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SQL Programming Resources

If I need to teach someone data analytics from the basics, here is my strategy:

1. I will first remove the fear of tools from that person

2. i will start with the excel because it looks familiar and easy to use

3. I put more emphasis on projects like at least 5 to 6 with the excel. because in industry you learn by doing things

4. I will release the person from the tutorial hell and move into a more action oriented person

5. Then I move to the sql because every job wants it , even with the ai tools you need strong understanding for it if you are going to use it daily

6. After strong understanding, I will push the person to solve 100 to 150 Sql problems from basic to advance

7. It helps the person to develop the analytical thinking

8. Then I push the person to solve 3 case studies as it helps how we pull the data in the real life

9. Then I move the person to power bi to do again 5 projects by using either sql or excel files

10. Now the fear is removed.

11. Now I push the person to solve unguided challenges and present them by video recording as it increases the problem solving, communication and data story telling skills

12. Further it helps you to clear case study round given by most of the companies

13. Now i help the person how to present them in resume and also how these tools are used in real world.

14. You know the interesting fact, all of above is present free in youtube and I also mentor the people through existing youtube videos.

15. But people stuck in the tutorial hell, loose motivation , stay confused that they are either in the right direction or not.

16. As a personal mentor , I help them to get of the tutorial hell, set them in the right direction and they stay motivated when they start to see the difference before amd after mentorship

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SQL Programming Resources

𝐒𝐨𝐦𝐞 𝐁𝐞𝐬𝐭 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 𝐭𝐨 𝐡𝐞𝐥𝐩 𝐲𝐨𝐮 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐲𝐨𝐮𝐫 𝐒𝐐𝐋 𝐪𝐮𝐞𝐫𝐢𝐞𝐬:

1. Simplify Joins

• Decompose complex joins into simpler, more manageable queries when possible.
• Index columns that are used as foreign keys in joins to enhance join performance.

2. Query Structure Optimization

• Apply WHERE clauses as early as possible to filter out rows before they are processed further.
• Utilize LIMIT or TOP clauses to restrict the number of rows returned, which can significantly reduce processing time.

3. Partition Large Tables

• Divide large tables into smaller, more manageable partitions.
• Ensure that each partition is properly indexed to maintain query performance.

4. Optimize SELECT Statements

• Limit the columns in your SELECT clause to only those you need. Avoid using SELECT * to prevent unnecessary data retrieval.
• Prefer using EXISTS over IN for subqueries to improve query performance.

5. Use Temporary Tables Wisely

• Temporary Tables: Use temporary tables to save intermediate results when you have a complex query. This helps break down a complicated query into simpler steps, making it easier to manage and faster to run.

6. Optimize Table Design

• Normalize your database schema to eliminate redundant data and improve consistency.
• Consider denormalization for read-heavy systems to reduce the number of joins needed.

7. Avoid Correlated Subqueries

• Replace correlated subqueries with joins or use derived tables to improve performance.
• Correlated subqueries can be very inefficient as they are executed multiple times.

8. Use Stored Procedures:

• Put complicated database tasks into stored procedures. These are pre-written sets of instructions saved in the database. They make your queries run faster because the database doesn’t have to figure out how to execute them each time

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SQL Programming Resources

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SQL Programming Resources

If I had to start learning data analyst all over again, I'd follow this:

1- Learn SQL:

---- Joins (Inner, Left, Full outer and Self)
---- Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)
---- Group by and Having clause
---- CTE and Subquery
---- Windows Function (Rank, Dense Rank, Row number, Lead, Lag etc)

2- Learn Excel:

---- Mathematical (COUNT, SUM, AVG, MIN, MAX, etc)
---- Logical Functions (IF, AND, OR, NOT)
---- Lookup and Reference (VLookup, INDEX, MATCH etc)
---- Pivot Table, Filters, Slicers

3- Learn BI Tools:

---- Data Integration and ETL (Extract, Transform, Load)
---- Report Generation
---- Data Exploration and Ad-hoc Analysis
---- Dashboard Creation

4- Learn Python (Pandas) Optional:

---- Data Structures, Data Cleaning and Preparation
---- Data Manipulation
---- Merging and Joining Data (Merging and joining DataFrames -similar to SQL joins)
---- Data Visualization (Basic plotting using Matplotlib and Seaborn)

