DataCamp for Business vs. Cloud Academy: Which Is Better in 2026?
DataCamp for Business is better for data and AI upskilling across a whole workforce. Cloud Academy (now QA) is better for cloud and IT certification teams.
The main question is who you're training. DataCamp for Business is the better choice for building data and AI skills across a whole workforce, from analysts to executives. Cloud Academy is a great choice for engineering and IT teams preparing for cloud and security certifications in live cloud environments.
A key thing to know: Cloud Academy isn't a standalone company anymore. QA acquired it and folded it into a single brand. Many buyers still search for it as Cloud Academy, which is why we use both names here.
DataCamp for Business vs. Cloud Academy at a Glance
DataCamp for Business is built for data and AI literacy at scale, with interactive coding and role-based paths for technical and non-technical staff.
Cloud Academy (QA) is built for cloud infrastructure, cybersecurity, and IT certifications, with labs that run in real AWS, Azure, and Google Cloud environments.
Choose DataCamp if your goal is company-wide data and AI upskilling with measurable skill gains.
Choose QA if your goal is getting engineers certified on cloud platforms, or you need a mix of IT, project management, and classroom training from one vendor.
What Is DataCamp for Business?
DataCamp for Business is our team and enterprise plan for data and AI training. It includes hundres of interactive courses, learning paths, and real-world projects, all taught through in-browser coding, with a powerful AI tutor, rather than video alone.
It covers the full range of roles in a data program. Engineers learn Python, SQL, and machine learning, while business teams get AI literacy, Power BI, and role-based courses for functions like finance, marketing, and HR. 80% of the Fortune 1000 use DataCamp for Business.
What Is Cloud Academy (Now QA)?
Cloud Academy is a cloud training platform that QA, a UK-based technology training company, bought and later merged into its own brand. Today it's the QA Learning Platform, the self-paced side of a business that also runs classroom courses, apprenticeships, and certification programs.
Its core strength is cloud and IT. The platform offers learning paths for AWS, Microsoft Azure, and Google Cloud, plus hands-on labs in real cloud environments. QA's wider catalog adds cybersecurity, ITIL, PRINCE2, agile, and project management.
DataCamp for Business vs. Cloud Academy: Head-to-Head Comparison
The main difference is scope: DataCamp goes deep on data and AI for every role, while QA goes deep on cloud and IT for technical teams.
Feature
DataCamp for Business
Cloud Academy (QA)
Main focus
Data and AI skills
Cloud, cybersecurity, and IT
Best for
Company-wide upskilling, all roles
Engineering and IT teams
Hands-on practice
In-browser coding, projects, AI tutor
Labs in real cloud environments
Certifications
Data and AI certifications, plus AWS and Azure entry level
Prep for AWS, Azure, Google Cloud, CompTIA, Cisco, and more
Live training
Live cohorts, bootcamps, masterclasses
Classroom and virtual courses, apprenticeships
Starting price
$28 per user/month (Teams, billed annually)
From $39 per user/month
Who each platform serves
This is the dimension that decides most purchases. DataCamp is built around data and AI, and it's designed for every level of the organization, not just technical staff.
Bayer is a good example. It organized its data academy into tiers spanning finance and admin staff through to advanced data scientists, and enrolled 3,400+ employees. That kind of mixed audience is where DataCamp fits best.
QA covers a wider spread of IT topics but leans technical. If you need cloud architects, security engineers, and IT service managers trained by the same vendor, QA's catalog fits that brief better. Its data and AI content exists, but it isn't the center of the platform.
Hands-on practice
Both platforms put practice first, but the practice looks very different.
DataCamp's exercises run in the browser. Learners write real Python, SQL, or R code from the first lesson, get instant feedback, and can ask an AI tutor for help. There's nothing to install and no cloud account to manage.
QA's labs run in live AWS, Azure, and Google Cloud environments. Learners provision and configure real resources, which is hard to replicate any other way. Reviewers on Capterra consistently name the labs as the platform's best feature, though some also say parts of the course library feel dated.
For data and AI work, browser-based coding gets learners productive faster. For cloud operations, nothing beats a real console.
Certifications
Each platform certifies the skills it teaches best.
DataCamp offers its own certifications in data analysis, data science, data engineering, SQL, and AI engineering, each with a timed exam and a practical. It also covers entry-level cloud with tracks for AWS Cloud Practitioner and Azure Fundamentals (AZ-900).
QA prepares learners for a much longer list of vendor exams, including professional-level AWS, Azure, and Google Cloud certifications, CompTIA, and Cisco. If your training plan is measured in vendor certifications passed, QA has the deeper bench.
Admin, reporting, and integrations
Both platforms cover the basics buyers expect: admin dashboards, progress tracking, and single sign-on (SSO).
