Day 6: Grouping Data with GROUP BY

Guys, it’s time to level up with GROUP BY! This command helps you group data and apply aggregate functions to each group.

Example:

SELECT department, COUNT(*) AS total_employees
FROM Employees
GROUP BY department;

🎯 This gives the total number of employees in each department.

Mini Challenge:
If you have a Sales table, how would you calculate total sales for each region? Drop your query below!

Tomorrow, we’ll wrap up with JOINs—one of the most powerful SQL concepts. Stay tuned!

#SQL #LearnSQL #DataSkills

Day 7: Combining Tables with JOINs

Guys, let’s end the week strong by learning about JOINs! They’re the secret to combining data from multiple tables.

Example:

SELECT Employees.name, Departments.department_name
FROM Employees
JOIN Departments
ON Employees.department_id = Departments.id;

🎯 This combines the Employees table with the Departments table to show each employee’s name along with their department.

Mini Challenge:
Imagine a Customers table and an Orders table. How would you join them to show each customer’s name with their order details? Share your query below!

Keep practicing, and let me know which SQL concept you’d like to learn next!

#SQL #LearnSQL #DataAnalytics

Congrats, guys! You've made it through the first week of SQL! 🎉 Now, let's talk about some tips to keep improving your SQL skills:

1️⃣ Practice Regularly: The more queries you write, the better you'll get. Try solving challenges on platforms like LeetCode, HackerRank, or SQLZoo.
2️⃣ Use Real-World Data: Work with data you find interesting—whether it’s sales, sports, or movies. It makes learning more fun!
3️⃣ Understand the Theory: Learn how SQL queries work behind the scenes (like indexing, optimization, etc.) to boost your performance.

Mini Challenge:
What’s the most complex SQL query you've written so far? Share it below and let’s discuss!

Thanks for joining me on this SQL journey! Keep practicing, and you’ll be a SQL pro in no time. 🚀

#SQL #LearnSQL #DataSkills

Mini Challenge:
Imagine a Customers table and an Orders table. How would you join them to show each customer’s name with their order details? Share your query below!

Keep practicing, and let me know which SQL concept you’d like to learn next!

Day 8: Handling NULL Values in SQL

Guys, today we're diving into NULL values. They can be tricky, but understanding how to handle them is key!

1️⃣ What is NULL?
NULL represents missing or unknown values in a database. It’s not the same as an empty string or zero—it means "no value."

2️⃣ How to check for NULL?
Use IS NULL or IS NOT NULL to filter rows with or without NULL values.
Example:

SELECT name, age
FROM Students
WHERE age IS NOT NULL;

🎯 This gives all students who have an age recorded.

Mini Challenge:
If you have a Products table, how would you find all products with missing prices? Post your query below!

Next, we’ll explore subqueries!

#SQL #LearnSQL #DataAnalytics

Day 9: Subqueries – Queries Within Queries

Guys, let’s take it up a notch with subqueries!

These are queries nested inside another query, and they’re super useful for complex data retrieval.

Example:

SELECT name
FROM Students
WHERE age > (SELECT AVG(age) FROM Students);

🎯 This fetches the names of students older than the average age.

Think of subqueries as a way to break down problems into smaller, manageable parts.

Mini Challenge:
Using an Employees table, how would you find employees earning more than the average salary? Share your query below!

Tomorrow, we’ll learn about views—stay tuned!

#SQL #LearnSQL #DataSkills

Day 10: SQL Views

Guys, let’s talk about Views now — for simplifying complex queries!

A View is like a virtual table created from a query. Instead of writing the same query repeatedly, you can save it as a View and use it like a table.

Example:

CREATE VIEW HighEarners AS
SELECT name, salary
FROM Employees
WHERE salary > 50000;

SELECT * FROM HighEarners;

🎯 This saves all employees earning more than 50,000 into a View called HighEarners.

Mini Challenge:
If you had a Sales table, what View would you create to find regions with sales above 1,00,000? Drop your ideas below!

Tomorrow, we’ll explore Indexes for faster queries—don’t miss it!

#SQL #LearnSQL #DataAnalytics

Day 11: Speed Up Your Queries with Indexes

Guys, let’s talk about Indexes! They’re like a book’s table of contents—they help you find data faster in large tables.

