SQL Programming Resources

✅ SQL Practice Questions with Answers 🧠🗃️

🔍 Q1. How to find the 2nd highest salary from a table?
✅ Answer:

SELECT MAX(salary) FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);

🔍 Q2. How to find duplicate values in a column?
✅ Answer:

SELECT name, COUNT(*) FROM employees
GROUP BY name
HAVING COUNT(*) > 1;

🔍 Q3. How to select records that exist in one table but not in another?
✅ Answer:

SELECT * FROM employees
WHERE id NOT IN (SELECT employee_id FROM payroll);

🔍 Q4. How to get the top 3 highest salaries? (MySQL)
✅ Answer:

SELECT DISTINCT salary FROM employees
ORDER BY salary DESC
LIMIT 3;

🔍 Q5. How to fetch employees with the same salary?
✅ Answer:

SELECT * FROM employees e1
WHERE EXISTS (
  SELECT 1 FROM employees e2
  WHERE e1.salary = e2.salary AND e1.id <> e2.id
);

🔍 Q6. How to get the department-wise highest salary?
✅ Answer:

SELECT department, MAX(salary) AS max_salary
FROM employees
GROUP BY department;

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Data Analytics isn't rocket science. It's just a different language.

Here's a beginner's guide to the world of data analytics:

1) Understand the fundamentals:
- Mathematics
- Statistics
- Technology

2) Learn the tools:
- SQL
- Python
- Excel (yes, it's still relevant!)

3) Understand the data:
- What do you want to measure?
- How are you measuring it?
- What metrics are important to you?

4) Data Visualization:
- A picture is worth a thousand words

5) Practice:
- There's no better way to learn than to do it yourself.

Data Analytics is a valuable skill that can help you make better decisions, understand your audience better, and ultimately grow your business.

It's never too late to start learning!

✅ Advanced SQL Queries 🗄️💡

1️⃣ GROUP BY & HAVING
⦁ GROUP BY groups rows sharing a value to perform aggregate calculations.
⦁ HAVING filters groups based on conditions (like WHERE but for groups).

Example:
Find total sales per product with sales > 1000:
SELECT product_id, SUM(sales) AS total_sales
FROM sales_data
GROUP BY product_id
HAVING SUM(sales) > 1000;

2️⃣ Subqueries
⦁ A query inside another query. Useful for filtering or calculating values dynamically.

Example:
Get customers who placed orders over 500:
SELECT customer_id, order_id, amount
FROM orders
WHERE amount > (SELECT AVG(amount) FROM orders);

3️⃣ Aggregate Functions
⦁ Perform calculations on sets of rows:
⦁ COUNT() counts rows
⦁ SUM() adds numeric values
⦁ AVG() calculates average
⦁ MAX() and MIN() find extremes

Example:
Find average order amount per customer:
SELECT customer_id, AVG(amount) AS avg_order
FROM orders
GROUP BY customer_id;

4️⃣ Complex Joins with Filtering
⦁ Join tables and filter results in one query.

Example:
List customers with orders over100:
SELECT c.customer_name, o.order_id, o.amount
FROM customers c
JOIN orders o ON c.customer_id = o.customer_id
WHERE o.amount > 100;

📌 SQL Roadmap: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v/1506

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✅10 Most Useful SQL Interview Queries (with Examples) 💼

1️⃣ Find the second highest salary:

SELECT MAX(salary)  
FROM employees  
WHERE salary < (SELECT MAX(salary) FROM employees);

2️⃣ Count employees in each department:

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

3️⃣ Fetch duplicate emails:

SELECT email, COUNT(*)  
FROM users  
GROUP BY email  
HAVING COUNT(*) > 1;

4️⃣ Join orders with customer names:

SELECT c.name, o.order_date  
FROM customers c  
JOIN orders o ON c.id = o.customer_id;

5️⃣ Get top 3 highest salaries:

SELECT DISTINCT salary  
FROM employees  
ORDER BY salary DESC  
LIMIT 3;

