Data Analyst Certifications Worth Getting and Which Ones to Skip

Start with the tool your target employers actually use, because the certification that pays off most is usually the one that matches it. In a SHRM skills-first survey fielded in October 2025, 78% of HR professionals in the United States said skilled credentials are used sometimes, often, or almost always in hiring. That is a real opening for you, but it is not a promise that any badge gets you hired. This guide sorts the credentials into the ones worth the exam fee, the ones worth a second look, and the ones to skip, so you can pick one and move on. Metaintro can then help you find analyst openings that name the tool you just learned.

Do data analyst certifications actually matter to employers?

They matter, but as proof of a specific skill and not as a replacement for experience. The same October 2025 SHRM survey found that 78% of the HR professionals in the United States it polled said skilled credentials are used at least sometimes in their hiring. Look closely at the wording. "Sometimes" is a low bar, and the survey describes how often HR professionals say credentials are used, not how much weight a credential carries against a portfolio, a degree or a referral.

A second number points the same direction. In its 2025 State of Skills-Based Hiring report, TestGorilla found that 85% of employers were using skills-based hiring, up from 81% the year before. That survey was fielded in April 2025 among people involved in hiring decisions in the US and UK. Skills-based hiring means employers lean on demonstrated ability, and a certification is one cheap, standardized way to demonstrate it.

For you, the takeaway is practical. A certification works best when it answers a question a hiring manager is already asking, such as "Can this person build a dashboard in the tool we use?" or "Do they know basic data concepts?" It works poorly when it is a line on a resume with nothing behind it. Pair every credential you earn with something you can show, and you turn a checkbox into evidence.

Which certification should you get first if you are brand new?

If you are starting from zero, begin with an entry-level fundamentals credential, not an exam that assumes you already work with data. Two options fit most beginners.

• Microsoft's Azure Data Fundamentals is an entry-level exam on core data concepts and how they show up in cloud services. It is a gentle on-ramp if you want a recognizable vendor name without committing to a hard exam.
• The Python Institute offers PCEP, its entry-level Python programmer credential, which is worth a look if your target postings ask for Python and you have no coding history.

You will often see CompTIA Data+ on beginner lists, but the exam itself is pitched at people with some analyst experience. CompTIA describes it as an early-career credential and recommends prior time in a data analyst or similar role, with exposure to databases, analytical tools, basic statistics and visualization. It is a vendor-neutral option worth considering once you have some on-the-job experience and do not want to tie yourself to one tool. SQL, which most analyst postings expect, is a skill you will build through practice and a project instead.

Whichever you choose, treat it as step one. Foundation credentials signal that you are serious, but they rarely differentiate you from other applicants. The next tier, tied to a tool, usually does more of the work. If you are starting from zero, see how to become a data analyst without a degree.

78% of HR professionals in the United States say skilled credentials are used sometimes, often, or almost always in hiring, according to SHRM.

Which tool-specific certifications are worth the exam fee?

Tool-specific credentials are the strongest value for analysts because they match the language of job postings. When a posting says "Power BI," a credential with that name in the title speaks directly to it. Three are worth knowing.

• Microsoft's Power BI Data Analyst Associate is aimed at people who model and visualize data for business decisions. Microsoft rates it an intermediate exam, so it is best taken after you have built real reports in Power BI. If your target employers run on Microsoft products, it is often the tool credential to chase once you have that practice.
• Databricks Certified Data Analyst Associate fits analysts who work with SQL on data platforms built around the lakehouse approach. Databricks recommends months of hands-on analysis work before the exam, and it is more niche, so check that your target employers use that platform and that you have that experience before you invest.
• SAS's Applied Statistics for Machine Learning credential covers fundamental statistics and linear and logistic regression, so it suits people headed toward statistics-heavy work.

The pattern is simple. Pick the credential whose tool appears in the postings you would actually apply to. Open ten job listings for the role you want, count which tools show up, and let that count decide. A credential for a tool nobody on your target list uses is a weak purchase no matter how respected the vendor is.