DataCamp adds skill assessments that benchmark employees before training, then recommend paths based on their gaps. On Enterprise plans, it also integrates with learning management systems (LMS). Colgate-Palmolive used SSO and a Degreed integration to run a program for 14,860+ employees.
QA lists integrations with Okta, Microsoft Entra ID, and Degreed, plus skills assessments and custom learning paths. On reporting, the two are close; the bigger difference is what's being measured.
Instructor-led training ,/ custom content
QA's background is classroom training, and it shows. It runs in-person and virtual courses, short live sessions, and UK apprenticeship programs alongside the self-paced platform.
DataCamp offers live cohorts, bootcamps, and masterclasses, and can build custom curriculum around your own data and tools. Rolls-Royce used this to run Python training for engineers next to Power BI and data literacy for non-technical staff.
If you need large-scale classroom delivery across many IT topics, QA has more of it. If you need live training focused on data and AI, DataCamp covers it.
Pricing
DataCamp is easier to price up front. The Teams plan costs $28 per user per month, billed annually, for teams of 2 or more. Enterprise and Unlimited plans are quoted and add SSO, LMS integration, custom tracks, and professional services.
Capterra lists QA's plans from $39 per user per month, and business pricing is quoted on request.
For small teams, DataCamp is the cheaper way to start. For larger rollouts, both vendors will quote, so compare like for like. Pricing note: Business and enterprise rates are often quoted individually, so confirm current pricing with each vendor.
Which Is Better for Your Team?
DataCamp for Business is the better choice for most data and AI training programs. QA is the better choice when cloud and IT certification is the goal.
Use case
Recommended
Why
Company-wide AI literacy
DataCamp
Role-based AI courses for technical and non-technical staff
Upskilling analysts and data scientists
DataCamp
Deep Python, SQL, and machine learning catalog with coding practice
Broad IT catalog, including CompTIA, Cisco, and ITIL
Large-scale classroom delivery
QA
Long history of in-person and virtual instructor-led courses
Choose DataCamp for Business if:
You want data and AI skills across the whole company, not just in engineering
You need to measure skill gaps and show progress to leadership
You want to start small with a self-serve plan
Choose Cloud Academy (QA) if:
Your priority is cloud certifications for engineers and IT staff
You need real cloud environments for hands-on practice
You want one vendor for IT, security, and project management training
Final Thoughts
For most organizations investing in data and AI skills, DataCamp for Business is the better fit. It reaches every role, starts with practice instead of video, and makes it easy to measure what employees actually learned.
QA AKA Cloud Academy earns its place for a different job. If you're training cloud engineers for vendor certifications, its live labs and exam prep are hard to beat. T
I'm a data science editor with contributions to research articles in scientific journals. I'm especially interested in linear algebra, statistics, R, and the like.
FAQs
Is Cloud Academy still available?⌄
Yes, but under a different name. QA acquired Cloud Academy and merged it into its own brand, so the platform is now the QA Learning Platform. Existing Cloud Academy links redirect to QA's site.
Is DataCamp or Cloud Academy better for AI training?⌄
DataCamp. It offers role-based AI courses for business functions, AI literacy content for executives, and technical AI engineering paths, all on one platform. QA covers AI too, but its platform is centered on cloud and IT.
Which is cheaper, DataCamp for Business or Cloud Academy?⌄
DataCamp's Teams plan starts at $28 per user per month, billed annually, for teams of 2 or more. Capterra lists QA's plans from $39 per user per month. Both quote custom pricing for larger organizations.
Does DataCamp cover cloud certifications?⌄
Yes, at the entry level. DataCamp has tracks for AWS Cloud Practitioner and Azure Fundamentals (AZ-900), plus courses on Azure, AWS, Databricks, and Snowflake. For professional-level cloud certifications, QA offers deeper exam prep.
Can we use DataCamp and Cloud Academy together?⌄
Yes. A common split is QA for cloud and security certification and DataCamp for data and AI upskilling across the business. Both support SSO and integrate with LMS platforms like Degreed.
The main question is who you're training. DataCamp for Business is the better choice for building data and AI skills across a whole workforce, from analysts to executives. Cloud Academy is a great choice for engineering and IT teams preparing for cloud and security certifications in live cloud environments.
A key thing to know: Cloud Academy isn't a standalone company anymore. QA acquired it and folded it into a single brand. Many buyers still search for it as Cloud Academy, which is why we use both names here.
DataCamp for Business vs. Cloud Academy at a Glance
What Is DataCamp for Business?
DataCamp for Business is our team and enterprise plan for data and AI training. It includes hundres of interactive courses, learning paths, and real-world projects, all taught through in-browser coding, with a powerful AI tutor, rather than video alone.