6️⃣ Retrieve latest 5 logins:

SELECT * FROM logins  
ORDER BY login_time DESC  
LIMIT 5;

7️⃣ Employees with no manager:

SELECT name  
FROM employees  
WHERE manager_id IS NULL;

8️⃣ Search names starting with ‘S’:

SELECT * FROM employees  
WHERE name LIKE 'S%';

9️⃣ Total sales per month:

SELECT MONTH(order_date) AS month, SUM(amount)  
FROM sales  
GROUP BY MONTH(order_date);

🔟 Delete inactive users:

DELETE FROM users  
WHERE last_active < '2023-01-01';

✅ Tip: Master subqueries, joins, groupings & filters – they show up in nearly every interview!

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✅ Interviewer: Count the number of employees in each department. 📊

Me: Using GROUP BY and COUNT():

SELECT d.dept_name,
       COUNT(e.id) AS employee_count
FROM employees e
INNER JOIN departments d
ON e.dept_id = d.dept_id
GROUP BY d.dept_name;

✔ Why it works: 
– COUNT() tallies employees per department by counting non-null IDs. 
– GROUP BY segments the results by department name for aggregated output. 
– INNER JOIN links employees to departments only where IDs match, avoiding nulls—add ORDER BY employee_count DESC to sort by largest teams first!

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✅ SQL Interview Challenge! 📊🧠

𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝗲𝗿: Find the average salary of employees in each department.

𝗠𝗲: Using GROUP BY and AVG():
SELECT d.dept_name,
AVG(e.salary) AS avg_salary
FROM employees e
INNER JOIN departments d
ON e.dept_id = d.dept_id
GROUP BY d.dept_name;

✔ Why it works:
– AVG() computes the mean salary per group, handling decimals nicely.
– GROUP BY clusters rows by department name for department-level aggregates.
– INNER JOIN links employee salaries to department names only for matching records—add ORDER BY avg_salary DESC for ranked insights!

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✅ SQL Interview Challenge! 🧠💻

𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝗲𝗿: Retrieve all employees along with their department names. Only include employees who belong to a department.

𝗠𝗲: Using INNER JOIN:

SELECT e.name AS employee_name,
       d.dept_name AS department_name
FROM employees e
INNER JOIN departments d
ON e.dept_id = d.dept_id;

✔ Why it works:
– INNER JOIN returns only rows with matching values in both tables based on the ON condition, excluding employees without a dept_id match (or vice versa).
– This ensures we get complete, valid pairs—perfect for reports focusing on assigned staff, and it's efficient for large datasets in 2025's analytics tools.

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✅ SQL Scenario-Based Question & Answer 💻📊

Scenario:
You have two tables:

Employees

| emp_id | name  | dept_id | salary |
| ------ | ----- | ------- | ------ |
| 1      | John  | 10      | 5000   |
| 2      | Alice | 20      | 6000   |
| 3      | Bob   | 10      | 4500   |
| 4      | Mary  | NULL    | 7000   |

Departments

| dept_id | dept_name |
| ------- | --------- |
| 10      | Sales     |
| 20      | Marketing |
| 30      | HR        |

Question:
Write a query to display all employees with their department name. If an employee doesn't belong to any department, show "Not Assigned" instead.

Answer:

SELECT e.name AS employee_name,
       COALESCE(d.dept_name, 'Not Assigned') AS department_name
FROM Employees e
LEFT JOIN Departments d
ON e.dept_id = d.dept_id;

Explanation:
⦁ LEFT JOIN ensures all employees are included, even those without a matching dept_id (like Mary).
⦁ COALESCE picks the first non-NULL value: dept_name if available, otherwise "Not Assigned".
⦁ This handles NULLs gracefully while keeping the full employee list intact.

Result:

| employee_name | department_name |
| ------------- | --------------- |
| John          | Sales           |
| Alice         | Marketing       |
| Bob           | Sales           |
| Mary          | Not Assigned    |

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✅ SQL Mini-Challenge! 🔍💻

𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝗲𝗿: List all employees and their managers. If an employee doesn’t have a manager, still include them.

