Data Analyst skills

Essential skills

• Data cleaning: Employers may ask you to explain how you found and handled missing, duplicate, or inconsistent data.
• Data analysis: Employers may give you a dataset and ask you to identify patterns or answer a business question.
• Basic statistics: Employers may check whether you can interpret averages, variation, and relationships without overstating what the data shows.
• Data visualisation: Employers may ask you to choose a chart and explain how it makes findings clear.
• Business understanding: Employers may ask how your analysis could help answer a practical question or support a decision.

Technical and specialised skills

• Spreadsheets: Employers may test formulas, pivot tables, data sorting, and basic charts.
• SQL: Employers may ask you to write queries that filter, join, group, and summarise data.
• Python or R: Employers may review a small script or ask how you would use code to prepare or analyse data.
• Dashboard tools: Employers may ask you to build or explain a dashboard that helps people track useful measures.
• Data quality and privacy: Employers may ask how you check accuracy and handle sensitive information responsibly.
• Specialised methods: For some roles, employers may assess skills such as forecasting, experimentation, or working with a particular type of data.

Soft skills

• Communication: Employers may ask you to explain a finding to someone without a technical background.
• Critical thinking: Employers may test how you question assumptions, investigate unusual results, and judge whether evidence supports a conclusion.
• Problem-solving: Employers may give you an open-ended task and look at how you break it into manageable steps.
• Attention to detail: Employers may check whether you spot errors, unclear labels, or inconsistent results in your work.
• Collaboration: Employers may ask how you have worked with others to clarify requirements or share findings.
• Time management: Employers may ask how you prioritise tasks when deadlines or requests compete.

How to show these skills on your resume

• Cleaned and analysed a project dataset using SQL and spreadsheets, documenting data issues and presenting the main findings.
• Built a dashboard to track key measures, with clear labels and views tailored to the audience.
• Explained analysis to a non-technical audience and recommended next steps based on the evidence.

How to build them

• Practise with public or sample datasets, starting with a question you want the data to answer.
• Learn spreadsheet skills and SQL first, then add a programming language or dashboard tool relevant to the roles you want.
• Create small projects that include data cleaning, analysis, and a clear summary of your findings.
• Ask someone to review your work for accuracy, clarity, and usefulness.
• Practise explaining your methods and conclusions in plain language, including what the data cannot tell you.
• Read job descriptions for roles you want and use them to guide what you learn and practise.