Data analyst interview questions for freshers
For entry-level analyst roles, interviewers check that your SQL and Excel basics are solid, that you think clearly about numbers, and that you can explain a project where you worked with real data.
Here are the questions freshers are most often asked, with what a good answer includes.
What interviewers assess
- Basic SQL: SELECT, filtering, joins and GROUP BY
- Excel or Sheets: formulas, lookups and pivot tables
- Simple statistics: averages, percentages and spotting odd data
- Explaining a data project clearly to a non-technical person
SQL and Excel basics questions
Write a query to find the total sales for each product.
What a good answer covers: SELECT product, SUM(amount) FROM sales GROUP BY product. Then mention ordering by total and filtering with HAVING.
What is a primary key and a foreign key?
What a good answer covers: A primary key uniquely identifies a row; a foreign key links to a primary key in another table. Give an orders and customers example.
Explain INNER JOIN and LEFT JOIN with an example.
What a good answer covers: INNER keeps only matching rows; LEFT keeps every row from the left table with NULLs where there is no match, for example customers with no orders.
What is the difference between VLOOKUP and XLOOKUP (or INDEX/MATCH)?
What a good answer covers: VLOOKUP only looks to the right and breaks when columns move; XLOOKUP and INDEX/MATCH are more flexible. Mention exact-match mode.
What is a pivot table and when would you use one?
What a good answer covers: A quick way to summarise data by categories, such as sales by region and month. Mention filtering and grouping dates.
Numbers and reasoning questions
What is the difference between mean, median and mode?
What a good answer covers: Definitions plus when each is useful; the median is better with outliers, such as salaries.
Sales went up 50% one month and down 50% the next. Are we back where we started?
What a good answer covers: No: 100 becomes 150, then 75. Tests whether you reason carefully about percentages.
You find a few values that look wrong in a dataset. What do you do?
What a good answer covers: Check the source, look for a pattern, decide whether to fix, remove or flag them, and note what you changed so others can trust the result.
About your projects questions
Walk me through a data project you did. What question were you answering?
What a good answer covers: The question, where the data came from, how you cleaned it, the tool you used, the main finding and what someone could do with it.
Which chart would you use to show sales over time, and which to compare categories?
What a good answer covers: A line chart for trends over time; a bar chart for comparing categories. Avoid pie charts with many slices.
Show us a dashboard or notebook you built. Who was it for?
What a good answer covers: Have one ready to describe or share. Explain the audience and the one or two numbers that matter most.
HR and motivation questions
Tell me about yourself.
What a good answer covers: Degree, the data project or internship most relevant to the role, what draws you to analysis, and why this company.
Why do you want to be a data analyst?
What a good answer covers: A real reason, such as enjoying finding answers in data, backed by something you have done.
How do you explain a technical result to someone non-technical?
What a good answer covers: Start with the conclusion, use one simple chart, avoid jargon, and say what action it suggests.
Common mistakes
- Listing Python, R, Tableau and Power BI but being comfortable with none of them.
- Describing a project by the tools used rather than the question it answered.
- Rushing a SQL question without checking for duplicates or NULLs.
- Not having a single dataset or dashboard you can talk about.
How to prepare
- Practise basic SQL daily on a free practice site until joins and GROUP BY feel natural.
- Build one small end-to-end project on a public dataset and be ready to explain it.
- Revise pivot tables and lookups in Excel or Google Sheets.
- Practise explaining your project in two minutes to a friend who isn't technical.
Reading questions only goes so far: the real test is answering them aloud, under follow-up questions. Career Scan builds a mock interview from your own resume and the job, then shows exactly which answers need work.
Frequently asked questions
Can I become a data analyst without a computer science degree?
Yes. Many analysts come from commerce, economics, statistics or engineering. A project portfolio and solid SQL matter more than the degree name.
Is Python required for fresher data analyst roles?
Not always. SQL and Excel are the most common requirements. Basic Python with pandas is a strong plus.
What kind of test do freshers get?
Often an online SQL or aptitude test, followed by a technical interview and an HR round. Some companies give a small take-home dataset.