Why data and business analysts are in demand

From online shopping to healthcare planning, organisations rely on people who can turn data into decisions. That’s where data analysts and business analysts come in. Demand for both continues to grow across the UK.

If you’re considering your next step (or a career change), this guide covers roles, UK salary ranges, core skills, and study routes into the field.

Data analyst vs business analyst: what’s the difference?

The job titles are sometimes used interchangeably, but the focus can be different.

Data analysts work directly with datasets to find patterns, answer questions and build dashboards. They often use SQL and tools such as Power BI/Tableau, with Python or R for deeper analysis and automation.

Business analysts sit closer to operational decisions. They translate business needs into workable solutions, map processes, gather requirements and help improve how an organisation runs. They may use data, but communication and stakeholder management are central to the role.

In practice, many roles combine both,  especially in positions like Business Intelligence Analyst or Data and Insights Analyst. That's why employers value graduates who can connect technical analysis with real business context.

What does the job involve?

Analyst roles tend to be collaborative and varied. A typical week might include:

• Assessing performance (for example, a marketing campaign or service change)
• Building dashboards for teams to track key metrics
• Cleaning and preparing inconsistent data
• Explaining results to non-technical colleagues and leaders

The common thread is using evidence to support better decisions.

UK salaries: what can you expect?

Pay varies by location, sector and experience, but typical UK ranges are:

• Junior analyst: £25,000–£35,000
• Mid-level analyst: £35,000–£50,000
• Senior analyst: £50,000–£70,000+

Specialist or leadership roles (including analytics management, data science and consulting) can go higher.

Skills employers look for

Technical skills matter, but they’re most valuable when paired with judgement and communication.

Core technical skills

• SQL (querying databases is a daily requirement in many roles)
• Spreadsheets (Excel/Google Sheets are still widely used)
• Data visualisation tools (commonly Power BI or Tableau)
• Python or R (analysis, automation, working with larger datasets)

The skills that help you stand out

• Explaining insights clearly to non-specialists
• Critical thinking and curiosity (“what’s driving this result?”)
• Understanding goals and constraints in the real organisation
• Confidence challenging assumptions when the data doesn’t support a conclusion

Why choose this career?

Data and business analysis offers:

• Transferable skills across sectors (healthcare, finance, retail, government and more)
• Strong job security, as organisations rely more heavily on evidence-based decision-making
• Varied, problem-solving work with visible impact
• Clear progression, including specialisms (product, marketing, finance, people analytics) or leadership routes

For many people, that combination of stability, flexibility and progression makes analyst roles a strong long-term option.

Building the right foundations at UEL

If you’re choosing a course pathway, the most employable skill set usually combines technical capability with applied problem-solving and the ability to communicate insights.

For students starting at undergraduate level, UEL’s BSc (Hons) Data Science and Artificial Intelligence is designed to build core skills in data analysis, programming and applied AI, alongside the critical thinking needed to use data in real-world contexts.

For graduates and career changers who want to deepen expertise, UEL’s MSc Data Science takes a project-led approach focused on end-to-end data work - from framing questions and working with complex data to building solutions and communicating results clearly. Our MSc AI and Data Science boosts your practical knowledge and intellectual skills, while MSc Big Data Technologies teaches you to turn big data into meaningful insights and advice.

The realities to be aware of

Analyst work isn’t always tidy. Data can be messy, questions can be unclear, and stakeholders often want quick answers. Good analysts learn to:

• Clean and validate data before trusting it
• Define the real question behind the request
• Communicate uncertainty and limitations clearly
• Recommend next steps when the data can’t answer something directly

These are the professional habits that build trust and accelerate progression.

Is it right for you?

If you enjoy solving problems, working with evidence and explaining complex ideas clearly, data or business analysis can be a strong fit. Salaries are competitive, demand remains strong, and the skills transfer across industries.