Hope this helps you 😊

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SQL Programming Resources

🛠️ Must-Know SQL Commands & Functions

✅

1. SELECT – Retrieve data
   › SELECT * FROM customers;

2. WHERE – Filter rows
   › SELECT * FROM orders WHERE amount > 500;

3. ORDER BY – Sort results
   › SELECT name FROM users ORDER BY age DESC;

4. GROUP BY – Aggregate data
   › SELECT department, COUNT(*) FROM employees GROUP BY department;

5. JOIN – Combine tables
   › SELECT a.name, b.salary FROM employees a JOIN salaries b ON a.id = b.emp_id;

6. INSERT INTO – Add new data
   › INSERT INTO users (name, age) VALUES ('John', 30);

7. UPDATE – Modify existing data
   › UPDATE products SET price = 100 WHERE id = 1;

8. DELETE – Remove data
   › DELETE FROM logs WHERE date < '2023-01-01';

9. LIKE – Pattern matching
   › SELECT * FROM customers WHERE name LIKE 'A%';

10. LIMIT – Restrict result rows
    › SELECT * FROM sales LIMIT 10;

💡 Tip: Practice on real datasets. Learn JOIN and GROUP BY early—they’re game changers!

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7 Baby Steps to Learn SQL

1. Understand the Basics: Start by learning the foundational concepts of SQL. Understand what SQL is, its role in managing databases, and basic operations like selecting data using SELECT, filtering with WHERE, and sorting with ORDER BY. Familiarize yourself with relational database management systems (RDBMS) such as MySQL, PostgreSQL, or SQLite.

2. Master CRUD Operations: Practice writing SQL queries to perform CRUD operations (Create, Read, Update, Delete). Learn how to:

Insert data using INSERT INTO.

Retrieve data with SELECT.

Update records with UPDATE.

Delete rows using DELETE.

3. Work with Functions and Aggregations: Dive into SQL functions and aggregate queries. Understand how to use functions like MIN, MAX, AVG, COUNT, and SUM. Practice grouping data with GROUP BY and filtering aggregated data using HAVING.

4. Explore Joins and Relationships: Learn to combine data from multiple tables using different types of joins (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN). Understand table relationships (one-to-one, one-to-many, many-to-many) and how to leverage them effectively in queries.

5. Write Complex Queries: Advance to writing more complex SQL queries, including subqueries, Common Table Expressions (CTEs), and nested queries. Practice scenarios like finding duplicate entries, ranking data, or retrieving hierarchical data.

6. Understand Database Design: Learn about database normalization and denormalization to design efficient database schemas. Understand primary keys, foreign keys, constraints, and indexing to optimize query performance.

7. Engage with SQL Communities: Join SQL forums, GitHub repositories, and platforms like StackOverflow, or WhatsApp's SQL community. Participate in SQL challenges on websites like HackerRank, LeetCode, or Stratascrach to sharpen your skills and get feedback from experienced developers.

Additional Tips:

- Work on real-world datasets to understand practical applications.
- Explore advanced concepts like stored procedures, triggers, and views as you progress.
- Regularly review your queries to find optimization opportunities.

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🔹 Top 10 SQL Functions/Commands Commonly Used in Data Analysis 📊

1️⃣ SELECT
– Used to retrieve specific columns from a table.
SELECT name, age FROM users;

2️⃣ WHERE
– Filters rows based on a condition.
SELECT × FROM sales WHERE region = 'North';

3️⃣ GROUP BY
– Groups rows that have the same values into summary rows.
SELECT region, SUM(sales) FROM sales GROUP BY region;

4️⃣ ORDER BY
– Sorts the result by one or more columns.
SELECT * FROM customers ORDER BY created_at DESC;

5️⃣ JOIN
– Combines rows from two or more tables based on a related column.
SELECT a.name, b.salary
FROM employees a
JOIN salaries b ON a.id = b.emp_id;

6️⃣ COUNT() / SUM() / AVG() / MIN() / MAX()
– Common aggregate functions for metrics and summaries.
SELECT COUNT(×) FROM orders WHERE status = 'completed';