One more caution: tool vendors update their exams and retire old ones. Before you pay, confirm on the vendor's own certification page that the exam is still offered and what it currently covers.

What about business analysis and data management certifications?

Some data analysts sit closer to the business side, and for them a business analysis credential can fit better than a technical one. The International Institute of Business Analysis offers a ladder you can climb as you gain experience.

• IIBA's Entry Certificate in Business Analysis is aimed at people new to the field.
• IIBA's Certification of Capability in Business Analysis is designed for people who already have hands-on business analysis experience, so it is a mid-career move and not a starter credential.

These help most if your goal is a title like business analyst, product analyst or operations analyst, where requirements gathering and stakeholder communication count as much as queries and charts. If you are leaning toward product work, Metaintro's guide to product analyst interview questions shows how those roles are screened.

For analysts who care about data quality and governance, DAMA International runs the Certified Data Management Professional program. It has an Associate level for people new to data management and higher levels for deeper experience, and it fits people who expect to move into data governance, stewardship or management.

The honest filter is this: choose the business or governance track only if the job titles you are chasing ask for it. Otherwise, those hours are better spent on a tool credential and a project.

Are cloud and data engineering certifications worth it for an analyst?

Sometimes, but only for a specific kind of analyst. Cloud certifications are larger commitments, and they point toward engineering as much as analysis. Amazon Web Services' Certified Data Engineer Associate and the credentials in Google Cloud's certification catalog are built around building and running data pipelines and storage, which is a step beyond writing queries and building dashboards. Oracle's certification program covers database and cloud skills in a similar vein.

These make sense in two situations. First, you already work with a cloud platform at your job and want a credential that backs up what you do. Second, you want a bridge from analyst work into analytics engineering or data engineering, and you are willing to study harder material.

They make less sense as a first purchase. If your goal is to land a first analyst role, a cloud engineering exam can eat months while a Power BI credential and two portfolio projects would have gotten you more interviews. Match the credential to the job you want next, not the job you dream about in five years.

64% of HR professionals in the United States expect industry or professional certifications to remain valuable over the next three years, according to SHRM.

How do you tell a worthwhile certification from a waste of money?

Run any credential through a short filter before you pay. The filter below is built so you can answer each question from a job posting or the vendor's own site.

• Does the credential name appear in postings for the job you want? If you cannot find it in ten listings, hold off.
• Is it issued by the company that makes the tool, or by a recognized professional body? A vendor or an association stands behind the exam, while an unfamiliar issuer may not carry weight anywhere.
• Does it require a proctored exam? A credential you earn by watching videos and clicking through quizzes proves less than one where you must pass an exam under test conditions.
• Does it expire or require renewal? Renewal can keep a credential meaningful, but it also adds recurring cost.
• Can you show something built with it? If not, plan a project before you test.

The pattern in the best credentials is a real exam, a named issuer and a clear link to everyday tasks. The pattern in the weakest is a promise of a job or a salary. No credential can guarantee either, and any program that does should lose your trust immediately.

You can also use free signals before spending anything. Read the exam's published skills outline on the vendor's page and see how much of it you already know. If you cover most of it, the exam fee may be a good investment. If you know almost none of it, spend a few weeks learning the material first and then decide whether the paper is worth it.

How much time and money should a certification cost you?

Budget the whole cost, not just the exam fee. The fee is the visible part. The hidden parts are study time, practice material, a retake if you miss the passing score and any renewal that keeps the credential active. Add those up before you commit, and compare the total to the realistic benefit for the job you want.

A useful rule is to match the size of the commitment to the size of your gap. If you already use a tool daily, a short review and the exam may be enough. If the tool is new to you, plan on weeks of hands-on practice, because passing without real use leaves you unable to answer interview questions about it. Many vendors publish a skills outline and sample questions for free, so use those to estimate your starting point honestly.

Ask your employer, too. Some companies reimburse certification fees or give paid study time, especially for tools they already run. If you are between jobs, look at workforce programs near you, because some cover training costs for in-demand skills. Free funding is never guaranteed, but asking costs nothing and can turn a hesitant purchase into an easy one.

