SQL Interview Questions

1. How would you find duplicate records in SQL?
2.What are various types of SQL joins?
3.What is a trigger in SQL?
4.What are different DDL,DML commands in SQL?
5.What is difference between Delete, Drop and Truncate?
6.What is difference between Union and Union all?
7.Which command give Unique values?
8. What is the difference between Where and Having Clause?
9.Give the execution of keywords in SQL?
10. What is difference between IN and BETWEEN Operator?
11. What is primary and Foreign key?
12. What is an aggregate Functions?
13. What is the difference between Rank and Dense Rank?
14. List the ACID Properties and explain what they are?
15. What is the difference between % and _ in like operator?
16. What does CTE stands for?
17. What is database?what is DBMS?What is RDMS?
18.What is Alias in SQL?
19. What is Normalisation?Describe various form?
20. How do you sort the results of a query?
21. Explain the types of Window functions?
22. What is limit and offset?
23. What is candidate key?
24. Describe various types of Alter command?
25. What is Cartesian product?

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Guys, Big Announcement!

I’m launching a Complete SQL Learning Series — designed for everyone — whether you're a beginner, intermediate, or someone preparing for data interviews.

This is a complete step-by-step journey — from scratch to advanced — filled with practical examples, relatable scenarios, and short quizzes after each topic to solidify your learning.

Here’s the 5-Week Plan:

Week 1: SQL Fundamentals (No Prior Knowledge Needed)

- What is SQL? Real-world Use Cases

- Databases vs Tables

- SELECT Queries — The Heart of SQL

- Filtering Data with WHERE

- Sorting with ORDER BY

- Using DISTINCT and LIMIT

- Basic Arithmetic and Column Aliases

Week 2: Aggregations & Grouping

- COUNT, SUM, AVG, MIN, MAX — When and How

- GROUP BY — The Right Way

- HAVING vs WHERE

- Dealing with NULLs in Aggregations

- CASE Statements for Conditional Logic

*Week 3: Mastering JOINS & Relationships*

- Understanding Table Relationships (1-to-1, 1-to-Many)

- INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN

- Practical Examples with Two or More Tables

- SELF JOIN & CROSS JOIN — What, When & Why

- Common Join Mistakes & Fixes

Week 4: Advanced SQL Concepts

- Subqueries: Writing Queries Inside Queries

- CTEs (WITH Clause): Cleaner & More Readable SQL

- Window Functions: RANK, DENSE_RANK, ROW_NUMBER

- Using PARTITION BY and ORDER BY

- EXISTS vs IN: Performance and Use Cases


Week 5: Real-World Scenarios & Interview-Ready SQL

- Using SQL to Solve Real Business Problems

- SQL for Sales, Marketing, HR & Product Analytics

- Writing Clean, Efficient & Complex Queries

- Most Common SQL Interview Questions like:

“Find the second highest salary”

“Detect duplicates in a table”

“Calculate running totals”

“Identify top N products per category”

- Practice Challenges Based on Real Interviews

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SQL Joins – Essential Concepts 🚀

1️⃣ What Are SQL Joins?

SQL Joins are used to combine rows from two or more tables based on a related column.

2️⃣ Types of Joins

INNER JOIN: Returns only matching rows from both tables.
SELECT * FROM TableA INNER JOIN TableB ON TableA.id = TableB.id;

LEFT JOIN (LEFT OUTER JOIN): Returns all rows from the left table and matching rows from the right table.
SELECT * FROM TableA LEFT JOIN TableB ON TableA.id = TableB.id;

RIGHT JOIN (RIGHT OUTER JOIN): Returns all rows from the right table and matching rows from the left table.
SELECT * FROM TableA RIGHT JOIN TableB ON TableA.id = TableB.id;

FULL JOIN (FULL OUTER JOIN): Returns all rows when there is a match in either table.
SELECT * FROM TableA FULL JOIN TableB ON TableA.id = TableB.id;


3️⃣ Self Join

A table joins with itself to compare rows.
SELECT A.name, B.name FROM Employees A JOIN Employees B ON A.manager_id = B.id;

4️⃣ Cross Join

Returns the Cartesian product of both tables (every row from Table A pairs with every row from Table B).
SELECT * FROM TableA CROSS JOIN TableB;

5️⃣ Joins with Multiple Conditions

Using multiple columns for matching.
SELECT * FROM TableA INNER JOIN TableB ON TableA.id = TableB.id AND TableA.type = TableB.type;

6️⃣ Using Aliases in Joins

Shortens table names for better readability.
SELECT A.name, B.salary FROM Employees A INNER JOIN Salaries B ON A.id = B.emp_id;

7️⃣ Handling NULLs in Joins

Use COALESCE(column, default_value) to replace NULL values.