𝗠𝗲: Using a self-join with LEFT JOIN:

SELECT e.name AS employee_name, m.name AS manager_name
FROM employees e
LEFT JOIN employees m ON e.manager_id = m.id;

✔ Why it works:
– LEFT JOIN ensures employees without managers are still included.
– Self-join allows referencing the same table for managers.
– Simple and clean solution for interviews.

🔎 Bonus Tip:
Always consider null values in joins; LEFT JOIN helps preserve the main table rows even if the related data is missing.

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𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝗲𝗿: Write a query to get the names of all employees along with their department names. If an employee is not assigned to a department, still include them.

𝗠𝗲: Here’s my SQL solution using a LEFT JOIN:

SELECT e.name AS employee_name, d.name AS department_name
FROM employees e
LEFT JOIN departments d ON e.department_id = d.id;

✔ Why it works:
– LEFT JOIN ensures all employees are shown, even those without departments.
– It joins the employees and departments tables on department_id.
– Clean, readable, and interview-ready!

🔎 Bonus Insight:
Always understand the difference between INNER JOIN, LEFT JOIN, and RIGHT JOIN. In real-world databases, missing data is common — use joins wisely to handle it.

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𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝗲𝗿: You have 2 minutes to solve this SQL query.
Retrieve the department name and the highest salary in each department from the employees table, but only for departments where the highest salary is greater than $70,000.

𝗠𝗲: Challenge accepted!

SELECT department, MAX(salary) AS highest_salary
FROM employees
GROUP BY department
HAVING MAX(salary) > 70000;

I used GROUP BY to group employees by department, MAX() to get the highest salary, and HAVING to filter the result based on the condition that the highest salary exceeds $70,000. This solution effectively shows my understanding of aggregation functions and how to apply conditions on the result of those aggregations.

𝗧𝗶𝗽 𝗳𝗼𝗿 𝗦𝗤𝗟 𝗝𝗼𝗯 𝗦𝗲𝗲𝗸𝗲𝗿𝘀:
It's not about writing complex queries; it's about writing clean, efficient, and scalable code. Focus on mastering subqueries, joins, and aggregation functions to stand out!

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✅ Advanced SQL Practice Questions with Answers 🧠📝

1️⃣ Get the second highest salary from the employees table.

SELECT MAX(salary)  
FROM employees  
WHERE salary < (SELECT MAX(salary) FROM employees);

2️⃣ List employees who earn more than the average salary.

SELECT name, salary  
FROM employees  
WHERE salary > (SELECT AVG(salary) FROM employees);

3️⃣ Show department-wise highest paid employee.

SELECT department, name, salary  
FROM (
  SELECT *,  
         RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS rnk  
  FROM employees
) AS ranked  
WHERE rnk = 1;

4️⃣ Display total sales made by each employee in 2023.

SELECT emp_id, SUM(amount) AS total_sales  
FROM sales  
WHERE YEAR(sale_date) = 2023  
GROUP BY emp_id;

5️⃣ Retrieve products with price above average in their category.

SELECT p.name, p.category, p.price  
FROM products p  
WHERE price > (
  SELECT AVG(price)  
  FROM products  
  WHERE category = p.category
);

6️⃣ Identify duplicate emails in the users table.

SELECT email, COUNT(*)  
FROM users  
GROUP BY email  
HAVING COUNT(*) > 1;

7️⃣ Rank customers based on total purchase amount.

