Q1
Walk me through how you would write a SQL query to identify duplicate records in a customer table and explain the JOIN or window function approach you'd use.
Why they ask this:* Data Analysts must be proficient in SQL for data cleaning and exploration. This tests your ability to write efficient queries and understand different approaches to solve common data problems.
Q2
Explain the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN with a real-world example of when you would use each in analysis.
Why they ask this:* Joining datasets is fundamental to data analysis. This assesses your understanding of how different join types affect query results and your ability to select the appropriate method for different analytical scenarios.
Q3
You have a dataset with missing values. How would you decide whether to remove rows with missing data, impute them, or use another approach, and what tools would you use in Excel, Python, or SQL?
Why they ask this:* Data quality directly impacts analysis accuracy. This tests your critical thinking about data handling decisions and your familiarity with practical tools for data preprocessing.
Q4
Describe how you would create a dashboard to track monthly sales trends. What metrics would you include, and which visualization tool (Tableau, Power BI, or Google Sheets) would you choose and why?