📊 Data Analytics Interview Questions With Answers Part-1 👇

1️⃣ What is Data Analytics and how does it differ from Data Science? 
Data Analytics focuses on examining past data using statistical tools & reporting to answer specific business questions. Data Science is broader, using algorithms & machine learning to predict future trends and deeper insights.

2️⃣ How do you handle missing or duplicate data?
⦁ Missing data: remove, impute with mean/median/mode, or predict missing values.
⦁ Duplicate data: identify with functions (e.g., duplicated()) and remove or merge based on context.

3️⃣ Explain descriptive vs diagnostic analytics.
⦁ Descriptive Analytics: What happened? Summarizes data trends.
⦁ Diagnostic Analytics: Why did it happen? Explores cause-effect relationships.

4️⃣ What is data cleaning and why is it important? 
Data cleaning removes errors, inconsistencies, and duplicates to ensure accuracy for analysis and decision-making.

5️⃣ What are common data visualization techniques? 
Bar charts, histograms, scatter plots, pie charts, heatmaps, and dashboards.

6️⃣ Explain correlation vs causation. 
Correlation indicates a statistical relationship between variables; causation means one variable causes change in another.

7️⃣ How do you choose the right KPI for a project? 
Based on business goals, relevance, measurability, and actionability.

8️⃣ What tools do you use for data analytics? 
Excel, SQL, Tableau, Power BI, Python (Pandas, Matplotlib), R.

9️⃣ What is ETL and its importance? 
Extract, Transform, Load – process to gather data from sources, clean & transform it, then load into data storage ready for querying.

🔟 Difference between structured and unstructured data? 
Structured data fits rows & columns (databases). Unstructured data includes text, images, videos, lacking a predefined format.

💬 React ♥️ for Part-2!