Data science
A data science degree teaches how to collect, clean, analyse and learn from data, combining statistics, programming and machine learning with knowledge of real-world problems.
Updated How we use data
Data analysts collect, clean and study data to answer practical questions, such as which products sell best or where a service is failing. They present their findings in reports, charts and dashboards. Many have a degree in a subject such as mathematics, economics, business or computer science, but career changers often enter through short courses, apprenticeships and on-the-job training.
Data analysts work in almost every sector, including retail, banking, insurance, healthcare, marketing, logistics, telecommunications, charities and government. Some work in a central data team, while others sit in a department such as finance, sales or human resources. Consultancies and outsourcing firms also employ analysts to work on client projects. The job is mostly done at a computer in an office or at home, and hybrid working is common.
Essential skills listed for this occupation in ESCO, the European Commission's multilingual classification of skills and occupations.
Essential knowledge: information categorisation · resource description framework query language · visual presentation techniques · data quality assessment · information extraction · statistics · business intelligence · information structure
A degree in mathematics, statistics, economics, computer science, business or another subject that uses numbers is a common starting point. However, many employers focus on skills rather than a specific degree. You should be comfortable with spreadsheets, SQL and at least one data visualisation tool, and ideally know some Python or R. Career changers often move in from finance, marketing, operations or research roles, where they already work with data. A small portfolio of analysis projects using public data sets helps you show your skills, because interviews often include a practical test.
A data science degree teaches how to collect, clean, analyse and learn from data, combining statistics, programming and machine learning with knowledge of real-world problems.
A mathematics degree develops advanced reasoning and problem-solving through pure mathematics, such as algebra and analysis, and applied areas, such as statistics, modelling and computing.
An economics degree studies how people, businesses and governments make choices with limited resources, and how markets, money and policy affect jobs, prices and growth.
A computer science degree teaches how software, data and computer systems work, from programming and algorithms to networks and artificial intelligence.
A business management degree teaches how organisations are run, including strategy, marketing, finance, people management and operations.
Ready to apply? Build a free CV and cover letter with our CV builder
Data analysis is not a regulated profession, and you do not need a licence to work as a data analyst. You must follow data protection and privacy laws, which vary between countries, and some sectors such as healthcare and banking have extra rules on how data can be used. Certifications from software providers and professional bodies are optional, but they can help beginners show their skills.
The US Bureau of Labor Statistics does not publish a separate pay estimate that matches this occupation, so we do not show one.
Most countries do not publish pay for single job titles. The International Labour Organization collects median monthly earnings for broad occupation groups instead. This career belongs to ISCO-08 major group 2, "Professionals". The table covers the whole group, which includes data analyst and many other occupations.
| Country | Local currency a month | PPP$ a month | vs all employees | Year |
|---|---|---|---|---|
| Netherlands | €6,217 | 8,102 | +22% | 2025 |
| Germany | €5,315 | 7,389 | +41% | 2022 |
| France | €5,314 | 7,255 | +43% | 2025 |
| Switzerland | CHF 7,600 | 7,133 | +27% | 2025 |
| Ireland | €6,252 | 6,917 | +56% | 2025 |
| Spain | €4,153 | 6,832 | +57% | 2025 |
| United States | $6,673 | 6,673 | +49% | 2025 |
| Italy | €3,716 | 5,762 | +19% | 2025 |
| Sweden | €4,398 | 5,491 | +13% | 2025 |
| United Kingdom | £3,501 | 4,991 | +29% | 2025 |
| Türkiye | TRY 60,000 | 3,381 | +100% | 2025 |
| South Africa | ZAR 17,000 | 2,292 | +209% | 2020 |
| Brazil | R$5,000 | 1,937 | +127% | 2025 |
| India | ₹32,000 | 1,613 | +113% | 2025 |
| Philippines | ₱30,417 | 1,466 | +100% | 2024 |
| Mexico | MX$14,745 | 1,304 | +68% | 2025 |
| Egypt | EGP 5,000 | 719 | +10% | 2024 |
| Indonesia | IDR 2,759,817 | 537 | +23% | 2023 |
| Pakistan | PKR 34,640 | 530 | +34% | 2025 |
| Nigeria | NGN 50,000 | 188 | 0% | 2024 |
Source: ILOSTAT, median monthly earnings of employees, latest year available. PPP$ adjusts for price differences between countries so figures can be compared. "vs all employees" compares the group's median with the median for all occupations in the same country.
Organisations in every sector rely on data to plan and measure their work, which keeps demand for analysts broad. AI tools can now write queries, summarise data and build simple charts, so routine reporting is likely to need fewer people. Analysts who understand the business, ask good questions, check results critically and explain them clearly should remain valuable. Many people use the role as a stepping stone to data science, data engineering or management.
Yes, in many countries. Employers often care more about practical skills in SQL, spreadsheets and visualisation than about a specific degree, and some offer apprenticeships. However, many job adverts still ask for a degree, so without one you usually need a strong portfolio, relevant work experience or an internal move.
The core skills are SQL, advanced spreadsheets, a data visualisation tool and basic statistics, and Python or R is increasingly expected. Equally important are attention to detail, curiosity and the ability to explain your findings to people who are not data specialists.
It is one of the more accessible routes into technology. The basic tools can be learned in months, and many roles value knowledge of a sector such as finance, health or retail. Competition for entry-level jobs can be strong, so combining new data skills with your existing industry experience is often the best approach.
AI tools already automate parts of the job, such as writing queries and producing standard reports. They still make mistakes and cannot judge which questions matter to a business. Analysts who can frame problems, check data quality and turn results into decisions are likely to stay in demand, but entry-level work is changing.
Data scientists use statistics, programming and machine learning to find patterns in data and help organisations make decisions or build data-driven products.
Business analysts help organisations improve the way they work.
Statisticians collect, analyse and interpret data to answer questions and support decisions.
Financial analysts study financial data, markets and company performance to help businesses and investors make decisions about money.
How to cite this page: CourseToJob (2026). How to become a data analyst: degrees, skills and salary. https://coursetojob.com/careers/data-analyst/ (accessed September 26, 2026)