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https://github.com/arij01/datahub-frontend

This repository contains the Angular-based frontend for a state-of-the-art Data Catalog SaaS application, providing an intuitive and dynamic user interface for seamless data governance.
https://github.com/arij01/datahub-frontend

angular css html microservices-architecture nodejs saas typ

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This repository contains the Angular-based frontend for a state-of-the-art Data Catalog SaaS application, providing an intuitive and dynamic user interface for seamless data governance.

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## Data Catalog SaaS Frontend

This repository contains the frontend for a state-of-the-art Data Catalog Software as a Service (SaaS) application. Designed to streamline data governance for French enterprises, our solution offers an intuitive and dynamic user interface, seamless API integrations, and real-time data quality visualizations. Built with Angular, it ensures a responsive and engaging user experience. Join us in pioneering excellence in data management and governance!

## Table of Contents
- [Introduction](#introduction)
- [Features](#features)
- [Tech Stack](#tech-stack)
- [Architecture](#architecture)
- [Acknowledgements](#acknowledgements)
## Introduction
In today's data-driven world, managing vast amounts of data efficiently is crucial. Our Data Catalog SaaS application addresses the challenges organizations face in maintaining data integrity, security, and usability. It provides businesses with unparalleled visibility and control over their data assets, fostering trust, transparency, and collaboration.
![image](https://github.com/user-attachments/assets/d785d765-b231-4ec7-a42a-8757585e7a2d)

## Features
**Centralized Metadata Management**: Easily catalog, categorize, and trace your data.
**User-friendly Interface**: Intuitive and dynamic UI for seamless data interaction.
**Automation**: Automatic metadata extraction and data profiling.
**API Integration**: Seamless integration with external systems via robust APIs.
Data Quality Monitoring: Utilize machine learning models for data quality assessment.

## Tech Stack
**Backend**: Java, Spring Boot
**Frontend**: Angular
**Database**: MongoDB, MySQL
**Containerization**: Docker
**Machine Learning**: Various ML libraries for data analysis and quality monitoring
## Architecture
The backend is built on a microservices architecture using Spring Boot, ensuring scalability and robustness. Angular powers the frontend, delivering a responsive and engaging user experience. Docker is used for containerization, facilitating consistent deployment across different environments.

## Logical Architecture
![spring-boot-architecture2](https://github.com/user-attachments/assets/2d8b8e4a-2c34-4703-b014-3a655cec1cfd)
![image](https://github.com/user-attachments/assets/f08fb98f-58d2-4143-8c88-9702d1355823)

## Technical Architecture
![image](https://github.com/user-attachments/assets/b83e4109-0eab-40e1-afe1-cdd3ff23d2e6)

## Acknowledgements
This project is developed by:

- Arij M’hiri
- Yacine Tazarki
- Rahma Farhat
- Haithem Meddeb
- Med Ali Belhadj

Supervised by Rihab Idoudi and Thouraya Louati.