SQL for Data Analysis

📖 Overview

This repository contains my SQL practice and business-oriented query solutions developed while learning MySQL for Data Analysis.

The repository demonstrates SQL concepts ranging from database creation to advanced analytical queries used for solving real-world business problems.

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🚀 Skills Demonstrated

• Database Design (DDL)
• Data Manipulation (DML)
• Constraints
• Aggregate Functions
• GROUP BY & HAVING
• Joins
• Subqueries
• Correlated Subqueries
• EXISTS, ANY & ALL
• Window Functions
• Views
• String Functions
• Date Functions
• NULL Handling
• CASE Statements
• Business-Oriented SQL Analysis

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📂 Repository Structure

SQL-for-Data-Analysis/
│
├── README.md
├── SQL/
│   └── SQL_for_Data_Analysis.sql
│
└── Images/

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📚 SQL Topics Covered

Database Design

• CREATE TABLE
• ALTER TABLE
• DROP TABLE

Data Manipulation

• INSERT
• UPDATE
• DELETE

SQL Queries

• SELECT
• WHERE
• ORDER BY
• GROUP BY
• HAVING

Joins

• INNER JOIN
• LEFT JOIN
• SELF JOIN

Aggregate Functions

• COUNT()
• SUM()
• AVG()
• MIN()
• MAX()

Subqueries

• Scalar Subqueries
• Correlated Subqueries
• EXISTS
• ANY
• ALL

Window Functions

• ROW_NUMBER()
• RANK()
• DENSE_RANK()
• LAG()
• LEAD()
• FIRST_VALUE()
• LAST_VALUE()

Views

• CREATE VIEW
• Business Reporting Views

Functions

• String Functions
• Date Functions
• NULL Functions
• CASE Expressions

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🎯 Objective

The objective of this repository is to strengthen SQL problem-solving skills and demonstrate practical experience in writing business-oriented SQL queries for data analysis.

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🛠 Tools

• MySQL
• MySQL Workbench
• Git
• GitHub

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👨‍💻 Author

M Manoj Kumar