Data Analyst Interview Questions and Answers (SQL, Excel)

Data analyst interviews usually test three things: whether you can get data out (SQL), whether you can work with it (Excel, Python or a BI tool), and whether you can turn it into a decision someone can act on. The third is where many candidates fall short. They know the syntax but can't explain what the numbers mean for the business.

Quick answer: Data analyst interviews usually cover SQL (joins, GROUP BY, window functions), Excel (VLOOKUP or XLOOKUP, pivot tables), basic statistics (mean vs median, correlation, A/B tests), a BI tool like Power BI or Tableau, and a business case question. Practise writing SQL by hand and explaining your insights in plain language.

SQL questions

SQL is almost always tested, often with a live query.

What's the difference between INNER JOIN and LEFT JOIN?

An INNER JOIN returns only rows with a match in both tables. A LEFT JOIN returns all rows from the left table, and NULLs for columns from the right table where there's no match.

What's the difference between WHERE and HAVING?

WHERE filters rows before grouping. HAVING filters groups after aggregation, so you use it with conditions on COUNT, SUM and similar.

Find the second highest salary

One common approach uses a window function:

SELECT salary FROM (SELECT salary, DENSE_RANK() OVER (ORDER BY salary DESC) AS rnk FROM employees) t WHERE rnk = 2;

Be ready to explain the difference between RANK, DENSE_RANK and ROW_NUMBER when there are ties.

Other SQL topics to practise

• GROUP BY with multiple aggregates
• Finding duplicates
• Running totals with window functions
• Month-over-month growth using LAG
• CTEs for readable multi-step queries
• Handling NULLs with COALESCE

Excel questions

• VLOOKUP vs XLOOKUP: XLOOKUP can look left, returns exact match by default, and handles missing values more cleanly.
• Pivot tables: be ready to summarise sales by region and month in under two minutes.
• Conditional formatting to highlight outliers.
• IF, SUMIFS, COUNTIFS for conditional calculations.
• Removing duplicates and cleaning text with TRIM, PROPER and text-to-columns.

Statistics questions

When would you use median instead of mean?

When the data is skewed or has outliers. Salaries and house prices are classic examples, since a few very high values pull the mean up.

What is correlation, and does it imply causation?

Correlation measures how two variables move together. It doesn't imply causation. Ice cream sales and drowning incidents both rise in summer, but one doesn't cause the other.

How would you explain an A/B test?

Split users randomly into two groups. Show one group the current version and the other a change. Compare a chosen metric, and check whether the difference is statistically significant before deciding.

Dashboard and BI questions

• Walk me through a dashboard you built. Who used it, and what decision did it support?
• How do you choose the right chart?
• How do you handle a stakeholder who wants 30 metrics on one page?

Business case questions

These test your thinking more than your tools.

"Sales dropped 15 percent last month. How would you investigate?"

A structured answer:

1. Confirm the data is correct. Check for tracking or pipeline issues.
2. Is it seasonal? Compare with the same month last year.
3. Break it down: by region, product, channel, customer segment. Where is the drop concentrated?
4. Check internal changes: pricing, website releases, stock issues, marketing spend.
5. Check external factors: competitor launches, holidays, economic changes.
6. Summarise the likely cause and suggest what to test next.

Structure matters more than getting the "right" cause.

Project walkthrough

You'll almost always be asked to explain a project. Use the STAR method and make sure the result is a business outcome, not just "I built a dashboard".

I built a churn dashboard in Power BI for the customer success team. It showed which accounts had declining usage. The team used it to call at-risk accounts early, and churn in the next quarter dropped compared with the previous one.

How to prepare

• Write SQL daily for two weeks, including window functions.
• Build or refresh one portfolio project with a clear business question.
• Practise explaining one chart in plain English in 60 seconds.
• Prepare two case study frameworks: investigating a drop and sizing a market.

If you tend to freeze on live SQL or case questions, SilentlyAI can show a suggested approach on your screen during the call when you ask.

Frequently asked questions

What SQL questions are asked in data analyst interviews?

Joins, GROUP BY with HAVING, subqueries, window functions like RANK and LAG, finding duplicates, and calculating growth or running totals.

Do data analysts need to know Python?

Many roles ask for it, especially pandas for data cleaning. Some roles only need SQL, Excel and a BI tool. Check the job description.

How do I become a data analyst as a fresher?

Learn SQL, Excel and one BI tool, build two or three portfolio projects that answer real business questions, and practise explaining insights clearly.

What is the most important skill for a data analyst?

Turning data into a clear recommendation. Tools can be learned quickly. Business thinking and communication set strong candidates apart.