✅ 📊 Top 10 Data Analyst Interview Questions

1️⃣ What is Data Wrangling?
Answer: It's the process of cleaning, structuring, and enriching raw data into a desired format for analysis. It includes handling nulls, removing duplicates, and standardizing formats.

2️⃣ How is Excel used in Data Analysis?
Answer: Excel is used for quick data cleaning, pivot tables, basic stats, visualizations, and what-if analysis.

3️⃣ What are the different types of data?
Answer:
- Structured: Organized in rows/columns (e.g. databases)
- Unstructured: No format (e.g. text, images)
- Semi-structured: Tags or markers (e.g. JSON, XML)

4️⃣ Define Normalization. Why is it important?
Answer: It's the process of organizing data to reduce redundancy. It ensures consistency and optimizes storage.

5️⃣ What is the difference between WHERE and HAVING in SQL?
Answer:
- WHERE: Filters rows before aggregation
- HAVING: Filters groups after aggregation

6️⃣ What is the use of GROUP BY in SQL?
Answer: It groups rows with the same values in specified columns, often used with aggregate functions like COUNT(), SUM(), AVG().

7️⃣ What is an Outlier? How do you detect it?
Answer: An outlier is a data point that differs significantly from others. Detection methods: IQR, Z-score, boxplots.

8️⃣ How do you prioritize tasks when handling multiple projects?
Answer: By assessing deadlines, impact, complexity, and using tools like Trello, Notion, or Excel trackers.

9️⃣ What are Data Dashboards?
Answer: Visual interfaces that display key metrics and KPIs in real-time, used for quick business decision-making.

🔟 What’s the difference between OLAP and OLTP?
Answer:
- OLAP (Analytical): Used for complex queries & reporting
- OLTP (Transactional): Used for real-time data processing (e.g. banking systems)

💡 Pro Tip: Be ready to explain your thought process with real-life projects or case studies during interviews!

👍 React ❤️ if this helped!