Data Analyst Interview Questions and Answers (2026 Edition)

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Data Analyst Interview Questions and Answers (2026 Edition)

Cracking a data analyst interview requires preparation across multiple areas — SQL, Python, statistics, business acumen, and communication skills. This guide covers the 25 most commonly asked questions with detailed answers.

SQL Questions

1. What is the difference between WHERE and HAVING?

Answer: WHERE filters rows before grouping (works on individual rows). HAVING filters groups after GROUP BY (works on aggregated results).

-- WHERE: filter individual rows
SELECT * FROM orders WHERE amount > 1000;

-- HAVING: filter groups
SELECT department, AVG(salary)
FROM employees
GROUP BY department
HAVING AVG(salary) > 800000;

2. Explain different types of JOINs

Answer:

  • INNER JOIN: Returns only matching rows from both tables
  • LEFT JOIN: Returns all rows from the left table + matching rows from the right
  • RIGHT JOIN: Returns all rows from the right table + matching rows from the left
  • FULL OUTER JOIN: Returns all rows from both tables, with NULLs where there's no match
  • CROSS JOIN: Returns the Cartesian product (every row paired with every row)

3. What are window functions? Give an example.

Answer: Window functions perform calculations across a set of rows related to the current row, without collapsing the result set like GROUP BY does.

SELECT 
  employee_name,
  department,
  salary,
  RANK() OVER (PARTITION BY department ORDER BY salary DESC) as dept_rank,
  AVG(salary) OVER (PARTITION BY department) as dept_avg
FROM employees;

4. How do you find duplicate records?

SELECT email, COUNT(*) as count
FROM customers
GROUP BY email
HAVING COUNT(*) > 1;

5. Write a query to find the second-highest salary.

SELECT MAX(salary) as second_highest
FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);

-- Or using window functions:
SELECT salary FROM (
  SELECT salary, DENSE_RANK() OVER (ORDER BY salary DESC) as rk
  FROM employees
) ranked
WHERE rk = 2;

Python Questions

6. How do you handle missing values in Pandas?

Answer:

import pandas as pd

# Check for missing values
df.isnull().sum()

# Drop rows with any missing values
df.dropna()

# Fill missing values
df['column'].fillna(df['column'].mean(), inplace=True)
df['column'].fillna(method='ffill')  # Forward fill
df['column'].fillna(0)  # Fill with specific value

7. What is the difference between loc and iloc?

Answer:

  • loc: Label-based indexing (uses column names and row labels)
  • iloc: Integer-based indexing (uses position numbers)
df.loc[0:5, 'name']      # rows 0-5, column 'name'
df.iloc[0:5, 0]           # rows 0-5, first column

8. How do you merge DataFrames?

# Like SQL JOINs
merged = pd.merge(orders_df, customers_df, on='customer_id', how='left')

# Concatenation (stacking)
combined = pd.concat([df1, df2], axis=0)

Statistics Questions

9. Explain the difference between mean, median, and mode.

Answer:

  • Mean: Average of all values. Sensitive to outliers.
  • Median: Middle value when sorted. Robust to outliers.
  • Mode: Most frequently occurring value.

Use median when data has outliers (salary data), mean when data is normally distributed.

10. What is a p-value?

Answer: The probability of observing results at least as extreme as the actual results, assuming the null hypothesis is true. If p-value < 0.05 (typically), we reject the null hypothesis and conclude the result is statistically significant.

11. Explain A/B testing.

Answer: A/B testing compares two versions of something (webpage, email, feature) to determine which performs better:

  1. Hypothesis: "Changing the CTA button color from blue to green will increase click-through rate"
  2. Split traffic: 50% sees version A (blue), 50% sees version B (green)
  3. Collect data: Track clicks for a sufficient sample size
  4. Statistical test: Use a chi-square test or t-test to check if the difference is significant
  5. Decision: If p-value < 0.05, implement the winning version

12. What is correlation vs. causation?

Answer: Correlation means two variables move together (positive or negative). Causation means one variable directly causes the other to change. Correlation does not imply causation. Example: Ice cream sales and drowning incidents are correlated (both increase in summer), but ice cream doesn't cause drowning.

Power BI / Visualization Questions

13. What is DAX in Power BI?

Answer: DAX (Data Analysis Expressions) is Power BI's formula language for creating calculated columns, measures, and tables. Key functions:

Total Sales = SUM(Sales[Amount])
YoY Growth = DIVIDE([This Year Sales] - [Last Year Sales], [Last Year Sales])
Running Total = CALCULATE(SUM(Sales[Amount]), FILTER(ALL(Calendar), Calendar[Date] <= MAX(Calendar[Date])))

14. When would you use a bar chart vs. a line chart?

Answer:

  • Bar chart: Comparing categories (sales by region, products by revenue)
  • Line chart: Showing trends over time (monthly revenue, daily active users)
  • Pie chart: Showing parts of a whole (market share) — use sparingly
  • Scatter plot: Showing relationships between two variables

Behavioral Questions

15. Tell me about a time you found an insight that surprised stakeholders.

Tip: Use the STAR method (Situation, Task, Action, Result). Focus on the business impact of your finding, not just the technical process.

16. How do you handle conflicting data from different sources?

Answer: First, identify the source of truth. Cross-reference with raw data or the system of record. Document discrepancies and their causes (timing differences, calculation methods, data transformation errors). Present findings with caveats to stakeholders.

Tips for Interview Day

  1. Practice SQL on paper — many interviews require whiteboard SQL
  2. Explain your thought process — interviewers want to see how you think
  3. Ask clarifying questions — "What metric defines success?" shows analytical thinking
  4. Bring your portfolio — walk through real projects you've built
  5. Know the company — research what data they have and what insights they might need

Prepare with Expert Guidance

Our Data Analyst Course includes 5+ mock interviews that simulate real company interview rounds. You'll practice SQL live, walk through case studies, and get structured feedback. Plus, our placement team provides direct referrals to hiring partners.

Good luck with your interview preparation! Bookmark this page and review before your next interview.