Best IT Certifications for Data Professionals

Picking a data certification is really a decision about which role you want to be paid for. An analyst who spends $165 (US price) on Microsoft's PL-300 exam is buying something quite different from an engineer sitting a cloud data engineering exam or a scientist proving machine learning skills — and the most common mistake data professionals make is choosing a well-known credential from the wrong track. This guide sorts the leading certifications by role — analyst, engineer, scientist, plus the BI and database specialisms that sit between them — so you can match a credential to the job you actually want.

One framing note before the lists: everything here is organised by track, not ranked into a single top ten. A "best certification" only exists relative to your target role, your current skills and the tools your market hires for. If you are brand new to data with no experience at all, the entry-level picks are compared in more depth in our guide to the best data certifications for beginners.

How to choose your track first

Before comparing exams, decide which of these descriptions fits the work you want to do, because certifications rarely transfer well between tracks:

• Data analyst — you answer business questions with data: cleaning, modelling, visualising and reporting, typically in Power BI, Tableau, SQL and spreadsheets.
• Data engineer — you build and run the pipelines and platforms that move and store data: ingestion, transformation, orchestration, warehousing, usually in cloud platforms with SQL and Python or Spark.
• Data scientist / ML practitioner — you build statistical and machine learning models on top of that data.
• BI / database specialist — you own the reporting layer or the database platform itself, a lane that overlaps the analyst track but goes deeper on one toolset.

A simple test: look at five job adverts you would genuinely apply for and note which certifications and tools they name. Certify towards the adverts, not towards whichever exam is most talked about.

Best certifications for data analysts

Microsoft PL-300: Power BI Data Analyst

The PL-300 exam earns the Microsoft Certified: Power BI Data Analyst Associate credential and is the most direct certification signal for analyst roles in Microsoft-centric organisations. It is an intermediate-level, proctored exam covering four skill areas — preparing data, modelling data, visualising and analysing data, and managing and securing Power BI — and expects real proficiency with Power Query and DAX, not just chart-building.

Key facts as of 2026: the exam runs 100 minutes, is delivered by Pearson VUE at a test centre or online, costs $165 USD in the United States (pricing varies by country), and requires a 700 score on a 1,000-point scale. Microsoft does not publish an official question count, so treat circulating figures as community reports. The certification is valid for 12 months and renews free through an online assessment on Microsoft Learn — you never pay to keep it current if you renew on time. Once you have covered the four domains, working through PL-300 practice questions under timed conditions is a sensible way to find which domain needs another pass before you book.

Deeper questions about this exam — difficulty, prep planning and whether it pays off — are covered in the dedicated Microsoft Power BI certification guide.

Salesforce Certified Tableau Data Analyst

If your market runs on Tableau rather than Power BI, the analyst-tier Tableau credential is the equivalent signal. Note the naming: since Salesforce migrated all Tableau certifications onto Trailhead Academy on 21 July 2025, the exams carry "Salesforce Certified Tableau" names, though delivery remains via Pearson VUE and job adverts often still use the old names. The Data Analyst exam is commonly listed at $250 USD — confirm the current fee on Trailhead Academy, as post-migration pricing comes from secondary sources — with no formal prerequisites, though roughly six months of Tableau experience has been the historical recommendation. Whether the exam still includes hands-on lab tasks after the migration is not confirmed, so check the current official exam guide. The full tier structure is unpacked in Tableau Certifications Explained.

CompTIA Data+ (DA0-002)

Data+ is the vendor-neutral option: a single exam covering analytics concepts, data quality, visualisation and governance without tying you to one tool. The current version is DA0-002, with a maximum of 90 questions (multiple-choice and performance-based) in 90 minutes and a passing score of 675 on a 100–900 scale. Pricing is about $264 USD as of mid-2026 following CompTIA's May 2026 voucher increase — confirm on comptia.org. There are no prerequisites, though CompTIA suggests around 1.5–2 years in a data-adjacent role. It suits analysts who want a tool-agnostic credential alongside, rather than instead of, a Power BI or Tableau certification.

Where the Google Data Analytics Certificate fits

The Google Data Analytics Professional Certificate on Coursera appears on most analyst lists, but it is a different kind of credential: a course-based professional certificate you complete through graded coursework, not a proctored certification exam. There is no exam code and no pass/fail test, and it cannot expire the way a certification does. Google estimates about six months at ten hours per week across its eight courses, billed by Coursera subscription (widely reported at $49/month for the individual certificate, with Coursera Plus quoted at $59/month in Coursera's own 2026 material — regional pricing varies). Treat it as structured training that prepares you for exams like Data+ or PL-300, not as a substitute for them.

Best certifications for data engineers

Data engineering credentials are dominated by the cloud platforms, so your employer's (or target employer's) cloud usually decides the exam.

Microsoft DP-700: Fabric Data Engineer Associate

DP-700 (Implementing Data Engineering Solutions Using Microsoft Fabric) is Microsoft's current data engineering exam, introduced as the Fabric-era successor after Microsoft retired the Azure-focused DP-203. It covers implementing and managing an analytics solution, ingesting and transforming data, and monitoring and optimisation, and expects working SQL, PySpark and KQL. Logistics match Microsoft's associate pattern: 100 minutes, Pearson VUE delivery, $165 USD in the US, 700/1,000 to pass, 12-month validity with free online renewal. For engineers in Microsoft shops this is now the default pick, and the Microsoft exams hub lists the wider family of Microsoft data exams if you want to see what sits around it.

AWS Certified Data Engineer – Associate

For AWS-centred teams, the AWS Certified Data Engineer – Associate (DEA-C01) is the platform-native equivalent. This guide's research scope does not extend to verified AWS exam logistics, so check the format, fee and domain weightings on AWS's official certification page before planning around it; you can preview the style of questions involved on the AWS Certified Data Engineer Associate exam page.

Google Cloud Professional Data Engineer

Google Cloud's Professional Data Engineer plays the same role for GCP-based organisations: a professional-level credential for people who design and operationalise data processing systems on Google Cloud. Again, confirm current format and pricing on Google Cloud's certification site; the Professional Data Engineer exam page gives a feel for the exam's territory.

Databricks and Snowflake

Two platform-specific credentials worth knowing exist alongside the big clouds: Databricks' Certified Data Engineer track (for lakehouse and Spark-heavy environments) and Snowflake's SnowPro certifications (for Snowflake warehousing shops). Neither is covered by verified exam data here, so treat them as targets to research on the vendors' official certification pages once you know your stack. The practical rule: certify on the platform your pipelines actually run on — a Databricks credential in a Snowflake shop signals less than hands-on relevance would.