher, which makes you great at explaining things.

As Chris Savage, Founder and CEO of Wistia famously wrote on his blog:

“You can’t run a business today without data. But you also can’t let the numbers drive the car.”

Can you see how seemingly unrelated experience will actually set you apart as an excellent data analyst? The trick is to recognize your value and convey it to employers through your portfolio, your resumé, and how you talk about yourself in interviews.

4. Network 

I’ve found this to be a constantly underrated step when learning how to become a data analyst. Networking is a great way to learn about new job opportunities, get advice from experienced professionals, and build relationships that can help you advance your career.

How to go about doing it? After building a social profile so that people can find and connect with you easily, try and attend industry events or data meetups, connect with people on LinkedIn, and reach out to people you admire in the field for coffee chats or informational interviews.

5. Continuously learn the latest trends and tech

The field of data analytics is constantly evolving, so it’s important to stay up-to-date on the latest trends and technologies. Read industry publications, attend conferences (on- or offline), and take online courses to learn about new tools and techniques.

It’s important to recognize that it’s easy to get overwhelmed and feel left behind. Stop, take a breath, and realize that’s near-impossible to stay on top of absolutely everything.

Finding your niche or passion, and subscribing to the relevant newsletters, blogs, and thought leaders around this area will help you feel in the loop.

7. Prepare for job interviews

Once you start applying for data analyst jobs, be prepared to answer common data analyst interview questions and demonstrate your skills. Practice answering questions about your experience with data analysis techniques, as well as your problem-solving and analytical skills.

Another oft-overlooked thing to concentrate on if you want to become a data analyst is to emphasize your ability to communicate your findings to non-technical audiences. You’ll be working not just within a data team, but with other stakeholders, internal or external. Employers are looking to see not only that you can devise and carry out data analysis, but also that you can explain your results clearly and effectively.

Learn more about how to prepare for entry-level data analyst job interviews here.

How to increase your chances of getting hired as a data analyst

In the absence of industry experience, the best thing you can do to sharpen your competitive edge is to recognize the unique value you bring as a newcomer to the field.

This advice comes from Mike McCulloch, Director of Career Outcomes at CareerFoundry, who specializes in coaching graduates through career change.

Rather than being a setback, having no prior experience in the industry is actually seen as a major asset. As Mike explains:

“Newcomers don’t come with any of the preconceptions that mid-level professionals do. They see the business and its challenges through fresh eyes, and are therefore able to approach it from completely new angles. They don’t yet know what’s possible, so they ask different and unexpected questions. Not only does this keep seniors on their toes; it also helps the business to find new solutions to old problems.”

There are other advantages to hiring complete beginners:

  • Mentorship: It gives senior team members the opportunity to mentor someone, which benefits both parties.
  • Investing in employee growth: Another benefit that many companies will appreciate is the chance to train someone from scratch and nurture them for future career growth.

Data analyst working remotely

Industries (and salaries) for data analysts

When you’re just starting out, you can expect to land the job title of “data analyst” or “junior data analyst.” More specialized roles, such as healthcare data analyst, will require some industry experience.

As a newly qualified analyst, you’re likely to find job opportunities in the following sectors:

  • Media and entertainment
  • Finance
  • Retail
  • Marketing
  • Wellness and fitness
  • Education
  • Transport and logistics

…to name just a few! For a more specific idea of the opportunities available to you as a newly qualified data analyst, it’s worth searching for “data analyst” or “junior analyst” positions in your local area. Browse sites like LinkedIn, Indeed, and Glassdoor for a well-rounded view of the current job market.

Read more in our guide to entry-level data analyst jobs.

Bear in mind that in 2024 the data analyst skillset has split across a wide variety of positions and roles (like “sustainability analyst” for example), so it helps to search first for “analyst” in job sites and company job boards.

How much do entry-level data analysts earn?

According to data from Indeed, the average base salary for a junior data analyst in the United States is $73,404 USD. That’s considerably higher than the national average income of $53,490, so it’s not a bad starting point!

How much you can expect to earn in your first data analyst job depends on where you (or the job) are based, and the sector you’re going into.

Learn more about entry-level data analyst salaries in this article.

Key takeaways and next steps

As a newcomer to the industry, you have plenty of value to offer—and not just despite your lack of experience, but in many ways, because of it.

Ready to get the ball rolling? Here’s a free introductory data analytics short course to ease you in. And, if you’d like to learn more about forging a career in data, check out the following:

What You Should Do Now

  1. Get a hands-on introduction to data analytics and carry out your first analysis with our free, self-paced Data Analytics Short Course.

  2. Take part in one of our FREE live online data analytics events with industry experts, and read about Azadeh’s journey from school teacher to data analyst.

  3. Become a qualified data analyst in just 4-8 months—complete with a job guarantee.

  4. This month, we’re offering a partial scholarship worth up to $1,365 off on all of our career-change programs to the first 100 students who apply 🎉 Book your application call and secure your spot now!

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