IS NULL to filter unmatched rows in LEFT or RIGHT JOINs.


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SQL Cheatsheet ✅

𝗧𝗵𝗲 𝗯𝗲𝘀𝘁 𝗦𝗤𝗟 𝗹𝗲𝘀𝘀𝗼𝗻 𝘆𝗼𝘂’𝗹𝗹 𝗿𝗲𝗰𝗲𝗶𝘃𝗲 𝘁𝗼𝗱𝗮𝘆:

Master the core SQL statements—they are the building blocks of every powerful query you'll write.

-> SELECT retrieves data efficiently and accurately. Remember, clarity starts with understanding the result set you need.

-> WHERE filters data to show only the insights that matter. Precision is key.

-> CREATE, INSERT, UPDATE, DELETE allow you to mold your database like an artist—design it, fill it, improve it, or even clean it up.

In a world where everyone wants to take, give knowledge back.

Become an alchemist of your life. Learn, share, and build solutions.

Always follow best practices in SQL to avoid mistakes like missing WHERE in an UPDATE or DELETE. These oversights can cause chaos!

Without WHERE, you risk updating or deleting entire datasets unintentionally. That's a costly mistake.

But with proper syntax and habits, your databases will be secure, efficient, and insightful.

SQL is not just a skill—it's a mindset of precision, logic, and innovation.

Here you can find essential SQL Interview Resources👇
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#sql

SQL Roadmap
👇👇
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Complete SQL Topics for Data Analysts 😄👇

1. Introduction to SQL:
- Basic syntax and structure
- Understanding databases and tables

2. Querying Data:
- SELECT statement
- Filtering data using WHERE clause
- Sorting data with ORDER BY

3. Joins:
- INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
- Combining data from multiple tables

4. Aggregation Functions:
- GROUP BY
- Aggregate functions like COUNT, SUM, AVG, MAX, MIN

5. Subqueries:
- Using subqueries in SELECT, WHERE, and HAVING clauses

6. Data Modification:
- INSERT, UPDATE, DELETE statements
- Transactions and Rollback

7. Data Types and Constraints:
- Understanding various data types (e.g., INT, VARCHAR)
- Using constraints (e.g., PRIMARY KEY, FOREIGN KEY)

8. Indexes:
- Creating and managing indexes for performance optimization

9. Views:
- Creating and using views for simplified querying

10. Stored Procedures and Functions:
- Writing and executing stored procedures
- Creating and using functions

11. Normalization:
- Understanding database normalization concepts

12. Data Import and Export:
- Importing and exporting data using SQL

13. Window Functions:
- ROW_NUMBER(), RANK(), DENSE_RANK(), and others

14. Advanced Filtering:
- Using CASE statements for conditional logic

15. Advanced Join Techniques:
- Self-joins and other advanced join scenarios

16. Analytical Functions:
- LAG(), LEAD(), OVER() for advanced analytics

17. Working with Dates and Times:
- Date and time functions and formatting

18. Performance Tuning:
- Query optimization strategies

19. Security:
- Understanding SQL injection and best practices for security

20. Handling NULL Values:
- Dealing with NULL values in queries

Ensure hands-on practice on these topics to strengthen your SQL skills.

Since SQL is one of the most essential skill for data analysts, I have decided to teach each topic daily in this channel for free. Like this post if you want me to continue this SQL series 👍♥️

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Top 5 SQL Functions

1. SELECT Statement:
   - Function: Retrieving data from one or more tables.
   - Example: SELECT column1, column2 FROM table WHERE condition;

2. COUNT Function:
   - Function: Counts the number of rows that meet a specified condition.
   - Example: SELECT COUNT(column) FROM table WHERE condition;

3. SUM Function:
   - Function: Calculates the sum of values in a numeric column.
   - Example: SELECT SUM(column) FROM table WHERE condition;

4. AVG Function:
   - Function: Computes the average value of a numeric column.
   - Example: SELECT AVG(column) FROM table WHERE condition;

5. GROUP BY Clause:
   - Function: Groups rows that have the same values in specified columns into summary rows.
   - Example: SELECT column, AVG(numeric_column) FROM table GROUP BY column;

These functions are fundamental in SQL and are frequently used for various data manipulation tasks, including data retrieval, aggregation, and analysis.

SQL (Structured Query Language), which is used to manage and manipulate relational databases.

