Data Analytics Certification: Do You Need a Certificate to Get a Job as a Data Analyst?


If you’re interested in becoming a data analyst, or even just interested in adding some data skills to your resume, you’ve probably wondered: do I need some kind of data analytics certification?

Finding the real answer to this question is tricky. There are a million data analytics certificate programs out there, and they all have a financial incentive to say that you need their certificate. Heck, here at Dataquest, we have a Data Analyst career path that awards you a certificate!

But here’s the honest truth: no, you do NOT need a certification to get a job as a data analyst.

Now, that doesn’t mean that data analytics certification programs aren’t valuable. But it does mean that you need to think about your investment carefully, because the certificate itself — the actual piece of paper and/or LinkedIn flair — is likely worth nothing.

We’re going to talk about different certification programs and how to assess them. But first, we probably need to explain why the certification itself won’t help you.

Employers don’t care about data analytics certificates. Here’s why.

When I was researching Dataquest’s data science career guide, I spent a lot of time talking to people in the industry about what makes a good entry-level candidate for roles like Data Analyst.

In fact, I have almost 200 pages of interview transcripts with senior data scientists, hiring managers, recruiters, etc. that are all focused on that specific subject: what makes a candidate stand out when applying for entry-level data analyst positions?

You know what word never appears once in those 200 pages? Certification.

(The word certificate doesn’t appear, either.)

The reason for this is pretty straightforward. From an employer perspective, certificates aren’t a good predictor of how effective someone will be at actually doing the job.

This is particularly true in the realm of data analytics, because very few certificate programs actually require much real data work.

MOOC platform courses, for example, typically consist of a series of video lectures, punctuated with multiple-choice and fill-in-the-blank quizzes. They may or may not have a “capstone” project at the end.

Best case scenario, seeing that certification on a resume means that the recipient has completed one data analysis project. That’s not enough to be meaningful to an employer who knows that your effectiveness on the job will be measured by successful end-to-end data analysis project completion, not by your ability to score well on multiple-choice quizzes.

For example, here’s a sample question from a real IBM/Coursera MOOC on data skills. Imagine this from an employer’s perspective — does being able to answer this kind of question prove an applicant knows how to actually use this algorithm?

MOOC data quiz question

Probably not.

While some certification programs are more rigorous than others, there are simply too many certifications out there for employers to bother worrying about.

When a hiring manager looks at your resume, you have about seven seconds to get their attention. They’re not going to waste their time doing research to figure out whether the certification program you chose is any good.

It’s worth mentioning that brand doesn’t matter here, either. A university degree on your resume will impress a recruiter. But a university certification? Employers are well aware that’s a very different thing. Often, university-branded certificate programs (both online and off) aren’t even operated by the university. They’re run by for-profit companies who license the university’s brand and video lecture recordings.

What do employers want to see on a data analyst’s resume?

We’ve written a lengthy guide to data science and data analysis resumes, but the most important lesson is this: employers need to see proof that you can do the work.

Nobody will pay you to do something that you’ve never done before.

The best way to prove you can do the work is relevant work experience, but if you’re looking for your first job in the field, you won’t have that. That’s OK! You can prove you’ve done the work another way: showcasing your data analysis projects.

We’ve got an in-depth guide to data analysis project portfolios too, so I won’t repeat all those lessons here. But long story short: the more relevant your projects are to the job you’re applying for, the better your chances will be.

For entry-level positions, that’s what employers are looking for in the seven seconds they spend scanning your resume. They want to see projects using the skills required for their role, doing the kinds of analyses needed for their role. Seeing that you’ve already done the kind of work they’re hiring for is far, far more important to most hiring managers than any certification.

You’ll get about 7 seconds of an employer’s attention on your resume. Use them wisely.

Are data analytics certifications useless? No!

None of this means that certification programs are useless, of course. It just means you need to assess them with the knowledge that the certificate brand you choose probably isn’t going to help you get a job. What will help you get a job are the skills you learn over the course of the program.

Also, it’s important to note that while certificates likely won’t help your job candidacy, they’re also not going to hurt your chances. Most employers will simply ignore them — so we don’t recommend listing them until the end of your resume — and almost no one will see them as sufficient proof that you can do the job. Some recruiters do, however, see certificates as a sign that a job candidate is actively looking to learn and improve their skill set.

Since many other applicants will have certificates too, this isn’t likely to set you apart from other candidates. Having highly relevant projects is your best chance at doing that. But listing a certificate or two to show you’re serious about learning and growing is never a bad idea.

How to assess certificate programs

The single most important thing you can get from any certification program is the skills you learn, and that should be your most important consideration. Important questions to ask include:

  • How does this program teach? Does it use video lectures? Interactive coding lessons? In-person classes? Everybody learns differently, so you probably know what works best for you, but the science suggests that generally speaking, the more hands-on the teaching method, the better.
  • What does this program teach? Does it cover the most important data analyst skills in enough depth? SQL is one area where many certificate programs skimp because it’s not exciting, but it’s the single most important skill for anyone interested in data to learn. If you don’t already have statistics knowledge, finding a program that covers basic statistics is also important.

