Backend Data Management System for Structured Operational Datasets
DataFleet is a backend system designed to securely store, process, and analyze structured operational data in the shipyard domain.
The project focuses on backend architecture, relational database design, and scalable data processing workflows. It provides a modular Django-based structure that enables efficient data manipulation, statistical analysis, and future system expansion.
This project demonstrates backend engineering practices, database schema design, and structured API development using Python and Django.
- Python
- Django
- MySQL
- GNU/Linux (development environment)
- Relational database schema optimized for structured datasets
- Secure CRUD operations for data manipulation
- RESTful backend architecture
- Data validation and integrity enforcement
- Modular Django app structure for maintainability
- Statistical data processing modules
- Designed for scalability and future feature expansion
DataFleet follows a layered backend structure:
- Models Layer → Relational schema definition and data relationships
- API / View Layer → Request handling and data processing
- Database Layer → MySQL relational storage
- Business Logic Layer → Statistical and operational processing
The architecture is structured to allow future implementation of:
- Authentication and authorization systems
- Role-based access control
- Reporting modules
- Extended analytics features
git clone https://github.com/Killerbrine06/DataFleet.git
cd DataFleet
python -m venv venv
Activate the environment:
Linux / macOS
source venv/bin/activate
Windows
venv\Scripts\activate
pip install -r dependencies.txt
Set up your database credentials and required environment variables before running the project.
python manage.py migrate
python manage.py runserver
The application will start locally and can be accessed via your browser.
- Structured operational data storage
- Statistical data querying and processing
- Backend foundation for domain-specific management systems
- Scalable data handling for analytics workflows
This project is currently under active development.
Core backend architecture and database schema are implemented. Additional features and optimizations are planned to further expand analytical and system capabilities.
Vlad George Cacenschi
Python Backend & Automation Developer
This project is intended for educational and portfolio purposes.