SELECT customer_id,
SUM(amount) AS total_spent,  
       RANK() OVER (ORDER BY SUM(amount) DESC) AS rank  
FROM orders  
GROUP BY customer_id;

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✅ Advanced SQL Interview Questions with Answers 💼🧠

1️⃣ What are Window Functions in SQL?
Answer: They perform calculations across rows related to the current row without collapsing the result set.
Example:

SELECT name, salary, RANK() OVER (ORDER BY salary DESC) AS rank FROM employees;

2️⃣ Difference between RANK(), DENSE_RANK(), and ROW_NUMBER()?
– RANK(): skips numbers for ties
– DENSE_RANK(): doesn't skip numbers
– ROW_NUMBER(): gives unique numbers to each row
Use: Sorting, pagination, leaderboard design

3️⃣ What is the use of COALESCE()?
Answer: Returns the first non-null value in a list.
Example:

SELECT name, COALESCE(nickname, 'No Nick') FROM users;

4️⃣ How does CASE work in SQL?
Answer: It's used for conditional logic.
Example:

SELECT name, 
  CASE 
    WHEN score >= 90 THEN 'A' 
    WHEN score >= 80 THEN 'B' 
    ELSE 'C' 
  END AS grade 
FROM students;

5️⃣ Explain CTE (Common Table Expression).
Answer: Temporary result set for readable and reusable queries.
Example:

WITH TopSales AS (
  SELECT emp_id, SUM(sales) AS total_sales 
  FROM sales 
  GROUP BY emp_id
)  
SELECT * FROM TopSales WHERE total_sales > 5000;

6️⃣ What is the difference between EXISTS and IN?
– EXISTS: stops after finding the first match (more efficient)
– IN: compares a list of values
Use EXISTS for subqueries when checking existence

7️⃣ What are Indexes in SQL?
Answer: They improve read performance but slow down write operations.
– Types: Single-column, Composite, Unique

8️⃣ How to optimize SQL queries?
– Use proper indexes
– Avoid SELECT *
– Use WHERE filters early
– Analyze query plan

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SQL From Basic to Advanced level

Basic SQL is ONLY 7 commands:
- SELECT
- FROM
- WHERE (also use SQL comparison operators such as =, <=, >=, <> etc.)
- ORDER BY
- Aggregate functions such as SUM, AVERAGE, COUNT etc.
- GROUP BY
- CREATE, INSERT, DELETE, etc.
You can do all this in just one morning.

Once you know these, take the next step and learn commands like:
- LEFT JOIN
- INNER JOIN
- LIKE
- IN
- CASE WHEN
- HAVING (undertstand how it's different from GROUP BY)
- UNION ALL
This should take another day.

Once both basic and intermediate are done, start learning more advanced SQL concepts such as:
- Subqueries (when to use subqueries vs CTE?)
- CTEs (WITH AS)
- Stored Procedures
- Triggers
- Window functions (LEAD, LAG, PARTITION BY, RANK, DENSE RANK)
These can be done in a couple of days.
Learning these concepts is NOT hard at all

- what takes time is practice and knowing what command to use when. How do you master that?
- First, create a basic SQL project
- Then, work on an intermediate SQL project (search online) -

Lastly, create something advanced on SQL with many CTEs, subqueries, stored procedures and triggers etc.

This is ALL you need to become a badass in SQL, and trust me when I say this, it is not rocket science. It's just logic.

Remember that practice is the key here. It will be more clear and perfect with the continous practice

Best telegram channel to learn SQL: https://t.me/sqlanalyst

Data Analyst Jobs👇
https://t.me/jobs_SQL

Join @free4unow_backup for more free resources.

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ENJOY LEARNING 👍👍

✅Top 10 SQL Interview Questions 🔥

1️⃣ What is a table and a field in SQL?
⦁ Table: Organized data in rows and columns
⦁ Field: A column representing data attribute

2️⃣ Describe the SELECT statement.
⦁ Fetch data from one or more tables
⦁ Use WHERE to filter, ORDER BY to sort

3️⃣ Explain SQL constraints.
⦁ Rules for data integrity: PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, CHECK

4️⃣ What is normalization?
⦁ Process to reduce data redundancy & improve integrity (1NF, 2NF, 3NF…)

