📊 ETL Multi-CSV to SQLite with Summary Export

This project performs a simple but production-ready ETL pipeline that processes multiple CSV sales files, transforms the data, stores it in a SQLite database, and exports a monthly summary.

📌 Project Highlights

🚀 Features

• Load multiple CSV files from a folder
• Clean and convert date columns
• Extract and add a month column
• Save the full dataset to a SQLite database (sales_data.db)
• Generate a monthly and category sales summary to CSV (summary.csv)
• Track every ETL step using Python's built-in logging module

📁 Project Structure

etl_multi_csv_project/
├── data/                # Raw input CSV files
├── etl/                 # All ETL scripts (load, process, save, export)
├── output/              # Generated database, summary, and log files
├── main.py              # Main script to run the ETL pipeline
├── requirements.txt     # Python dependencies
└── README.md            # Project documentation

▶️ How to Run

1. Install dependencies:

pip install -r requirements.txt

2. Run the pipeline:

python main.py

🧪 Output

• sales_data.db — cleaned and combined data saved to SQLite
• summary.csv — total sales per month and category
• etl.log — ETL process logs

🧱 Built With

• pandas
• SQLAlchemy
• logging (built-in)

👨‍💻 Author

Khairu Ikramendra
Available for freelance dashboard & data analytics projects.
Let’s connect on Linkedin or explore more on Upwork !

📄 License

MIT License — feel free to use and modify for your own projects.

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This project is suitable for practicing ETL, documenting data projects, and building the foundation for automated dashboards and reports.