Here’s how to create an Index:

CREATE INDEX idx_name ON Employees(name);

🎯 This creates an Index on the name column of the Employees table, making searches by name much quicker.

But remember, while Indexes speed up reads, they can slow down writes (like INSERT or UPDATE). Use them wisely!

Mini Challenge:
If you had a Customers table, which column(s) would you index to improve query performance? Share your thoughts below!

Tomorrow, we’ll tackle Common Table Expressions (CTEs)—a must-know for clean and reusable queries!

#SQL #LearnSQL #DataSkills

Day 12: Writing Cleaner Queries with CTEs

Guys, let’s simplify complex queries with Common Table Expressions (CTEs)! They make your SQL code more readable and reusable.

Here’s how a CTE works:

WITH HighEarners AS (
SELECT name, salary
FROM Employees
WHERE salary > 50000
)
SELECT name
FROM HighEarners
WHERE salary > 70000;

🎯 This breaks the query into smaller, logical steps—perfect for complex scenarios.

Mini Challenge:
If you had a Sales table, how would you use a CTE to find regions with total sales greater than 1,00,000? Write your queries below!

Tomorrow, we’ll dive into Window Functions—get ready to level up!

#SQL #LearnSQL #DataAnalytics

Day 13: Level Up with Window Functions

Guys, today’s topic is Window Functions! They allow you to perform calculations across rows, without grouping the data like aggregate functions.

Here’s an example to calculate a running total:

SELECT name, salary,
SUM(salary) OVER (ORDER BY salary) AS running_total
FROM Employees;

🎯 This calculates a running total of salaries while keeping each row visible.

Window functions are great for ranking, percentages, and trends.

Mini Challenge:
Using a Sales table, how would you calculate the rank of each region based on total sales? Share your ideas below!

Tomorrow, we’ll explore how to handle duplicate records in SQL. Don’t miss it!

#SQL #LearnSQL #DataSkills

Day 14: Handling Duplicates in SQL

Guys, let’s tackle duplicate records in your data—an important skill for clean and accurate results!

To identify duplicates, use GROUP BY with HAVING:

SELECT name, COUNT(*) AS count
FROM Employees
GROUP BY name
HAVING COUNT(*) > 1;

🎯 This lists all duplicate names in the Employees table.

To remove duplicates, use DISTINCT:

SELECT DISTINCT name, department
FROM Employees;

🎯 This retrieves unique combinations of name and department.

Mini Challenge:
Using a Products table, how would you find and remove duplicate product entries? Drop your queries below!

Tomorrow, we’ll summarize the journey so far and discuss how to build your own SQL projects. Stay tuned!

#SQL #LearnSQL #DataSkills

Day 15: Building Your Own SQL Projects

Guys, it’s time to apply everything you’ve learned so far by building your own SQL project! Projects are the best way to solidify your skills and showcase them to potential employers.

Here’s a simple project idea:
1️⃣ Use a free dataset (like Kaggle or Data.gov).
2️⃣ Create a database with at least two related tables, like Customers and Orders.
3️⃣ Write queries to:

Retrieve insights (e.g., total sales by region).

Use joins, aggregate functions, and CTEs.

Apply window functions for trends or rankings.


🎯 Example Query:

WITH RegionalSales AS (
SELECT region, SUM(sales) AS total_sales
FROM Sales
GROUP BY region
)
SELECT region, total_sales,
RANK() OVER (ORDER BY total_sales DESC) AS rank
FROM RegionalSales;

Mini Challenge:
What SQL project idea excites you the most? Share your ideas below!

Stay consistent, and soon, SQL will be second nature. Let me know what other concepts you want to explore next!

#SQL #LearnSQL #DataAnalytics

Day 16: Exploring Advanced SQL Topics

Guys, now that you’ve built a foundation, let’s explore some advanced SQL topics to take your skills to the next level:

1️⃣ Stored Procedures: Write reusable blocks of SQL code.
2️⃣ Triggers: Automate actions like logging changes in a table.
3️⃣ Transaction Management: Ensure data consistency with COMMIT and ROLLBACK.
4️⃣ Performance Optimization: Learn about indexing strategies and query optimization.

