Data Analyst Interview Questions and Answers (UK): SQL, Excel, Power BI and Case Tasks

Data roles are among the most searched jobs in the UK, and their interviews follow a pattern: some technical questions, a practical task, and a lot of focus on how you communicate what the numbers mean. If you can show that you turn data into decisions, you will stand out from candidates who only list tools.

This guide covers what to expect at a data analyst interview in the UK, the questions that come up most, and sample answers you can adapt to your own experience.

What to expect at a data analyst interview

A typical process is a recruiter call, a technical screen, a take-home task or live exercise and a final interview with the hiring manager and stakeholders. The task may involve cleaning a messy dataset, writing SQL queries, building a dashboard in Power BI or Tableau, or presenting findings to a non-technical audience. Time limits are normal, so practise working to one.

Interview question: What is the difference between INNER JOIN and LEFT JOIN?

An inner join returns only rows that match in both tables. A left join returns all rows from the left table and the matching rows from the right, with nulls where there is no match. Give a quick example: "customers LEFT JOIN orders shows every customer, including those who have never ordered."

Interview question: How would you find duplicates in a table?

Group by the columns that should be unique and filter with HAVING COUNT(*) greater than 1. You can also use ROW_NUMBER() over a partition to flag and remove duplicates. Mention that you would first ask what counts as a duplicate, because that depends on the business definition.

Interview question: How do you clean a messy dataset?

Show a process: profile the data, check for missing values, duplicates, inconsistent formats, outliers and wrong data types, decide how to treat each one with the business context, document what you changed and keep the original data. "I would not simply delete missing values. I would ask why they are missing and whether they matter for the question."

Interview question: Explain a time you used data to influence a decision

This is the most important question. Use a clear structure: the business question, the data you used, your analysis, your recommendation and the outcome. Add numbers. "Sales were dropping in one region. I compared conversion by channel and found most of the fall came from one paid campaign. We shifted budget and recovered the lost conversions within two months."

Interview question: What is the difference between correlation and causation?

Correlation means two things move together. Causation means one produces the other. Ice cream sales and sunburn both rise in summer, but one does not cause the other. To test causation you need an experiment, such as an A/B test, or careful analysis that controls for other factors.

Interview question: How would you explain a result to a non-technical manager?

Lead with the answer, not the method. Use plain words, one clear chart, and say what you recommend and how confident you are. Avoid jargon. This is a skill UK employers repeatedly ask for.

Excel and Power BI questions

Be ready for VLOOKUP and XLOOKUP, INDEX MATCH, pivot tables, conditional formatting and basic formulas. For Power BI or Tableau, know the difference between a measure and a calculated column, how relationships work and what makes a dashboard useful rather than cluttered. For Power BI, DAX questions such as CALCULATE and time intelligence are common.

Statistics questions

Know mean, median and mode, standard deviation, confidence intervals, p-values and hypothesis testing in plain language. A p-value is the probability of seeing a result at least this extreme if there is no real effect. Explain A/B testing and sample size.

Data scientist and machine learning questions

Expect questions on regression and classification, overfitting and how to avoid it (cross-validation, regularisation), evaluation metrics such as precision, recall and AUC, feature engineering and how you would put a model into production. Employers increasingly ask about responsible AI, bias and explaining model decisions.

UK specific: data protection

Know the basics of UK GDPR: personal data must be used lawfully, kept secure and not kept longer than necessary. Be able to explain anonymisation versus pseudonymisation and why you would avoid sharing personal data when you do not need to.

Behavioural questions

• Tell me about a time your analysis was wrong. What did you do?

• How do you prioritise when several people ask for reports?

• Describe a time you disagreed with a stakeholder about what the data showed.

Common mistakes

• Listing tools without showing outcomes.

• Presenting a dashboard with no recommendation.

• Not asking clarifying questions before diving into the task.

Quick answers

Do I need a degree to be a data analyst? Not always. A portfolio and proven skills with SQL, Excel and a BI tool matter a lot.

Which language should I learn? SQL first, then Python or R.

What salary can I expect? It varies by region and sector, so check current adverts for the role you want.

Our question bank includes data and analytics roles with model answers, and every role has five questions free.

Practise for specific roles

Pick your role: Data Analyst, Business Intelligence Analyst, Data Scientist, Data Engineer, Machine Learning Engineer.