Other important factors to consider in your decision include:

  • Cost. Certification programs can range from a few hundred dollars to tens of thousands! What kind of return can you expect on your investment?
  • Time requirements. Some certificate programs, like Dataquest’s, are self-serve — you can begin whenever you want, and study as fast or as slow as you want. Others are cohort-based and time-sensitive — you might only be able to join a class at certain times of the year, or only be able to join live classes at specific times of day.
  • Prerequisites. Some programs require specific degrees, or prior experience and/or coursework.
  • Third-party reviews. Any data analytics certification program with a half-decent marketing team can write a landing page full of happy learner quotes. But what do real learners have to say about the program? Third-party review sites like Switchup, G2, and Course Report are all good places to do some research.

When in doubt, try it out! Many platforms offer free trials, or free courses. For example, you can sign up for a free account with Dataquest and complete any of our 60+ free lessons to get a feel for the different types of content and the teaching style.

If a platform or certification program doesn’t give you any opportunity to sample their product, that could be a bit of a red flag. Since many platforms and programs do allow you to “try before you buy,” it hardly makes sense to spend hundreds or thousands of dollars on a learning product before you’re sure their teaching style works for you!

One thing you definitely need to consider before choosing a certification program: what’s your budget? Costs can vary widely.

Analytics certifications compared:

There are an absolutely huge number of data analyst certificates out there. Below, we’ll compare a few of the most popular types of certification programs, so that you have a better idea of how each option stacks up.


Cost: $294 (on sale) for a full year of access.

Type: Online, self-serve.

Platform: Hands-on browser-based coding interface

Topics covered: Python, SQL, statistics, command line/shell, Git

Prerequisites: None.

Time constraints: None. (Most students meet their goals in less than a year of part-time study). Review Average: 4.85 out of 5

General Assembly Data Analytics

Cost: $3,950 or higher (loan options available)

Type: Online or in-person bootcamp.

Platform: In-person or online virtual classroom

Topics covered: SQL, Excel, Tableau

Prerequisites: None.

Time constraints: Must join a specific session, must attend courses at specific times. (However, new sessions start frequently so you won’t have to wait long to join). Review Average: 4.28 out of 5

Thinkful Data Analytics Immersion

Cost: $12,250 or higher (loan options available)

Type: Online.

Platform: Online virtual classroom.

Topics covered: Python, SQL, Machine Learning

Prerequisites: None.

Time constraints: Full-time for four months, or part-time (20-30 hours per week) for six months. Review Average: 4.65 out of 5

Springboard Data Analytics Track

Cost: $5,500 or higher (loan options available)

Type: Online.

Platform: Online virtual classroom.

Topics covered: Python, SQL

Prerequisites: None, although you do have to apply and be accepted.

Time constraints: Must wait for the next cohort to begin, then the program length is six months. Review Average: 4.67 out of 5

Of course, there are many other options, but these are just examples. As you can see, there are significant differences between these programs. The most obvious one is cost — the costs here range from less than $300 to over $12,000! — but there are other meaningful differences, too.

For example, user reviews: despite being the most affordable option, Dataquest also has the highest average review score.

Time constraints also vary dramatically, from programs like Dataquest or General Assembly that you can start immediately or very soon after making your decision, to programs like Springboard that require an application process and waiting for a cohort to start.

Most important, probably: what topics are actually covered? All of the programs cover SQL — that’s a good sign! General Assembly’s program may be focused on less-technically-demanding analyst roles, with its focus on just SQL, Excel, and Tableau. On the other hand, the Thinkful program covers machine learning, which isn’t typically required for data analyst roles. Dataquest appears to be the only one of these options with substantive coverage probability and statistics.

This is not to say that any of these programs is “best.” Obviously, you’re reading this article on the Dataquest site, and we’re very proud of our platform, but we also value honesty, and there’s no way any single platform is going to be the best option for everyone.

What about test-based certifications?

There are a number of certification programs, like Certified Analytics Professional (CAP) or Cloudera’s CCA Data Analyst that offer no education at all. These are tests you can take (if you’re willing to pay a few hundred dollars) and you’ll recieve a certification if you pass.

Are these a good investment? Generally not. There are specific jobs that may favor these certifications, but few require them. And there’s no real evidence that employers are interested in them. As previously mentioned, none of the data analytics employers, recruiters, and hiring managers we spoke with mentioned certifications.

A more quantitative analysis confirms this theory. As of this writing, there are about 39,000 open data jobs listed on in the United States. Of these, fewer than 100 require a CAP certification, and fewer than 20 mention wanting to see CCA.

Put another way: estimating conservatively, about 99.7% of all data jobs don’t require these certifications.

In fact, only 15% of the data jobs on Indeed include the word “certification” at all. Many of the certifications listed are software-specific certifications related to a company’s specific tech stack. And some of that 15% is also job listings that read “Certifications: None.”

Any way you look at it, the demand for generic data analytics certifications is not high. The vast majority of data jobs do not require or even mention these kinds of certificates — if you do need a certificate for a job, it’s likely to be something software specific, such as an AWS certification for a company that does a lot of cloud-based data processing.

So what’s the best data analytics certification option for you? That’s going to come down to a personal decision based on factors like:

  • What is your budget?
  • How much free time do you have to study?
  • Which data analyst skills, if any, do you already have?
  • What is your desired timeline?

Whatever decision you make, though, now you’ll be making it with your eyes open. Now that you know the name on the certificate doesn’t really matter when it comes to getting a job, you’ll be free to focus more on what does matter: learning the right skills and building great projects to prove your skills to potential employers.

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