SQL Interview Questions !!

🎗 Write a query to find all employees whose salaries exceed the company's average salary.
🎗 Write a query to retrieve the names of employees who work in the same department as 'John Doe'.
🎗 Write a query to display the second highest salary from the Employee table without using the MAX function twice.
🎗 Write a query to find all customers who have placed more than five orders.
🎗 Write a query to count the total number of orders placed by each customer.
🎗 Write a query to list employees who joined the company within the last 6 months.
🎗 Write a query to calculate the total sales amount for each product.
🎗 Write a query to list all products that have never been sold.
🎗 Write a query to remove duplicate rows from a table.
🎗 Write a query to identify the top 10 customers who have not placed any orders in the past year.

Here you can find essential SQL Interview Resources👇
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Data Analyst Interview Questions & Preparation Tips

Be prepared with a mix of technical, analytical, and business-oriented interview questions.

1. Technical Questions (Data Analysis & Reporting)

SQL Questions:

How do you write a query to fetch the top 5 highest revenue-generating customers?

Explain the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN.

How would you optimize a slow-running query?

What are CTEs and when would you use them?

Data Visualization (Power BI / Tableau / Excel)

How would you create a dashboard to track key performance metrics?

Explain the difference between measures and calculated columns in Power BI.

How do you handle missing data in Tableau?

What are DAX functions, and can you give an example?

ETL & Data Processing (Alteryx, Power BI, Excel)

What is ETL, and how does it relate to BI?

Have you used Alteryx for data transformation? Explain a complex workflow you built.

How do you automate reporting using Power Query in Excel?


2. Business and Analytical Questions

How do you define KPIs for a business process?

Give an example of how you used data to drive a business decision.

How would you identify cost-saving opportunities in a reporting process?

Explain a time when your report uncovered a hidden business insight.


3. Scenario-Based & Behavioral Questions

Stakeholder Management:

How do you handle a situation where different business units have conflicting reporting requirements?

How do you explain complex data insights to non-technical stakeholders?

Problem-Solving & Debugging:

What would you do if your report is showing incorrect numbers?

How do you ensure the accuracy of a new KPI you introduced?

Project Management & Process Improvement:

Have you led a project to automate or improve a reporting process?

What steps do you take to ensure the timely delivery of reports?


4. Industry-Specific Questions (Credit Reporting & Financial Services)

What are some key credit risk metrics used in financial services?

How would you analyze trends in customer credit behavior?

How do you ensure compliance and data security in reporting?


5. General HR Questions

Why do you want to work at this company?

Tell me about a challenging project and how you handled it.

What are your strengths and weaknesses?

Where do you see yourself in five years?

How to Prepare?

Brush up on SQL, Power BI, and ETL tools (especially Alteryx).

Learn about key financial and credit reporting metrics.(varies company to company)

Practice explaining data-driven insights in a business-friendly manner.

Be ready to showcase problem-solving skills with real-world examples.

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🧠 Data Analyst Interview Common Interview Traps – Day 4

❓ “Is NULL equal to zero or an empty string?”

❌ Trap Answer:

“Yes, NULL means no value, so it’s like zero or empty.”

✅ Smart Answer:

“No. NULL means unknown or missing.
It behaves differently in comparisons, aggregations, and joins.”

🎯 Interviewer is testing:
Your understanding of three-valued logic.

💡 Tip:
Always handle NULLs explicitly.

React 👍 if you want interview prep #5 tomorrow

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Deadline: 11th January 2026

Eligibility: Open to everyone
Duration: 6 Months
Program Mode: Online
Taught By: IIT Roorkee Professors

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📊 Day 6 – Data Analyst Most Asked Interview Question ❓

UNION vs UNION ALL (SQL)

━━━━━━━━━━━━━━

UNION

• Combines result sets
• Removes duplicate rows
• Slightly slower due to deduplication
• Columns count & data types must match

UNION ALL

• Combines result sets
• Keeps duplicates
• Faster than UNION
• Columns count & data types must match

━━━━━━━━━━━━━━

Rule:

👉 Duplicates should be removed → UNION
👉 Performance matters & duplicates allowed → UNION ALL ✅

━━━━━━━━━━━━━━

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Date :- 11th January 2026

✅ SQL Interview Challenge 💼🧠

𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝗲𝗿: How would you count how many employees are in each department?