It covers the full range of roles in a data program. Engineers learn Python, SQL, and machine learning, while business teams get AI literacy, Power BI, and role-based courses for functions like finance, marketing, and HR. 80% of the Fortune 1000 use DataCamp for Business.
What Is Cloud Academy (Now QA)?
Cloud Academy is a cloud training platform that QA, a UK-based technology training company, bought and later merged into its own brand. Today it's the QA Learning Platform, the self-paced side of a business that also runs classroom courses, apprenticeships, and certification programs.
Its core strength is cloud and IT. The platform offers learning paths for AWS, Microsoft Azure, and Google Cloud, plus hands-on labs in real cloud environments. QA's wider catalog adds cybersecurity, ITIL, PRINCE2, agile, and project management.
DataCamp for Business vs. Cloud Academy: Head-to-Head Comparison
The main difference is scope: DataCamp goes deep on data and AI for every role, while QA goes deep on cloud and IT for technical teams.
Who each platform serves
This is the dimension that decides most purchases. DataCamp is built around data and AI, and it's designed for every level of the organization, not just technical staff.
Bayer is a good example. It organized its data academy into tiers spanning finance and admin staff through to advanced data scientists, and enrolled 3,400+ employees. That kind of mixed audience is where DataCamp fits best.
QA covers a wider spread of IT topics but leans technical. If you need cloud architects, security engineers, and IT service managers trained by the same vendor, QA's catalog fits that brief better. Its data and AI content exists, but it isn't the center of the platform.
Hands-on practice
Both platforms put practice first, but the practice looks very different.
DataCamp's exercises run in the browser. Learners write real Python, SQL, or R code from the first lesson, get instant feedback, and can ask an AI tutor for help. There's nothing to install and no cloud account to manage.
QA's labs run in live AWS, Azure, and Google Cloud environments. Learners provision and configure real resources, which is hard to replicate any other way. Reviewers on Capterra consistently name the labs as the platform's best feature, though some also say parts of the course library feel dated.
For data and AI work, browser-based coding gets learners productive faster. For cloud operations, nothing beats a real console.
Certifications
Each platform certifies the skills it teaches best.
DataCamp offers its own certifications in data analysis, data science, data engineering, SQL, and AI engineering, each with a timed exam and a practical. It also covers entry-level cloud with tracks for AWS Cloud Practitioner and Azure Fundamentals (AZ-900).
QA prepares learners for a much longer list of vendor exams, including professional-level AWS, Azure, and Google Cloud certifications, CompTIA, and Cisco. If your training plan is measured in vendor certifications passed, QA has the deeper bench.
Admin, reporting, and integrations
Both platforms cover the basics buyers expect: admin dashboards, progress tracking, and single sign-on (SSO).
DataCamp adds skill assessments that benchmark employees before training, then recommend paths based on their gaps. On Enterprise plans, it also integrates with learning management systems (LMS). Colgate-Palmolive used SSO and a Degreed integration to run a program for 14,860+ employees.
QA lists integrations with Okta, Microsoft Entra ID, and Degreed, plus skills assessments and custom learning paths. On reporting, the two are close; the bigger difference is what's being measured.
Instructor-led training ,/ custom content
QA's background is classroom training, and it shows. It runs in-person and virtual courses, short live sessions, and UK apprenticeship programs alongside the self-paced platform.
DataCamp offers live cohorts, bootcamps, and masterclasses, and can build custom curriculum around your own data and tools. Rolls-Royce used this to run Python training for engineers next to Power BI and data literacy for non-technical staff.
If you need large-scale classroom delivery across many IT topics, QA has more of it. If you need live training focused on data and AI, DataCamp covers it.
Pricing
DataCamp is easier to price up front. The Teams plan costs $28 per user per month, billed annually, for teams of 2 or more. Enterprise and Unlimited plans are quoted and add SSO, LMS integration, custom tracks, and professional services.
Capterra lists QA's plans from $39 per user per month, and business pricing is quoted on request.
For small teams, DataCamp is the cheaper way to start. For larger rollouts, both vendors will quote, so compare like for like. Pricing note: Business and enterprise rates are often quoted individually, so confirm current pricing with each vendor.
Which Is Better for Your Team?
DataCamp for Business is the better choice for most data and AI training programs. QA is the better choice when cloud and IT certification is the goal.
Choose DataCamp for Business if:
Choose Cloud Academy (QA) if:
Final Thoughts
For most organizations investing in data and AI skills, DataCamp for Business is the better fit. It reaches every role, starts with practice instead of video, and makes it easy to measure what employees actually learned.
QA AKA Cloud Academy earns its place for a different job. If you're training cloud engineers for vendor certifications, its live labs and exam prep are hard to beat. T
If you're building a business case for data and AI training, our guide to the best platforms for enterprise AI upskilling is a good next step.