7️⃣ HAVING
– Filters after a GROUP BY (unlike WHERE, which filters before).
SELECT department, COUNT() FROM employees GROUP BY department HAVING COUNT() > 10;

8️⃣ LIMIT
– Restricts number of rows returned.
SELECT * FROM products LIMIT 5;

9️⃣ CASE
– Implements conditional logic in queries.
SELECT name,
CASE
WHEN score >= 90 THEN 'A'
WHEN score >= 75 THEN 'B'
ELSE 'C'
END AS grade
FROM students;

🔟 DATE functions (NOW(), DATE_PART(), DATEDIFF(), etc.)
– Handle and extract info from dates.
SELECT DATE_PART('year', order_date) FROM orders;

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SQL Programming Resources

✅

Top 10 SQL Interview Questions 💼📊

1️⃣ What is a CTE (Common Table Expression)?
A temporary result set used for complex queries.

WITH temp AS (SELECT * FROM employees WHERE salary > 50000)  
SELECT * FROM temp;

2️⃣ Difference between RANK(), DENSE_RANK(), and ROW_NUMBER()?
⦁ ROW_NUMBER(): Unique sequence number
⦁ RANK(): Skips ranks for ties
⦁ DENSE_RANK(): No gaps in ranking

3️⃣ What is a window function?
Calculations across a set of rows related to the current row, using OVER(PARTITION BY…).

4️⃣ Difference between WHERE and HAVING?
⦁ WHERE: Filters rows before aggregation
⦁ HAVING: Filters rows after aggregation

5️⃣ What is indexing and how does it work?
Speeds up queries by creating fast-lookups, like a book’s index.

6️⃣ How to remove duplicate records in SQL?

SELECT DISTINCT * FROM table_name;

7️⃣ Difference between UNION and UNION ALL?
⦁ UNION: Removes duplicates
⦁ UNION ALL: Includes all rows

8️⃣ How to update data using JOIN?

UPDATE emp  
SET emp.salary = dept.bonus  
FROM emp  
JOIN dept ON emp.dept_id = dept.id;

9️⃣ Explain COALESCE() vs ISNULL().
⦁ COALESCE(): Returns first non-null from a list
⦁ ISNULL(): Replaces NULL with a specified value (SQL Server)

🔟 What is a correlated subquery?
A subquery referencing outer query columns, executed row-by-row.

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SQL Programming Resources

🔰 SQL Roadmap for Beginners 2025
├── 🗃 Introduction to Databases & SQL
├── 📄 SQL vs NoSQL (Just Basics)
├── 🧱 Database Concepts (Tables, Rows, Columns, Keys)
├── 🔍 Basic SQL Queries (SELECT, WHERE)
├── ✏️ Filtering & Sorting Data (ORDER BY, LIMIT)
├── 🔢 SQL Operators (IN, BETWEEN, LIKE, AND, OR)
├── 📊 Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)
├── 👥 GROUP BY & HAVING Clauses
├── 🔗 SQL JOINS (INNER, LEFT, RIGHT, FULL, SELF)
├── 📦 Subqueries & Nested Queries
├── 🏷 Aliases & Case Statements
├── 🧾 Views & Indexes (Basics)
├── 🧠 Common Table Expressions (CTEs)
├── 🔄 Window Functions (ROW_NUMBER, RANK, PARTITION BY)
├── ⚙️ Data Manipulation (INSERT, UPDATE, DELETE)
├── 🧱 Data Definition (CREATE, ALTER, DROP)
├── 🔐 Constraints & Relationships (PK, FK, UNIQUE, CHECK)
├── 🧪 Real-world SQL Scenarios & Challenges

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🎯 Top 20 SQL Interview Questions You Must Know

SQL is one of the most in-demand skills for Data Analysts.

Here are 20 SQL interview questions that frequently appear in job interviews.

📌 Basic SQL Questions

1️⃣ What is the difference between INNER JOIN and LEFT JOIN?
2️⃣ How does GROUP BY work, and why do we use it?
3️⃣ What is the difference between HAVING and WHERE?
4️⃣ How do you remove duplicate rows from a table?
5️⃣ What is the difference between RANK(), DENSE_RANK(), and ROW_NUMBER()?

