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SQL-Databases (with Python Integration)

This repository contains structured SQL database projects, ranging from basic CRUD operations to advanced SQL concepts with Python integration via Jupyter Notebooks.

📌 Overview

This collection includes a variety of SQL database projects implemented using MySQL, SQLite, and IBM DB2. Python is used to query and manipulate databases within Jupyter Notebooks.

🔹 Key Topics Covered:

  • CRUD Operations (Create, Read, Update, Delete)
  • ACID Properties (Atomicity, Consistency, Isolation, Durability)
  • Database Design (Foreign Keys, Primary Keys, Indexing)
  • Advanced SQL Concepts:
    • Common Table Expressions (CTEs)
    • Joins (INNER, LEFT, RIGHT, FULL)
    • Subqueries & Nested Queries
    • Window Functions (RANK, ROW_NUMBER, LAG, LEAD, etc.)
    • Stored Procedures & Functions
    • Triggers & Views
    • Transactions & Rollback Mechanisms
    • Case Statements & Conditional Logic

📂 Project Structure

Below are the SQL database projects included in this repository:

🔹 Project Name 📂 Database Type ⚡ Status
Bank ATM Transaction MySQL ✅ Completed
Chicago Database MySQL ✅ Completed
Harley Davidson Museum Database MySQL ✅ Completed
LV Hospital Database MySQL ✅ Completed
Pet Company Database MySQL ✅ Completed
Riple Employees Database MySQL ✅ Completed
Delite Futures Database MySQL ✅ Completed
SQL with Python (IBM DB2, SQLite) IBM DB2, SQLite ✅ Completed

🛠 Technology Stack

Tool/Technology Purpose
MySQL Relational Database Management
SQLite Lightweight Database Engine
IBM DB2 Enterprise Database Solution
Python Data Querying & Manipulation
Jupyter Notebook Interactive SQL Execution

🚀 How to Use

  1. Clone the Repository: 
    git clone https://github.com/Tolumie/SQL-DATABASE-Projects.git
  2. Navigate into the Folder: 
    cd SQL-DATABASE-Projects
  3. Open Jupyter Notebook (For Python + SQL Integration Projects): 
    jupyter notebook
  4. Load the SQL files into your database of choice (MySQL, SQLite, IBM DB2)

📜 Contributions & Issues

  • Feel free to fork the repo and submit pull requests.
  • If you find any issues, please report them via GitHub Issues.

📧 Contact

For any inquiries, reach out via GitHub. 🚀

🔹 Happy Querying! 🛠️📊