🚀 Top 100 Data Analyst Interview Questions

🧠 Data Analyst Role Basics

1. What does a data analyst do in a company?
2. What is the difference between a data analyst, data scientist, and BI analyst?
3. What is the typical workflow of a data analyst (from requirement to insight)?
4. What are the main goals of data analysis (descriptive, diagnostic, predictive, prescriptive)?
5. What is KPI and why is it important?
6. What is the difference between metrics and KPIs?
7. What is a dashboard vs a report?
8. What is exploratory data analysis (EDA)?
9. What is the difference between raw data and processed data?
10. How do you prioritize which analysis to work on first?

📊 SQL Databases

11. What is SQL and why is it critical for data analysts?
12. How do SELECT, WHERE, ORDER BY, LIMIT work?
13. How do you join two tables (INNER, LEFT, RIGHT, FULL joins)?
14. How do GROUP BY and aggregate functions (SUM, AVG, COUNT, MAX, MIN) work?
15. How do you write subqueries and CTEs?
16. How do you calculate running totals or rolling averages with window functions?
17. How do you clean and filter data directly in SQL?
18. How do you handle duplicates and NULL values in SQL?
19. How do you optimize a slow query?
20. How do you design a simple schema for a business domain (e.g., orders, users)?

🧮 Excel Spreadsheets

21. How do you use Excel for quick data cleaning and analysis?
22. How do you use SUMIF, COUNTIF, VLOOKUP / XLOOKUP in Excel?
23. How do you remove duplicates and standardize text in Excel?
24. How do you use PivotTables for summarizing data?
25. How do you build simple dashboards in Excel (charts + slicers)?
26. How do you use conditional formatting for insights?
27. How do you export data to CSV or share formatted reports?
28. How do you handle large datasets in Excel vs a database?
29. How do you avoid common Excel pitfalls (e.g., hard‑coded numbers, no labels)?
30. How do you document your Excel analyses?

📈 Data Visualization BI Tools

31. What is the purpose of data visualization?
32. When do you use bar charts, line charts, pie charts, histograms?
33. What are best practices for labeling, colors, and readability?
34. How do you design a dashboard for a non‑technical stakeholder?
35. What is the difference between a report and a self‑service dashboard?
36. How do you use Power BI / Tableau / Looker / Google Data Studio for dashboards?
37. How do you filter and slice data in a BI tool?
38. How do you handle measures and dimensions in BI tools?
39. How do you share dashboards and control access?
40. How do you tell a “data story” using charts and annotations?

📊 Descriptive Statistics EDA

41. What are mean, median, and mode?
42. What is standard deviation and variance?
43. What are quartiles and IQR?
44. How do you detect outliers and what should you do with them?
45. What is a distribution and how do you inspect it (histograms, boxplots)?
46. What is skewness and kurtosis?
47. How do you calculate growth rate, percentage change, CAGR?
48. How do you compute cohort‑style metrics (e.g., retention by signup month)?
49. How do you summarize categorical vs numerical data?
50. How do you structure an EDA notebook or report?

🛠️ Python (or R) for Data Analysis

51. Why do data analysts use Python instead of (or along with) Excel?
52. How do you load data from CSV or SQL into a pandas DataFrame?
53. How do you inspect the first/last rows, shape, data types, and missing values?
54. How do you clean missing values (dropna, fillna, interpolation)?
55. How do you filter, sort, and group data with pandas?
56. How do you calculate aggregates and pivots with groupby and pivot_table?