Sasta Bazar is a comprehensive Android application designed for shopping clothing items, specifically for girls. The platform offers a diverse selection of affordable and stylish dresses. In addition to the user-facing shopping app, the project includes an admin application for efficient product management and uploads by administrators.
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Product Catalog: Offers a wide range of dresses , categorized into various sections like tops, bottoms, dresses, and more. Users can browse through the catalog to explore different clothing options.
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User Authentication: Supports user authentication and account management functionalities using Firebase Authentication. Users can create accounts, log in securely, and manage their profiles.
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Shopping Cart: Enables users to add products to their shopping carts, review their selections, and proceed to checkout. The shopping cart feature allows for easy management of selected items before making a purchase.
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Product Details: Provides detailed information about each product, including its name, price, description, available sizes, colors, and images. Users can view product details to make informed purchasing decisions
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Admin Panel for Product Management: Includes an admin application with functionalities for uploading, managing, and updating product listings, enhancing the platform's scalability and flexibility.
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Responsive Design: Ensures compatibility across various screen sizes and devices, providing a seamless shopping experience on smartphones and tablets.
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User-Friendly Interface: Offers an intuitive and visually appealing user interface in both the shopping and admin apps, optimizing the user experience for customers and administrators alike.
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Firebase Integration: tegrates with Firebase for backend services, including database management, user authentication, cloud storage, and analytics. Firebase integration enhances the app's functionality, security, and performance
- Programming Language: Kotlin
- IDE: Android Studio
- UI Design: XML
- Database Firebase
This project is the result of individual efforts.
Enhanced Search Functionality: Implement an advanced search feature with filters such as size, color, price range, and brand to help users quickly find specific products.
Personalized Recommendations: Utilize machine learning algorithms to analyze user preferences and browsing history, providing personalized product recommendations tailored to each user's taste.
Rating and Review System: Enable customers to rate and review products, providing valuable feedback to other shoppers and improving trust and transparency in the shopping experience.
Hello, I'm Raghavendra Kumar Sharma, currently pursuing a Master's in Computer Application from NIT Jamshedpur. My passion lies in Android development, with a strong foundation in Data Structures and Algorithms (DSA).