Data Analytics Interview Preparation Guide
π― Complete Preparation for Passing Your Interview
Test your skills by solving problems similar to those asked in real company interviews. Each problem includes detailed explanations and key points that interviewers look for in answers.
π Interview Guide by Category
ποΈ SQL Interview
Core SQL syntax including JOINs, window functions, subqueries, and query optimization problems
πΌ Pandas Interview
Pandas coding tests frequently asked in practice: data manipulation, aggregation, merging, and more
π Statistics/Analytics Interview
Statistical concepts and interpretation skills: hypothesis testing, A/B testing, regression analysis
πΌ Case Study
Comprehensive analysis problems based on real business scenarios and presentation tips
π Difficulty Guide
| Level | Target | Expected Companies |
|---|---|---|
| Beginner | Entry-level/Intern | Startups, Small-Medium Businesses |
| Intermediate | 1-3 Years Experience | Mid-sized Companies, Large Enterprises |
| Advanced | 3+ Years Experience | Big Tech, Finance |
π Interview Checklist
SQL Essential Concepts
- Types of JOINs and differences (INNER, LEFT, RIGHT, FULL, CROSS)
- GROUP BY + HAVING vs WHERE differences
- Window functions (ROW_NUMBER, RANK, LAG, LEAD, SUM OVER)
- Subqueries vs CTEs - pros and cons
- NULL handling (COALESCE, NULLIF, IS NULL)
- Index mechanics and optimization
Pandas Essential Concepts
- DataFrame basic operations (loc, iloc, query)
- Various uses of groupby + agg
- Differences between merge vs join vs concat
- Differences between apply, map, transform
- Missing value handling strategies
- Memory optimization techniques
Statistics Essential Concepts
- Meaning and interpretation of p-value
- Type I/Type II errors
- Confidence interval vs significance level
- A/B test design and analysis
- Correlation vs causation
- Regression analysis interpretation
π‘ Interview Tips
π What Interviewers Look For
- Problem Understanding: Do you accurately identify requirements and ask clarifying questions?
- Approach: How do you break down and solve problems?
- Code Quality: Readability, efficiency, edge case handling
- Communication: Do you clearly explain your thought process?
- Business Sense: Do you connect analysis results to actionable insights?
π Recommended Study Order
Week 1: SQL Beginner (10 questions) + Pandas Beginner (8 questions)
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Week 2: SQL Intermediate (10 questions) + Pandas Intermediate (9 questions)
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Week 3: Statistics Interview (20 questions)
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Week 4: SQL/Pandas Advanced + Case Study
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Before Interview: Review missed questions + Mock interviewπ Premium Interview Question Set
Complete 85 Question Bundle
| Category | Free Sample | Premium | Total |
|---|---|---|---|
| SQL Interview | 3 questions | 27 questions | 30 questions |
| Pandas Interview | 3 questions | 22 questions | 25 questions |
| Statistics Interview | 3 questions | 17 questions | 20 questions |
| Case Study | 1 question | 9 questions | 10 questions |
| Total | 10 questions | 75 questions | 85 questions |
What Youβll Learn in Premium
- β Advanced SQL: Window functions, cohort analysis, funnels, sessionization
- β Advanced Pandas: RFM analysis, memory optimization, cohort retention
- β Practical Statistics: A/B test design, multiple comparison, effect size
- β Case Study: Churn prediction, price optimization, LTV analysis
- β Interviewer Scoring Points: Evaluation criteria for each question
π― Purchase All 85 Questions + Explanations
30% off when purchasing bundle
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