Data Analyst Interview Questions - Get Hired in Analytics

Master data analyst interview questions with AI-generated practice. Prepare for SQL, Excel, statistics, data visualization, and business case study rounds at top companies.

Start PracticingView Pricing

What are Data Analyst Interview Questions?

Data analyst interview questions assess your ability to collect, process, and analyze data to drive business decisions. These interviews test SQL proficiency, Excel skills, statistical knowledge, data visualization, and business acumen. Whether you're preparing for junior analyst or senior data analyst roles, structured practice is key to success.

Typical data analyst interview rounds:

  • •SQL Assessment – Write queries, joins, aggregations, window functions (30-60 minutes)
  • •Excel/Spreadsheet Test – Pivot tables, VLOOKUP, data modeling, analysis
  • •Case Study – Business problem solving, metrics analysis, presenting insights
  • •Behavioral Round – Communication skills, stakeholder management, past projects

Master All Types of Data Analyst Questions

🗃️

SQL & Databases

SQL is the most tested skill in data analyst interviews. Master it thoroughly.

  • •JOINs (INNER, LEFT, RIGHT, FULL)
  • •GROUP BY & aggregations
  • •Window functions (ROW_NUMBER, RANK)
  • •Subqueries & CTEs
📊

Excel & Spreadsheets

Excel proficiency is essential for most data analyst positions.

  • •Pivot tables & pivot charts
  • •VLOOKUP, INDEX-MATCH, XLOOKUP
  • •Conditional formatting
  • •Data validation & cleaning
📈

Statistics & Analysis

Understand statistical concepts to analyze data meaningfully.

  • •Descriptive statistics (mean, median, mode)
  • •Correlation vs causation
  • •Hypothesis testing basics
  • •Trend analysis & forecasting
📉

Data Visualization

Present data insights clearly with effective visualizations.

  • •Tableau / Power BI basics
  • •Choosing the right chart type
  • •Dashboard design principles
  • •Storytelling with data

50+ Common Data Analyst Interview Questions

🗃️ SQL Questions

  • • Find customers who made purchases in consecutive months
  • • Calculate month-over-month growth rate
  • • Identify top 3 products by revenue per category
  • • Write a query to detect duplicate records

📊 Excel Questions

  • • Create a pivot table to show sales by region and quarter
  • • Use VLOOKUP to merge two datasets
  • • Build a dynamic dashboard with slicers
  • • Calculate running totals and averages

📈 Statistics Questions

  • • What's the difference between mean and median?
  • • Explain standard deviation in simple terms
  • • How would you identify outliers in a dataset?
  • • What is the difference between correlation and causation?

💼 Business Case Questions

  • • Sales dropped 15% last month. How would you investigate?
  • • What metrics would you track for an e-commerce site?
  • • How would you measure customer satisfaction?
  • • Present insights from this dataset (take-home)

Essential Tools for Data Analysts

🗄️

SQL

MySQL, PostgreSQL, SQL Server, BigQuery. Must-have skill for any data analyst role.

📗

Excel / Google Sheets

Pivot tables, formulas, charts. Still the most used tool in business analytics.

📊

Tableau / Power BI

Data visualization tools for creating dashboards and reports.

🐍

Python (Optional)

Pandas, NumPy for data manipulation. Increasingly valuable for senior roles.

📈

Google Analytics

Web analytics for marketing and product analyst roles.

📋

Looker / Metabase

Modern BI tools used by startups and tech companies.

Data Analyst vs Data Scientist: Interview Differences

AspectData AnalystData Scientist
SQL DepthAdvanced queries, optimizationIntermediate queries
StatisticsDescriptive, basic inferentialAdvanced, probability theory
ProgrammingSQL, Excel, basic PythonPython/R, ML libraries
Machine LearningNot requiredCore requirement
FocusReporting, dashboards, insightsPrediction, modeling, algorithms

Your Data Analyst Interview Prep Roadmap

📚

Week 1-2: SQL Mastery

Practice SQL daily on platforms like LeetCode, HackerRank, or StrataScratch. Master JOINs, GROUP BY, window functions, and subqueries.

📊

Week 3-4: Excel & Visualization

Practice pivot tables, advanced formulas, and dashboard creation. Learn Tableau or Power BI basics for visualization questions.

📈

Week 5-6: Statistics & Business Cases

Review descriptive statistics and basic hypothesis testing. Practice business case studies: metric investigation, KPI definition, presenting insights.

🎯

Week 7-8: Mock Interviews & Portfolio

Do timed SQL assessments. Practice explaining your analysis process clearly. Prepare 2-3 portfolio projects showcasing your analytical skills.

Ready to Land Your Data Analyst Role?

Practice unlimited data analyst interview questions with AI. Master SQL, Excel, statistics, and business case studies.

Start Practicing Now →