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Data analyst interview prep

Data Analyst Interview Questions: SQL, Stats and Business Sense

Data analyst interviews usually have three parts: SQL and Excel skills, basic statistics, and a business case where you turn a vague question into metrics. Expect to write a query live and explain how a dashboard or analysis changed a decision.

Practise with AI Interview PrepSee data analyst resume
  • 15 questions answered
  • SQL and Excel
  • Case questions
  • Fresher to 3 years

Sample answers

Connect every answer to a decision.

Interviewers want to see that you understand why the numbers matter, not just how to get them.

Model answers for 4 data analyst questions

Typical rounds: SQL test, technical interview, case or presentation

Q: Daily orders dropped 15% yesterday. How would you investigate? A: First confirm it's real: check data pipeline delays and tracking changes. Then segment the drop by platform, city, new vs returning users and funnel step to find where it is concentrated, compare with the same weekday last week, and check for releases, outages, holidays or competitor promotions.

Q: How do you handle missing data? A: Find out why it's missing first. Then drop rows if the share is small and random, impute with median or a business default if reasonable, or flag it as a separate category. I always note the choice and its effect in the report.

Q: What is the difference between mean and median, and when do you use each? A: The mean is the average and is pulled by outliers; the median is the middle value. For skewed data like order value or salary, the median gives a more honest typical value.

Q: Tell me about a dashboard you built. A: I built a Power BI sales dashboard for 12 regional managers with filters by region and product. It replaced a weekly Excel report, saved about 6 hours a week, and helped managers spot two slow product lines early.

What interviewers check

Built for scanners, humans and hiring intent.

  • SQL fluency

    Joins, GROUP BY, window functions and subqueries on a realistic schema are tested in almost every round.

  • Metrics thinking

    Choosing the right KPI and explaining changes in it is the core of analyst work.

  • Structured problem solving

    Breaking a vague business question into data steps shows you can work without hand-holding.

  • Communication

    Clear charts and plain-language takeaways matter as much as correct numbers.

Examples

Copy the structure, not the wording.

These examples show shape and specificity. Add your own facts, metrics, tools and outcomes.

SQL and Excel tasks

  • Find the top 3 products by revenue in each month.
  • Calculate month-over-month growth with LAG().
  • Find customers who ordered in January but not February.
  • Use VLOOKUP or XLOOKUP to match two sheets.
  • Build a pivot table of sales by region and quarter.

Statistics questions

  • What is a p-value?
  • What is correlation vs causation?
  • What is standard deviation?
  • What is an outlier and how do you treat it?
  • What is an A/B test?

Business case prompts

  • How would you measure the success of a new feature?
  • Which metrics would you track for a food delivery app?
  • Revenue is up but profit is down. What do you check?
  • How would you estimate the number of cars in Bengaluru?
  • A manager wants a dashboard by tomorrow. How do you scope it?

Actionable tips

Small edits that lift response rates.

Run through these before every application.

  1. 1Practise SQL on a real schemaOrders, customers and products tables cover most interview queries. Time yourself.
  2. 2Use a case frameworkClarify the goal, define metrics, segment the data, form hypotheses, then recommend an action.
  3. 3Bring a portfolio projectOne analysis with a clear question, method and recommendation beats a list of tools.
  4. 4Talk in business termsEnd answers with what the business should do, not just what the data shows.
  5. 5Rehearse aloudBrainUp AI Interview Prep runs analyst mock interviews and gives feedback on your answers.

FAQ

Common questions, direct answers.

What skills are tested in a data analyst interview?

SQL, Excel, a BI tool like Power BI or Tableau, basic statistics, data cleaning, and the ability to explain insights and recommend actions to stakeholders.

What SQL questions are asked for data analysts?

Joins, aggregations with GROUP BY and HAVING, window functions like ROW_NUMBER and LAG, subqueries, CTEs, date functions and finding duplicates or top N per group.

What is the difference between WHERE and HAVING?

WHERE filters rows before grouping; HAVING filters groups after GROUP BY using aggregate conditions.

What is data cleaning?

Fixing or removing incorrect, duplicate, inconsistent or missing data so analysis is reliable. It often takes most of an analyst's time.

How do you handle outliers?

Check whether they are errors or real events. Correct or remove errors; keep real outliers but use robust measures like the median or analyse them separately.

What is the difference between correlation and causation?

Correlation means two variables move together. Causation means one causes the other. Proving causation usually needs an experiment like an A/B test.

What is an A/B test?

An experiment that randomly splits users between a control and a variant and compares a metric, using statistical significance to judge whether the difference is real.

What is a p-value?

The probability of seeing a result at least as extreme as observed if there were truly no effect. A small p-value, often below 0.05, suggests the effect is unlikely to be chance.

What Excel functions should a data analyst know?

XLOOKUP or VLOOKUP, INDEX-MATCH, SUMIFS and COUNTIFS, IF, TEXT and date functions, pivot tables, conditional formatting and basic Power Query.

What is the difference between a data analyst and a data scientist?

Data analysts focus on describing what happened and why using SQL, Excel and BI. Data scientists build predictive models and use more advanced statistics and programming.

How do you choose the right chart?

Use line charts for trends over time, bar charts for comparing categories, scatter plots for relationships and tables when exact values matter. Avoid 3D and cluttered visuals.

What is a KPI?

A key performance indicator is a metric tied to a business goal, such as conversion rate, revenue per user or churn rate, tracked to measure progress.

How do you explain an analysis to a non-technical manager?

Lead with the answer and recommended action, support it with one or two clear charts, and keep method details for follow-up questions.

Can freshers get data analyst jobs?

Yes. Freshers with strong SQL and Excel, a BI tool and two or three portfolio projects on real datasets regularly land analyst and junior analyst roles.

How should I prepare for a data analyst interview?

Practise 40-50 SQL problems, revise statistics basics, prepare two project stories with impact, and rehearse a few business case questions out loud.

Related guides

Keep improving your application.

  • Data Analyst ResumePresent SQL, dashboards and business impact.View analyst resume →
  • SQL Interview Questions for FreshersGo deeper on the SQL round.See SQL questions →
  • Power BI Interview QuestionsFor analyst roles that centre on BI.See Power BI questions →

Practise data analyst interview answers

BrainUp AI Interview Prep asks analyst questions and gives feedback on your reasoning.

Start interview practiceBrowse templates

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