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Advanced SQL & Data Management A-Z 💻

🎉 Welcome to the Advanced SQL & Data Management A-Z repository! This repository contains comprehensive SQL scripts, projects, and best practices for mastering SQL and database management.

📚 What You Will Learn:

• SQL Basics: SELECT, WHERE, filtering, and basic functions.
• Intermediate SQL: JOINs, GROUP BY, subqueries, and string functions.
• Advanced SQL: Window functions, PIVOT/UNPIVOT, regular expressions (RegEx), and stored procedures.
• Employee Management Project: Custom database project demonstrating full database creation, normalization, and data manipulation.
• Final Projects: Real-world business projects, including data preparation for machine learning (ML).

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🛠️ Tools & Requirements:

• MySQL Workbench (for MySQL projects)
• PostgreSQL and PgAdmin 4 (optional)
• Basic knowledge of SQL (ideal but not required)

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📂 Project Structure:

Section 1: SQL Basics

Learn the basics of SQL including SELECT, WHERE, and basic filtering.

• DDL(S1).sql — Data Definition Language.
• DML+DQL(S1).sql — Data Manipulation and Query Languages.

Section 2: Intermediate SQL

Dive into JOINs, GROUP BY, HAVING, subqueries, and string functions.

• Aggregate_Functions(S2).sql — Working with aggregate functions such as SUM(), AVG(), etc.
• ReGeXP_Practice(S2).sql — Regular expressions and pattern matching.
• GROUP_BY_Practice_+_Comments(S2).sql — Grouping data with GROUP BY.
• SubQuery(S2).sql — Example of subqueries.
• SELECT_Disign(S2).sql — Advanced select query examples.
• String_Functions(S2).sql — Functions for string manipulation.

Section 3: Advanced SQL

Explore complex SQL topics including window functions, PIVOT, and query optimization.

• Window_Functions(S3).sql — Using window functions for advanced data analysis.
• PIVOT_in_MYSQL(S3).sql — Pivoting data in SQL.
• UNPIVOT_in_MYSQL(S3).sql — Unpivoting data in SQL.
• Indexes(S3).sql — Creating and using indexes for optimization.
• Query_Optimization_Techniques(S3).sql — Tips for optimizing SQL queries.
• Stored_Procedures(S3).sql — Creating and using stored procedures.
• View(S3).sql — Working with SQL views.

Section 4: Employee Management Project

This section demonstrates the full development of an Employee Management Database. The project includes database creation, normalization checks, data manipulation practices, and full-featured database management.

• Scrip_Employee_Management_Database.sql — Initial structure of the Employee Management database.
• Scrip_Employee_Management_Check_Normalization_Forms.sql — Demonstration of normalization forms (1NF, 2NF, 3NF).
• Scrip_Employee_Management_DML_Practice_Insert.sql — Practical examples of INSERT, UPDATE, and DELETE for the Employee Management database.
• Scrip_Employee_Management_Full_Features.sql — Full-featured database management script with validation and stored procedures.

Section 5: Final Projects

Real-world projects, including data preparation for machine learning.

• Final_Project_Script_part_1(S1).sql — First part of the final project scripts, involving core SQL concepts.
• Final_Project_Script_part_2(S2).sql — Second part of the final project, including intermediate SQL techniques.
• Final_Project_Script_part_3(S3).sql — Third part of the project, using advanced SQL concepts.
• Final_Project_Script_data_prep_for_ML(S4).sql — Final part focusing on preparing the data for machine learning.

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ER Diagrams:

This folder contains ER diagrams that visually represent the database structures used in various projects.

• ER_Diagram_Classsicmodels.mwb — Classic Models database diagram.
• ER_Diagram_Employee_Management.mwb — Employee Management database diagram.

You can open these diagrams using MySQL Workbench to view the structure and relationships between tables in each database.

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ADVANCED SQL SCRIPTS (ORIGINAL):

This folder contains additional advanced SQL scripts that demonstrate complex concepts and techniques. These scripts are organized by theme and can be useful for deepening your understanding of SQL:

• COMMON TABLE EXPRESSION (CTE).sql — Demonstrates the use of CTEs in SQL.
• Re-answering_Business_Questions.sql — Answering complex business questions using SQL.
• ReDDL_DML_TCL_DQL_DCL.sql — Covers DDL, DML, TCL, and DCL practices.
• Understanding_JOINS.sql — Explains various types of SQL JOINs with examples.
• Window_CTE_Views_StoredProc.sql — A comprehensive script combining window functions, CTEs, views, and stored procedures.

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🛠️ Setup & Installation:

1. Clone this repository:
   git clone https://github.com/evgeniimatveev/Advanced_SQL_Data_Management_A-Z.git
2. Open MySQL Workbench or your preferred SQL client.
3. Navigate to the relevant project section, and run the SQL scripts in your database.

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🎓 Why Master SQL?

SQL is a critical skill for anyone involved in data analysis, database management, or data science. This repository will help you:

• Analyze and manipulate large datasets efficiently.
• Design and manage scalable databases.
• Prepare data for advanced analytics, including machine learning.

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🏆 Contributing

We welcome contributions to improve this repository! Here’s how you can get involved:

1. Fork the repository.
2. Create a new branch: git checkout -b feature/new-feature.
3. Make changes and commit: git commit -m 'Add new feature'.
4. Push to the branch: git push origin feature/new-feature.
5. Submit a pull request.

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Happy coding! 🚀