MySQL Restaurant Database & Python Analytics System

This project combines a MySQL backend with Python analytics through MySQL Connector/Python to track operations from bookings to sales. Developed during Meta's Data Engineering course, the solution features 13 relational tables, connection pooling for performance, and automated Matplotlib visualizations.

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Implementation Process

1. Database Architecture

• Created the ER diagram.
• Set up a MySQL instance in MySQL Workbench.
• Implemented the database schema.

2. Database Connection

• Established database connectivity using mysql-connector-python.
• Configured secure connection parameters.

db_config = {
  'host': 'localhost',
  'user': '-------',  # Insert your username
  'password': '--------',  # Insert your password
  'database': 'restaurant_db'
}

# Connection handling with error management
try:
  conn = mysql.connector.connect(**db_config)
  cursor = conn.cursor()
  print("Successfully connected to database")
except mysql.connector.Error as err:
  print(f"Database connection failed: {err}")
  exit()

3. Query Execution

• Executed queries to insert sample data.
• Verified data integrity by counting records across tables.

4. Data Analysis

Generated visualizations using matplotlib.

See more of the data analysis in the restaurant-analysis.ipynb file.

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Built With

• MySQL Workbench
• MySQL Connector/Python
• Python
• Matplotlib

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How to Run the Project

1. Clone the repository:

   git clone https://github.com/larisanti/restaurant-db.git
   cd restaurant-db

2. Install the required Python libraries:

   pip install mysql-connector-python matplotlib

3. Set up the MySQL database:

   • Import the provided .sql file to create and populate the database.
   • Update your MySQL credentials for the database connection.

License

This project is licensed under the MIT License. For more details, see the LICENSE file.