Data Analyst Interview Questions & Preparation
SQL, statistics, analytics case, and behavioral rounds.
Data analyst interviews test SQL fluency, statistical reasoning, and turning data into business decisions. Expect SQL problems, stats/probability questions, an analytics case, and behavioral questions. This guide walks through each with examples.
What to Expect
SQL round
Write queries with joins, aggregations, window functions, and subqueries against a described schema. Correctness and readability both matter.
Statistics & metrics
A/B test interpretation, probability, and defining or diagnosing metrics. Show clear reasoning, not just formulas.
Analytics case + behavioral
'How would you measure the success of feature X?' plus stories about stakeholder communication and impact.
Common Questions & How to Answer
Find the second-highest salary per department.
How to answer: Use a window function (DENSE_RANK) partitioned by department, or a correlated subquery; explain the tie edge cases.
Difference between DELETE, TRUNCATE, and DROP.
How to answer: DELETE = row-level and logged; TRUNCATE = fast and resets the table; DROP = removes the table structure entirely.
How do you tell if an A/B test result is significant?
How to answer: Talk sample size, p-value/confidence, effect size, and pitfalls like peeking and multiple comparisons.
Daily orders dropped 10% — how do you investigate?
How to answer: Check data quality first, then segment by platform/region/cohort, form hypotheses, and validate with queries.
Tell me about an analysis that changed a decision.
How to answer: STAR: the question, your approach, the insight, and the business action it drove.
Preparation Tips
Master window functions (RANK, LAG/LEAD, running totals) — they show up constantly.
Always check data quality first when diagnosing a metric change.
Explain statistical concepts in plain business language, not just formulas.
Frame every analysis around the decision it enables.
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