𝗠𝗲: I’d use the GROUP BY clause with COUNT(*) to aggregate employee counts per department.

🔹 Query:

SELECT department, COUNT(*) AS employee_count  
FROM employees  
GROUP BY department;

✔ Why it works:
– GROUP BY groups rows by department
– COUNT(*) counts employees in each group
– Clean, scalable, and works with large datasets

🔎 Bonus Insight:
To filter only departments with more than 5 employees:

SELECT department, COUNT(*) AS employee_count  
FROM employees  
GROUP BY department  
HAVING COUNT(*) > 5;

– HAVING filters aggregated results
– Useful in dashboards, reports, and business logic

💬 Tap ❤️ for more SQL interview tips!

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✅ Data Analyst Interview Questions for Freshers 📊

1) What is the role of a data analyst?
Answer: A data analyst collects, processes, and performs statistical analyses on data to provide actionable insights that support business decision-making.

2) What are the key skills required for a data analyst?
Answer: Strong skills in SQL, Excel, data visualization tools (like Tableau or Power BI), statistical analysis, and problem-solving abilities are essential.

3) What is data cleaning?
Answer: Data cleaning involves identifying and correcting inaccuracies, inconsistencies, or missing values in datasets to improve data quality.

4) What is the difference between structured and unstructured data?
Answer: Structured data is organized in rows and columns (e.g., spreadsheets), while unstructured data includes formats like text, images, and videos that lack a predefined structure.

5) What is a KPI?
Answer: KPI stands for Key Performance Indicator, which is a measurable value that demonstrates how effectively a company is achieving its business goals.

6) What tools do you use for data analysis?
Answer: Common tools include Excel, SQL, Python (with libraries like Pandas), R, Tableau, and Power BI.

7) Why is data visualization important?
Answer: Data visualization helps translate complex data into understandable charts and graphs, making it easier for stakeholders to grasp insights and trends.

8) What is a pivot table?
Answer: A pivot table is a feature in Excel that allows you to summarize, analyze, and explore data by reorganizing and grouping it dynamically.

9) What is correlation?
Answer: Correlation measures the statistical relationship between two variables, indicating whether they move together and how strongly.

10) What is a data warehouse?
Answer: A data warehouse is a centralized repository that consolidates data from multiple sources, optimized for querying and analysis.

11) Explain the difference between INNER JOIN and OUTER JOIN in SQL.
Answer: INNER JOIN returns only the matching rows between two tables, while OUTER JOIN returns all matching rows plus unmatched rows from one or both tables, depending on whether it’s LEFT, RIGHT, or FULL OUTER JOIN.

12) What is hypothesis testing?
Answer: Hypothesis testing is a statistical method used to determine if there is enough evidence in a sample to infer that a certain condition holds true for the entire population.

13) What is the difference between mean, median, and mode?
Answer:
⦁ Mean: The average of all numbers.
⦁ Median: The middle value when data is sorted.
⦁ Mode: The most frequently occurring value in a dataset.

14) What is data normalization?
Answer: Normalization is the process of organizing data to reduce redundancy and improve integrity, often by dividing data into related tables.

15) How do you handle missing data?
Answer: Missing data can be handled by removing rows, imputing values (mean, median, mode), or using algorithms that support missing data.

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📊 Day 7 – Data Analyst Most Asked Interview Question ❓

DELETE vs TRUNCATE vs DROP (SQL)

━━━━━━━━━━━━━━

DELETE

• Removes specific rows using WHERE
• Can be rolled back (transactional)
• Table structure remains
• Slower for large data

TRUNCATE

• Removes all rows at once
• Cannot be rolled back
• Table structure remains
• Faster than DELETE

DROP

• Removes entire table
• Deletes data + structure
• Cannot be rolled back
• Frees storage completely

━━━━━━━━━━━━━━

Rule:

👉 Remove specific data → DELETE
👉 Clear entire table fast → TRUNCATE
👉 Remove table completely → DROP ✅

━━━━━━━━━━━━━━

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