Here’s a sneak peek of a stored procedure:

CREATE PROCEDURE GetHighEarners()
AS
BEGIN
SELECT name, salary
FROM Employees
WHERE salary > 70000;
END;

🎯 You can call this procedure anytime with EXEC GetHighEarners.

Mini Challenge:
Which advanced SQL topic would you like to learn first? Drop your suggestions below, and let’s deep dive!

#SQL #LearnSQL #DataSkills

Day 17: SQL for Real-World Scenarios

Guys, today let’s discuss how SQL is used in real-world scenarios. Understanding the applications makes learning more exciting and practical!

1️⃣ E-Commerce: Analyze sales trends, customer behavior, and product performance.
Example Query:

SELECT product_name, SUM(quantity) AS total_sold
FROM Orders
GROUP BY product_name
ORDER BY total_sold DESC;

2️⃣ Finance: Monitor transactions, detect fraud, and calculate account balances.
Example Query:

SELECT account_id, SUM(amount) AS balance
FROM Transactions
GROUP BY account_id;

3️⃣ Healthcare: Manage patient records and monitor hospital performance.
Example Query:

SELECT department, COUNT(*) AS total_patients
FROM Patients
GROUP BY department;

Mini Challenge:
Which industry interests you the most, and how would you apply SQL to solve a problem in it? Share your ideas below!

Tomorrow, we’ll start exploring how to prepare for SQL interviews—don’t miss it!

#SQL #LearnSQL #DataAnalytics

Day 18: Preparing for SQL Interviews

Guys, let’s shift gears and focus on SQL interview prep. Knowing how to tackle interview questions can set you apart!

Here’s a quick breakdown of common SQL interview topics:

1️⃣ Basic Queries: Write SELECT, WHERE, and GROUP BY queries.
Example:

SELECT department, AVG(salary) AS avg_salary
FROM Employees
GROUP BY department;

2️⃣ Joins: Understand INNER, LEFT, RIGHT, FULL, and SELF JOIN.
Example:

SELECT Orders.order_id, Customers.customer_name
FROM Orders
INNER JOIN Customers
ON Orders.customer_id = Customers.customer_id;

3️⃣ Complex Scenarios: Use CTEs, Window Functions, and Subqueries.

4️⃣ Problem Solving: Be ready to debug and optimize inefficient queries.

Mini Challenge:
What’s one SQL question you’ve faced or are curious about? Share it below, and I’ll help you crack it!

Tomorrow, we’ll go over a list of must-know SQL functions. Stay tuned!

#SQL #LearnSQL #DataSkills

Basic SQL commands and aggregate functions: 👇
https://news.1rj.ru/str/mysqldata/32

Day 18: Preparing for SQL Interviews

Guys, let’s shift gears and focus on SQL interview prep. Knowing how to tackle interview questions can set you apart!

Here’s a quick breakdown of common SQL interview topics:

1️⃣ Basic Queries: Write SELECT, WHERE, and GROUP BY queries.
Example:

SELECT department, AVG(salary) AS avg_salary
FROM Employees
GROUP BY department;

2️⃣ Joins: Understand INNER, LEFT, RIGHT, FULL, and SELF JOIN.
Example:

SELECT Orders.order_id, Customers.customer_name
FROM Orders
INNER JOIN Customers
ON Orders.customer_id = Customers.customer_id;

3️⃣ Complex Scenarios: Use CTEs, Window Functions, and Subqueries.

4️⃣ Problem Solving: Be ready to debug and optimize inefficient queries.

Mini Challenge:
What’s one SQL question you’ve faced or are curious about? Share it below, and I’ll help you crack it!

Tomorrow, we’ll go over a list of must-know SQL functions. Stay tuned!

#SQL #LearnSQL #DataSkills

Day 19: Must-Know SQL Functions

Guys, today we’re diving into some essential SQL functions that can make your queries powerful and efficient!

1️⃣ Aggregate Functions:

SUM(): Adds up values.

AVG(): Finds the average.

COUNT(): Counts rows.

MIN() / MAX(): Gets the smallest or largest value.


Example:

SELECT department, COUNT(*) AS num_employees, AVG(salary) AS avg_salary
FROM Employees
GROUP BY department;

2️⃣ String Functions:

CONCAT(): Combines strings.

SUBSTRING(): Extracts part of a string.