Here's a beginner-friendly introduction:

SELECT columns
FROM table
WHERE condition;

The SELECT statement retrieves data from a table

SELECT * FROM customers;

--This retrieves all columns from the "customers" table.

You can use the WHERE clause to filter rows based on conditions.

To limit the number of rows returned, you can use the LIMIT clause.

--This retrieves the first 10 rows from the "products" table.

Use the ORDER BY clause to sort the results in ascending or descending order.

The INSERT INTO statement adds new records to a table

INSERT INTO employees (first_name, last_name) VALUES ('John', 'Doe');

--This inserts a new employee named John Doe into the "employees" table.

The UPDATE statement modifies existing records in a table.

UPDATE customers SET email = '[email protected]' WHERE customer_id = 123;

--This updates the email address for the customer with ID 123.

Joins allow you to combine data from multiple tables based on related columns

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Quick SQL functions cheat sheet for beginners

Aggregate Functions

COUNT(*): Counts rows.

SUM(column): Total sum.

AVG(column): Average value.

MAX(column): Maximum value.

MIN(column): Minimum value.


String Functions

CONCAT(a, b, …): Concatenates strings.

SUBSTRING(s, start, length): Extracts part of a string.

UPPER(s) / LOWER(s): Converts string case.

TRIM(s): Removes leading/trailing spaces.


Date & Time Functions

CURRENT_DATE / CURRENT_TIME / CURRENT_TIMESTAMP: Current date/time.

EXTRACT(unit FROM date): Retrieves a date part (e.g., year, month).

DATE_ADD(date, INTERVAL n unit): Adds an interval to a date.


Numeric Functions

ROUND(num, decimals): Rounds to a specified decimal.

CEIL(num) / FLOOR(num): Rounds up/down.

ABS(num): Absolute value.

MOD(a, b): Returns the remainder.


Control Flow Functions

CASE: Conditional logic.

COALESCE(val1, val2, …): Returns the first non-null value.


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#dataanalytics

SQL Joins – Essential Concepts 🚀

1️⃣ What Are SQL Joins?

SQL Joins are used to combine rows from two or more tables based on a related column.

2️⃣ Types of Joins

INNER JOIN: Returns only matching rows from both tables.
SELECT * FROM TableA INNER JOIN TableB ON TableA.id = TableB.id;

LEFT JOIN (LEFT OUTER JOIN): Returns all rows from the left table and matching rows from the right table.
SELECT * FROM TableA LEFT JOIN TableB ON TableA.id = TableB.id;

RIGHT JOIN (RIGHT OUTER JOIN): Returns all rows from the right table and matching rows from the left table.
SELECT * FROM TableA RIGHT JOIN TableB ON TableA.id = TableB.id;

FULL JOIN (FULL OUTER JOIN): Returns all rows when there is a match in either table.
SELECT * FROM TableA FULL JOIN TableB ON TableA.id = TableB.id;


3️⃣ Self Join

A table joins with itself to compare rows.
SELECT A.name, B.name FROM Employees A JOIN Employees B ON A.manager_id = B.id;

4️⃣ Cross Join

Returns the Cartesian product of both tables (every row from Table A pairs with every row from Table B).
SELECT * FROM TableA CROSS JOIN TableB;

5️⃣ Joins with Multiple Conditions

Using multiple columns for matching.
SELECT * FROM TableA INNER JOIN TableB ON TableA.id = TableB.id AND TableA.type = TableB.type;

6️⃣ Using Aliases in Joins

Shortens table names for better readability.
SELECT A.name, B.salary FROM Employees A INNER JOIN Salaries B ON A.id = B.emp_id;

7️⃣ Handling NULLs in Joins

Use COALESCE(column, default_value) to replace NULL values.

IS NULL to filter unmatched rows in LEFT or RIGHT JOINs.


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10 SQL Concepts Every Data Analyst Should Master 👇

✅ SELECT, WHERE, ORDER BY – Core of querying your data
✅ JOINs (INNER, LEFT, RIGHT, FULL) – Combine data from multiple tables
✅ GROUP BY & HAVING – Aggregate and filter grouped data
✅ Subqueries – Nest queries inside queries for complex logic
✅ CTEs (Common Table Expressions) – Write cleaner, reusable SQL logic
✅ Window Functions – Perform advanced analytics like rankings & running totals
✅ Indexes – Boost your query performance
✅ Normalization – Structure your database efficiently
✅ UNION vs UNION ALL – Combine result sets with or without duplicates
✅ Stored Procedures & Functions – Reusable logic inside your DB

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