How to become a data analyst

Data analysts collect, process, and interpret data to help organisations make business decisions. From customer databases and sales records to social media metrics and market research, they use various data sources to inform their analysis. 

Their main responsibilities typically include organising raw data, conducting statistical analysis, identifying patterns and trends, and presenting their findings to stakeholders. Their roles often involve using various software, programming languages, and data visualisation tools to create clear, actionable insights from complex data. 

Demand for data analysts (external link) continues to grow as businesses increasingly rely on data to inform decisions.

Employers typically seek candidates with strong thinking, mathematical, and technical skills. While formal qualifications are not always required, they can provide a solid foundation for work in the data sector. 

Degrees and certifications 

There are many ways for data analysts to gain relevant skills and experience. 

For example, at universities: 

• Statistics or Mathematics degrees teach statistical methods, probability theory, and mathematical modelling.
• Computer Science degrees offer programming skills, database management knowledge, and an understanding of algorithms.
• Economics or Business degrees combine business analysis and theory, helping analysts understand commercial applications of their work.
• Data Science or Analytics degrees cover statistics, programming, and business applications. 

There are also various certifications to explore: 

• Google Data Analytics Professional Certificate covers fundamentals, SQL, R programming, and visualisation tools.
• Microsoft Certified: Data Analyst Associate tests skills in Power BI, data modelling, and creating intelligence solutions.
• Tableau Desktop Specialist certification demonstrates understanding of one of the leading data visualisation tools in the industry. 

Alternative qualifications 

While formal training can be beneficial, it is not always essential and may not be suitable for everyone. Many data analysts choose more independent, alternative routes. 

For instance, online learning platforms like Coursera, edX, and Udemy offer flexible data analysis courses that can be completed alongside existing work or study commitments. 

Free resources like YouTube tutorials and open-source software documentation can help you learn foundational skills. Alternatively, coding bootcamps can provide intensive, practical training in the most-used programming languages, like Python and SQL. 

Having developed the essential skills, many non-qualified data analysts develop a portfolio to demonstrate their proficiency to employers.

Regular teamwork on complex datasets means that data analysis requires both technical abilities and interpersonal skills. 

Hard skills, such as proficiency in programming languages like Python, R, or SQL, as well as data visualisation tools like Tableau or Power BI, are often required. Statistical knowledge and database management are typically valued. Understanding data ethics and privacy principles is also increasingly important, as analysts must handle sensitive information responsibly and comply with data protection regulations. 

Soft skills can be equally important. Communication is crucial, helping analysts explain their technical findings to non-technical stakeholders clearly and coherently. Attention to detail and effective time management are also typically highly valued, enabling analysts to handle multiple projects and meet tight deadlines.

Many data analysts build a portfolio of independent projects to demonstrate their skills to potential employers. Using government sources or industry-specific databases to practice data cleaning, analysis, and visualisation techniques can help you showcase your abilities. 

Platforms like GitHub let you share code, document your processes, and collaborate with others, creating a visible, public portfolio of your work and helping you refine your skills. Short-term freelancing opportunities can also help you gain valuable experience across different industries.

Salaries can vary significantly between roles and industries. GOV.UK (external link) states that entry-level salaries may start at £23,000 per year, while experienced analysts can earn £60,000 or more. 

Data analysts can use their skills in various industries, including finance, healthcare, sports, and pharmaceuticals. With experience, you might become a senior analyst, specialise in business intelligence analysis, or transition into a management role. Many analysts also use their knowledge to teach or start a consultancy business.

Data analysis can be a rewarding job, valuing both technical and interpersonal skills. There are opportunities for continuous learning and for exploring different sectors, as programming languages are constantly evolving and becoming more sophisticated. If you enjoy working with numbers, problem-solving, and turning information into insights, data analysis may be a good fit for you. 

For small businesses looking to leverage data analysis, protecting the valuable insights and customer information you handle is essential. Understanding your responsibilities around data protection and having the right safeguards in place can help you grow with confidence.