5️⃣ Explain different JOIN types with examples.
⦁ INNER, LEFT, RIGHT, FULL JOIN: Various ways to combine tables based on matching rows

6️⃣ What is a subquery? Give example.
⦁ Query inside another query:

SELECT name FROM employees
WHERE department_id = (SELECT id FROM departments WHERE name='Sales');

7️⃣ How to optimize slow queries?
⦁ Use indexes, avoid SELECT *, simplify joins, reduce nested queries

8️⃣ What are aggregate functions? Examples?
⦁ Perform calculations on sets: SUM(), COUNT(), AVG(), MIN(), MAX()

9️⃣ What is SQL injection? How to prevent it?
⦁ Security risk manipulating queries
⦁ Prevent: parameterized queries, input validation

🔟 How to find the Nth highest salary without TOP/LIMIT?

SELECT DISTINCT salary FROM employees e1
WHERE N-1 = (SELECT COUNT(DISTINCT salary) FROM employees e2 WHERE e2.salary > e1.salary);

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SQL Cheatsheet 📝

This SQL cheatsheet is designed to be your quick reference guide for SQL programming. Whether you’re a beginner learning how to query databases or an experienced developer looking for a handy resource, this cheatsheet covers essential SQL topics.

1. Database Basics
- CREATE DATABASE db_name;
- USE db_name;

2. Tables
- Create Table: CREATE TABLE table_name (col1 datatype, col2 datatype);
- Drop Table: DROP TABLE table_name;
- Alter Table: ALTER TABLE table_name ADD column_name datatype;

3. Insert Data
- INSERT INTO table_name (col1, col2) VALUES (val1, val2);

4. Select Queries
- Basic Select: SELECT * FROM table_name;
- Select Specific Columns: SELECT col1, col2 FROM table_name;
- Select with Condition: SELECT * FROM table_name WHERE condition;

5. Update Data
- UPDATE table_name SET col1 = value1 WHERE condition;

6. Delete Data
- DELETE FROM table_name WHERE condition;

7. Joins
- Inner Join: SELECT * FROM table1 INNER JOIN table2 ON table1.col = table2.col;
- Left Join: SELECT * FROM table1 LEFT JOIN table2 ON table1.col = table2.col;
- Right Join: SELECT * FROM table1 RIGHT JOIN table2 ON table1.col = table2.col;

8. Aggregations
- Count: SELECT COUNT(*) FROM table_name;
- Sum: SELECT SUM(col) FROM table_name;
- Group By: SELECT col, COUNT(*) FROM table_name GROUP BY col;

9. Sorting & Limiting
- Order By: SELECT * FROM table_name ORDER BY col ASC|DESC;
- Limit Results: SELECT * FROM table_name LIMIT n;

10. Indexes
- Create Index: CREATE INDEX idx_name ON table_name (col);
- Drop Index: DROP INDEX idx_name;

11. Subqueries
- SELECT * FROM table_name WHERE col IN (SELECT col FROM other_table);

12. Views
- Create View: CREATE VIEW view_name AS SELECT * FROM table_name;
- Drop View: DROP VIEW view_name;

✅ Top 10 SQL Interview Questions

1️⃣ What is SQL and its types? 
SQL (Structured Query Language) is used to manage and manipulate databases. 
Types: DDL, DML, DCL, TCL 
Example: CREATE, SELECT, GRANT, COMMIT

2️⃣ Explain SQL constraints. 
Constraints ensure data integrity:
⦁ PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, CHECK

3️⃣ What is normalization? 
It's organizing data to reduce redundancy and improve integrity (1NF, 2NF, 3NF…).

4️⃣ Explain different types of JOINs with example.
⦁ INNER JOIN: Returns matching rows
⦁ LEFT JOIN: All from left + matching right rows
⦁ RIGHT JOIN: All from right + matching left rows
⦁ FULL JOIN: All rows from both tables

5️⃣ What is a subquery? Give example. 
A query inside another query:

SELECT name FROM employees
WHERE department_id = (SELECT id FROM departments WHERE name='Sales');

6️⃣ How to optimize slow queries? 
Use indexes, avoid SELECT *, use joins wisely, reduce nested queries.

