AI-Powered Data Analysis Platform with Flask Microservices
Analytica Hub is a scalable, AI-powered data analytics platform built with Django, Flask, Redis, Celery, and Docker. It enables users to upload large CSV files (up to lakhs of rows), perform Exploratory Data Analysis (EDA), and clean data automatically using a single-click AI-based process. The platform features a “Chat with CSV” interface powered by natural language, capable of returning both text-based and visual insights.
AI functionalities like EDA, data cleaning, and natural language querying are handled through a Flask microservice that communicates with the Django app via internal REST APIs. Redis ensures real-time consistency and avoids frequent database queries by maintaining intermediate states in memory.
- 📂 Upload and process large CSV files (lakhs of rows supported)
- 📊 AI-powered Exploratory Data Analysis (EDA)
- 🧹 One-click AI-based Data Cleaning
- 💬 “Chat with CSV” using natural language queries
- Supports textual and graph-based responses
- 🔄 Real-time undo/redo functionality using Redis
- 🧠 Flask microservice for scalable and isolated AI processing
- 🐳 Fully containerized using Docker
- 🏗️ Efficient server-to-server communication for microservices
- ⚡ Redis-powered in-memory consistency with reduced DB hits
- Django (Core App) handles user management, CSV upload, task orchestration, and frontend (if any).
- Flask Microservice handles AI-heavy tasks: EDA, data cleaning, and natural language query processing.
- Redis maintains state after every operation, allowing low-level consistency and real-time undo/redo.
- Celery runs background tasks like calling the Flask microservice and storing processed CSVs.
- Docker ensures portability and isolation of services via separate containers for Django, Flask, Redis, and Celery workers.
- Core Backend: Django (no DRF)
- AI Microservice: Flask
- Task Queue: Celery
- In-Memory Store: Redis
- Containerization: Docker, Docker Compose
- AI & Data Tools: Pandas, Numpy, Matplotlib, Scikit-learn, Custom NLP
- Communication: Internal REST API (server-to-server)
git clone https://github.com/your-username/analytica-hub.git
cd analytica-hub