How to Become a Data Analyst in the UK
How to become a data analyst in the UK
Data analysts gather and clean data, look for patterns and trends, and turn what they find into charts and reports that help people decide what to do. You can come in through a degree, a college course, an apprenticeship or a government graduate scheme. This guide covers what the work involves, the formal routes in, and the order we suggest for building the practical skills.
See the learning pathFive self-paced courses, from first spreadsheet to code
The National Careers Service data analyst-statistician job profile lists day-to-day tasks including:
The same profile says you need maths knowledge, analytical thinking and logical reasoning, attention to detail, good verbal communication and a solid understanding of computer systems and applications.
typical starting salary a year
typical salary with experience
typical hours a week
Figures from the National Careers Service data analyst-statistician profile. Pay varies by employer, sector, location and seniority.
Not always. The National Careers Service lists several ways in:
A degree in a subject such as statistics, maths, economics, operational research or psychology, or a subject with statistics content such as social science or geography.
A college course in maths, statistics, computing or economics, or the T Level in Digital Data Analytics, which could lead to a junior role.
Including the Data Technician Level 3, Data Analyst Level 4 and Data Scientist Level 6 apprenticeships. You can search for vacancies on Find an apprenticeship.
Graduates can join the Government Statistical Service through the Civil Service Fast Stream, and graduates and experienced people can apply directly for roles such as statistical officer.
The profile also mentions the Royal Statistical Society for career development and volunteering schemes. Rootlet courses are practical training, not formal qualifications, so they won't replace a degree or apprenticeship. They are a good way to learn the tools analysts use every day, whether you're testing the idea, preparing for an apprenticeship or adding data skills to the job you already have.
Each course on this path ends with a final project. Keeping those projects, with a short note on the question you answered and how, gives you real examples to talk through in applications and interviews.
These five courses build on each other, from your first spreadsheet to working with data in code. Each one is full length and done at your own pace.
Step 1
Excel for Beginners starts from a blank sheet: entering and formatting data, your first formulas and essential functions, sorting, filtering and tables, XLOOKUP and VLOOKUP, charts and your first pivot tables.
View Excel for BeginnersStep 2
Intermediate Excel covers logical formulas, conditional sums and counts, lookups in depth, dynamic arrays, text and dates, data validation, Power Query for cleaning data, pivot tables in depth and building a dashboard.
View Intermediate ExcelStep 3
Most business data lives in databases. SQL for Beginners teaches you to filter, sort and calculate, work with dates, summarise with aggregates, join tables, and use subqueries, CTEs and window functions.
View SQL for BeginnersStep 4
Power BI for Beginners takes you through getting data in, cleaning it with Power Query, building a data model, visuals, DAX basics, dates and time, designing a clear report, and publishing and sharing it.
View Power BI for BeginnersStep 5
Python for Data Analysis uses pandas to select, filter and sort data, clean messy data, group and summarise, combine data sets, make charts with matplotlib and automate reports. If you've never coded, start with our free Python for Beginners course first.
View Python for Data AnalysisThe National Careers Service says that with experience you could become a senior or lead analyst or manage a data team, work as a freelance consultant, or move into data science, developing AI tools. Its profile is the best place to check current routes and apprenticeships.
Questions about any of these courses? Email support@rootlet.co.uk.