7️⃣ What are aggregate functions? List examples. 
Functions that perform a calculation on a set of values: 
SUM(), COUNT(), AVG(), MIN(), MAX()

8️⃣ Explain SQL injection and prevention. 
A security vulnerability to manipulate queries. Prevent via parameterized queries, input validation.

9️⃣ How to find Nth highest salary without TOP/LIMIT?

SELECT DISTINCT salary FROM employees e1
WHERE N-1 = (SELECT COUNT(DISTINCT salary) FROM employees e2 WHERE e2.salary > e1.salary);

🔟 What is a stored procedure? 
A precompiled SQL program that can be executed to perform operations repeatedly.

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✅ 50 Must-Know SQL Concepts for Interviews 💾📊

📍 SQL Basics
1. What is SQL
2. Types of SQL commands (DDL, DML, DCL, TCL)
3. Database vs Table
4. Primary Key & Foreign Key
5. NULL vs NOT NULL

📍 Data Retrieval
6. SELECT statement
7. WHERE clause
8. DISTINCT keyword
9. ORDER BY clause
10. LIMIT / TOP

📍 Filtering & Conditions
11. LIKE, BETWEEN, IN
12. IS NULL & IS NOT NULL
13. AND, OR, NOT
14. CASE statements
15. Aliases using AS

📍 Joins (Very Important)
16. INNER JOIN
17. LEFT JOIN
18. RIGHT JOIN
19. FULL OUTER JOIN
20. SELF JOIN

📍 Aggregation & Grouping
21. COUNT(), SUM(), AVG()
22. MIN(), MAX()
23. GROUP BY clause
24. HAVING vs WHERE
25. GROUP BY with multiple columns

📍 Subqueries & Nested Queries
26. Scalar subqueries
27. Correlated subqueries
28. IN vs EXISTS
29. Using subqueries in SELECT
30. CTE (Common Table Expressions)

📍 Modifying Data
31. INSERT INTO
32. UPDATE
33. DELETE
34. UPSERT (MERGE)
35. TRUNCATE vs DELETE

📍 Constraints & Indexing
36. UNIQUE constraint
37. CHECK constraint
38. DEFAULT values
39. Indexes – clustered vs non-clustered
40. AUTO_INCREMENT / SERIAL

📍 Views & Stored Procedures
41. Creating and using Views
42. Stored Procedures basics
43. Functions vs Procedures
44. Triggers
45. Transactions (COMMIT, ROLLBACK)

📍 Optimization & Tools
46. EXPLAIN or Query Plan
47. Avoiding SELECT *
48. Normalization
49. Denormalization
50. Popular SQL platforms (MySQL, PostgreSQL, MS SQL Server)

SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v

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📉 20 High-Income Skills to Learn...

𝗦𝗤𝗟 𝗠𝘂𝘀𝘁-𝗞𝗻𝗼𝘄 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 📊

Whether you're writing daily queries or preparing for interviews, understanding these subtle SQL differences can make a big impact on both performance and accuracy.

🧠 Here’s a powerful visual that compares the most commonly misunderstood SQL concepts — side by side.

📌 𝗖𝗼𝘃𝗲𝗿𝗲𝗱 𝗶𝗻 𝘁𝗵𝗶𝘀 𝘀𝗻𝗮𝗽𝘀𝗵𝗼𝘁:
🔹 RANK() vs DENSE_RANK()
🔹 HAVING vs WHERE
🔹 UNION vs UNION ALL
🔹 JOIN vs UNION
🔹 CTE vs TEMP TABLE
🔹 SUBQUERY vs CTE
🔹 ISNULL vs COALESCE
🔹 DELETE vs DROP
🔹 INTERSECT vs INNER JOIN
🔹 EXCEPT vs NOT IN

React ♥️ for detailed explanation