Which certifications should you skip?

Skip the ones that sell a result instead of a skill. The warning signs are easy to spot once you know them. A program that promises a salary, guarantees a job or advertises a "master" title after a weekend is selling hope. Another red flag is an issuer you cannot identify, with no published exam outline and no way to verify a credential once earned.

Also skip credentials that do not match your level. An advanced governance or engineering exam is a poor first purchase if you have never written a query. And skip collecting for its own sake. Five foundation badges tell a recruiter less than one tool credential and one solid project, because they show breadth without depth.

Finally, be wary of any credential whose name shows up in no job posting. Employers hire for the tools they run. If a certification does not appear in the listings you are targeting, it may still teach you something, but it will not do the signaling work you are paying for.

What does a certification mean for your career, pay and next move?

A certification is a lever on your next move, not a guarantee of a raise. Think about it in terms of which door you are trying to open.

If you are breaking in, a tool credential and a project can get your resume past a screen that otherwise would have passed over a career changer. In its Job Outlook 2026 survey, NACE found that 70% of responding employers use skill-based hiring, up from 65% the year before, and that 42% of the responding employers screen candidates by GPA, down from 73% in 2019. The respondents were mostly employers that hire new college graduates, so the numbers describe entry-level hiring and not every kind of employer. For early-career applicants, that is a reason to lead with proof of skill rather than a grade-point average.

If you already work in an analyst role, the question is different. A credential can support a case for a promotion or a move into a more technical or specialized track. Before a raise conversation, gather what you can: your current pay, the pay for similar roles, and your concrete results. A credential belongs in that file as supporting evidence, not as the whole argument.

The roles you might target next are worth researching on their own terms. O*NET publishes occupation summaries of tasks, tools and skills, including data scientists, statisticians, operations research analysts, market research analysts, management analysts and computer systems analysts. Reading two or three of them shows which software and skills each path expects, and that tells you which certification is the logical next step. Each summary is a separate page for its own occupation.

How do you prove the skills your certification covers?

A certification gets you noticed, and a project gets you believed. The strongest approach pairs them. After you pass an exam, build one or two projects that use the same tool on a real question, and describe the result in plain language on your resume and profile.

A good project has four parts.

• A question a business could actually ask, such as which products are losing sales or where wait times are longest.
• A public dataset you can clean, with a short note on what you removed and why.
• An analysis or dashboard built in the tool your credential covers.
• A one-paragraph summary of what you found and what you would recommend.

This matters because many hiring managers will test you directly. Part of the reason skills-based hiring is growing is that employers want to see ability on the job's own terms. In SHRM's October 2025 survey of HR professionals in the United States, 34% of organizations were reported to often or almost always use skills-first strategies. Skills-first hiring is far from universal, so assume both your credential and your resume story will be read.

When you apply, name the credential and the project in the same breath. "Earned the Power BI Data Analyst Associate credential and built a sales dashboard from public retail data" tells a recruiter more than either fact alone. Then keep applying while you keep learning. Metaintro lists openings across the country, so you can filter for roles that mention the tool you just proved.

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People Also Asked

Q: Is a beginner online data analytics program worth it?

A: Treat a beginner program the same way you would treat the credentials above. Check whether the postings you want mention it, whether the issuer stands behind a proctored exam, and whether you will build a project with it. A beginner program can teach the basics, but on its own it rarely separates you from other applicants.

Q: Can you get a data analyst job with only a certification?

A: It is possible but difficult. A certification proves you passed an exam, while employers also want to see you apply the skill. Pair your credential with at least one project, and consider an internship, volunteer analysis for a nonprofit or a stretch project at your current job.

Q: How many data analyst certifications do you need?

A: Usually one or two. Pick one that matches your target tool, add a foundation or programming credential if you have gaps, and stop there. Stacking many credentials takes time that would be better spent on projects and applications.

Ready to put your credential to work? Metaintro can help you find data analyst openings that match your skills, and you can Sign up to get started.