Dealerships
This project is a full-stack web application for a national car dealership, designed to centralize dealership reviews and provide a seamless user experience. It allows users to browse and filter dealerships by state, view reviews, and post their own feedback with sentiment analysis.
Project Overview
This project is a full-stack web application developed for Best Cars Dealership, a nationwide car dealership network in the United States. It centralizes dealership reviews and allows users to browse, filter, and evaluate dealerships across different states, with authenticated users able to post reviews enhanced by sentiment analysis. Built under a microservices-based architecture, the system integrates modules for user management, dealership and review handling, and natural language processing, ensuring scalability and efficient data flow. The application demonstrates the implementation of a multi-tier architecture that combines robust backend services with an interactive frontend for a seamless and reliable user experience.
👩💻 Role in the Project
As a Full-Stack Developer, I developed this application as part of the final project for the IBM Full Stack Software Developer course. I was responsible for implementing both frontend and backend components, including user authentication, dealership and review management, and the integration of the sentiment analysis service. I also contributed to the system’s architecture, database design, and deployment to ensure a functional and scalable solution.
🚑 Problem it Solves
Customers looking for car dealerships faced:
- A fragmented and untrustworthy review ecosystem.
- No easy way to compare dealerships in a specific area.
- Difficulty in quickly assessing the overall sentiment of reviews.
🛠️ Technologies Used
- Backend: Django (Python)
- Database: MongoDB
- Frontend: React, HTML5, CSS3, JavaScript
- NLP: Python NLTK for sentiment analysis.
⭐ Key Features
- User authentication for posting reviews.
- Filtering dealerships by state.
- Detailed dealership pages with reviews and ratings.
- Sentiment analysis of reviews (Positive, Negative, Neutral).
- Responsive design for mobile and desktop users.
📐 Development Methodology
Scrum methodology with a focus on user-centric design and iterative feature development.
✅ Results
The platform provides a much-needed service for car buyers, offering a reliable and easy-to-use tool for dealership research. The sentiment analysis feature has been particularly praised for its ability to provide quick insights.