UPPER() / LOWER(): Changes case.


Example:

SELECT CONCAT(first_name, ' ', last_name) AS full_name
FROM Employees;

3️⃣ Date Functions:

NOW(): Returns the current date and time.

DATEDIFF(): Calculates the difference between dates.

YEAR() / MONTH(): Extracts year/month from a date.


Example:

SELECT name, DATEDIFF(NOW(), hire_date) AS days_employed
FROM Employees;

Mini Challenge:
Try writing a query that uses both an aggregate and a date function. Share your query below!

Tomorrow, we’ll cover SQL best practices to write clean and maintainable code. Don’t miss it!

#SQL #LearnSQL #DataSkills

Day 20: SQL Best Practices for Clean Code

Guys, let’s wrap up our journey with some SQL best practices to keep your code clean, efficient, and easy to maintain!

1️⃣ Use Denoscriptive Naming:

Name your tables, columns, and variables clearly.

Example: Instead of tbl1, use SalesData.


2️⃣ Comment Your Code:

Use comments to explain complex logic.

Example:


-- Selecting the top 5 highest-paid employees
SELECT name, salary
FROM Employees
ORDER BY salary DESC
LIMIT 5;

3️⃣ Avoid SELECT *:

Specify only the columns you need to improve performance and clarity.


4️⃣ Use Aliases Wisely:

Shorten long table or column names with aliases for better readability.

Example:


SELECT e.name, d.department_name
FROM Employees e
JOIN Departments d ON e.department_id = d.department_id;

5️⃣ Consistent Formatting:

Indent your code to make it easier to read.


6️⃣ Optimize Joins:

Be mindful of the type of join and how it impacts performance.


Mini Challenge:
Revise one of your older SQL queries to apply these best practices. Share the improved version below!

That wraps up our SQL series! I hope this helped you level up your skills. What would you like to learn next?

#SQL #LearnSQL #DataSkills

Since we’ve covered 20 days of engaging and educational content on SQL, it’s time to consolidate everything you’ve learned and keep the momentum going!

Bonus Day: SQL Project Ideas to Build Your Portfolio

Guys, now that you've mastered SQL fundamentals and best practices, it's time to apply your skills to real projects that can boost your portfolio! Here are a few project ideas:

1️⃣ E-commerce Sales Dashboard:

Create a dashboard that tracks total sales, top-selling products, customer demographics, and trends over time.

Use SQL queries to aggregate data from different tables and create reports.


2️⃣ Employee Management System:

Build an HR database with employee details, salaries, departments, and performance metrics.

Write queries to identify top performers, calculate average salaries, and monitor department headcounts.


3️⃣ Sales and Marketing Analytics:

Create a project that analyzes the effectiveness of marketing campaigns by comparing conversion rates, customer acquisition costs, and ROI.


4️⃣ Customer Segmentation Tool:

Design a project that segments customers based on their purchase history, location, and demographics.

Use SQL to write complex queries with CASE statements and GROUP BY for insightful segments.


5️⃣ Hospital Management Database:

Build a database with patient records, doctor assignments, treatment history, and appointment scheduling.

Create queries to find the most booked doctors, calculate average wait times, and analyze patient demographics.


Mini Challenge:

Pick one of the projects above or come up with your own idea. Start by sketching out the main tables and their relationships. Share your project plan below!

#SQL #SQLProjects #DataSkills

SQL 𝗢𝗿𝗱𝗲𝗿 𝗢𝗳 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 ↓

1 → FROM (Tables selected).
2 → WHERE (Filters applied).
3 → GROUP BY (Rows grouped).
4 → HAVING (Filter on grouped data).
5 → SELECT (Columns selected).
6 → ORDER BY (Sort the data).
7 → LIMIT (Restrict number of rows).

𝗖𝗼𝗺𝗺𝗼𝗻 𝗤𝘂𝗲𝗿𝗶𝗲𝘀 𝗧𝗼 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 ↓

↬ Find the second-highest salary:

SELECT MAX(Salary) FROM Employees WHERE Salary < (SELECT MAX(Salary) FROM Employees);

↬ Find duplicate records:

SELECT Name, COUNT(*)
FROM Emp
GROUP BY Name
HAVING COUNT(*) > 1;