📌 Intermediate SQL Questions

6️⃣ How do you find the second highest salary from an Employee table?
7️⃣ What is a Common Table Expression (CTE), and when should you use it?
8️⃣ How do you identify missing values in a dataset using SQL?
9️⃣ What is the difference between UNION and UNION ALL?
🔟 How do you calculate a running total in SQL?

📌 Advanced SQL Questions

1️⃣1️⃣ How does a self-join work? Give an example.
1️⃣2️⃣ What is a window function, and how is it different from GROUP BY?
1️⃣3️⃣ How do you detect and remove duplicate records in SQL?
1️⃣4️⃣ Explain the difference between EXISTS and IN.
1️⃣5️⃣ What is the purpose of COALESCE()?

📌 Real-World SQL Scenarios

1️⃣6️⃣ How do you optimize a slow SQL query?
1️⃣7️⃣ What is indexing in SQL, and how does it improve performance?
1️⃣8️⃣ Write an SQL query to find customers who have placed more than 3 orders.
1️⃣9️⃣ How do you calculate the percentage of total sales for each category?
2️⃣0️⃣ What is the use of CASE statements in SQL?

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Learn SQL from basic to advanced level in 30 days

Week 1: SQL Basics

Day 1: Introduction to SQL and Relational Databases

Overview of SQL Syntax

Setting up a Database (MySQL, PostgreSQL, or SQL Server)

Day 2: Data Types (Numeric, String, Date, etc.)

Writing Basic SQL Queries:

SELECT, FROM

Day 3: WHERE Clause for Filtering Data

Using Logical Operators:

AND, OR, NOT

Day 4: Sorting Data: ORDER BY

Limiting Results: LIMIT and OFFSET

Understanding DISTINCT

Day 5: Aggregate Functions:

COUNT, SUM, AVG, MIN, MAX

Day 6: Grouping Data: GROUP BY and HAVING

Combining Filters with Aggregations

Day 7: Review Week 1 Topics with Hands-On Practice

Solve SQL Exercises on platforms like HackerRank, LeetCode, or W3Schools

Week 2: Intermediate SQL

Day 8: SQL JOINS:

INNER JOIN, LEFT JOIN

Day 9: SQL JOINS Continued: RIGHT JOIN, FULL OUTER JOIN, SELF JOIN

Day 10: Working with NULL Values

Using Conditional Logic with CASE Statements

Day 11: Subqueries: Simple Subqueries (Single-row and Multi-row)

Correlated Subqueries

Day 12: String Functions:

CONCAT, SUBSTRING, LENGTH, REPLACE

Day 13: Date and Time Functions: NOW, CURDATE, DATEDIFF, DATEADD

Day 14: Combining Results: UNION, UNION ALL, INTERSECT, EXCEPT

Review Week 2 Topics and Practice

Week 3: Advanced SQL

Day 15: Common Table Expressions (CTEs)

WITH Clauses and Recursive Queries

Day 16: Window Functions:

ROW_NUMBER, RANK, DENSE_RANK, NTILE

Day 17: More Window Functions:

LEAD, LAG, FIRST_VALUE, LAST_VALUE

Day 18: Creating and Managing Views

Temporary Tables and Table Variables

Day 19: Transactions and ACID Properties

Working with Indexes for Query Optimization

Day 20: Error Handling in SQL

Writing Dynamic SQL Queries

Day 21: Review Week 3 Topics with Complex Query Practice

Solve Intermediate to Advanced SQL Challenges

Week 4: Database Management and Advanced Applications

Day 22: Database Design and Normalization:

1NF, 2NF, 3NF

Day 23: Constraints in SQL:
PRIMARY KEY, FOREIGN KEY, UNIQUE, CHECK, DEFAULT

Day 24: Creating and Managing Indexes

Understanding Query Execution Plans

Day 25: Backup and Restore Strategies in SQL

Role-Based Permissions

Day 26: Pivoting and Unpivoting Data

Working with JSON and XML in SQL

Day 27: Writing Stored Procedures and Functions

Automating Processes with Triggers

Day 28: Integrating SQL with Other Tools (e.g., Python, Power BI, Tableau)

SQL in Big Data: Introduction to NoSQL

Day 29: Query Performance Tuning:

Tips and Tricks to Optimize SQL Queries

Day 30: Final Review of All Topics

Attempt SQL Projects or Case Studies (e.g., analyzing sales data, building a reporting dashboard)

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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🖥 SQL Mindmap

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SQL Programming Resources

SQL Cheatsheet

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SQL Programming Resources

✅ SQL Clauses Cheat Sheet! 🧠📘

1️⃣ SELECT – Pick the columns you want

SELECT name, age FROM students;

2️⃣ WHERE – Filter rows based on condition

SELECT * FROM orders WHERE status = 'delivered';

3️⃣ ORDER BY – Sort the results

SELECT * FROM products ORDER BY price DESC;

4️⃣ GROUP BY – Group rows for aggregation

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

5️⃣ HAVING – Filter groups after aggregation

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

6️⃣ LIMIT / TOP – Restrict number of rows
-- MySQL/PostgreSQL

SELECT * FROM sales LIMIT 10;

-- SQL Server

SELECT TOP 10 * FROM sales;

7️⃣ DISTINCT – Remove duplicates

SELECT DISTINCT city FROM customers;

8️⃣ BETWEEN – Filter within a range

SELECT * FROM invoices WHERE amount BETWEEN 100 AND 500;

9️⃣ IN – Match any from a list

SELECT * FROM users WHERE role IN ('admin', 'manager');

🔟 ALIAS (AS) – Rename columns or tables

SELECT name AS EmployeeName FROM employees;

💡 Tip: Combine clauses for powerful queries!

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SQL Programming Resources

20 medium-level SQL interview questions:

1. Write a SQL query to find the second-highest salary.
2. How would you optimize a slow SQL query?
3. What is the difference between INNER JOIN and OUTER JOIN?
4. Write a SQL query to find the top 3 departments with the highest average salary.
5. How do you handle duplicate rows in a SQL query?
6. Write a SQL query to find the employees who have the same name and work in the same department.
7. What is the difference between UNION and UNION ALL?
8. Write a SQL query to find the departments with no employees.
9. How do you use indexing to improve SQL query performance?
10. Write a SQL query to find the employees who have worked for more than 5 years.
11. What is the difference between SUBQUERY and JOIN?
12. Write a SQL query to find the top 2 products with the highest sales.
13. How do you use stored procedures to improve SQL query performance?
14. Write a SQL query to find the customers who have placed an order but have not made a payment.
15. What is the difference between GROUP BY and HAVING?
16. Write a SQL query to find the employees who work in the same department as their manager.
17. How do you use window functions to solve complex queries?
18. Write a SQL query to find the top 3 products with the highest average price.
19. What is the difference between TRUNCATE and DELETE?
20. Write a SQL query to find the employees who have not taken any leave in the last 6 months.

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SQL Programming Resources

SQL isn't easy!

It’s the powerful language that helps you manage and manipulate data in databases.

To truly master SQL, focus on these key areas:

0. Understanding the Basics: Get comfortable with SQL syntax, data types, and basic queries like SELECT, INSERT, UPDATE, and DELETE.

1. Mastering Data Retrieval: Learn advanced SELECT statements, including JOINs, GROUP BY, HAVING, and subqueries to retrieve complex datasets.

2. Working with Aggregation Functions: Use functions like COUNT(), SUM(), AVG(), MIN(), and MAX() to summarize and analyze data efficiently.

3. Optimizing Queries: Understand how to write efficient queries and use techniques like indexing and query execution plans for performance optimization.

4. Creating and Managing Databases: Master CREATE, ALTER, and DROP commands for building and maintaining database structures.

5. Understanding Constraints and Keys: Learn the importance of primary keys, foreign keys, unique constraints, and indexes for data integrity.

6. Advanced SQL Techniques: Dive into CASE statements, CTEs (Common Table Expressions), window functions, and stored procedures for more powerful querying.

7. Normalizing Data: Understand database normalization principles and how to design databases to avoid redundancy and ensure consistency.

8. Handling Transactions: Learn how to use BEGIN, COMMIT, and ROLLBACK to manage transactions and ensure data integrity.

9. Staying Updated with SQL Trends: The world of databases evolves—stay informed about new SQL functions, database management systems (DBMS), and best practices.

⏳ With practice, hands-on experience, and a thirst for learning, SQL will empower you to unlock the full potential of data!

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