Linq Technology Intern Take-Home Project

Welcome to my submission for the Linq Technology Intern Take-Home Assessment! This project demonstrates how we can collect, process, and visualize live data using Python, MongoDB, and Streamlit.

What This Project Does

-Simulates real-time data for 6 different categories like Food, Health, Travel, etc. -Stores the data in a MongoDB database using an automated ingestion script. -Displays a live dashboard that auto-refreshes every 5 seconds to show the latest stats. -Visualizes trends of selected categories from the last 1 hour.

Technologies Used

Python MongoDB (via Docker) Streamlit (for dashboard) Docker & Docker Compose

Project Structure

File Description data_ingest.py -> Script that generates and inserts mock data into MongoDB. visualization.py -> Streamlit app that shows live visual analytics. docker-compose.yml -> Sets up MongoDB and runs both scripts in containers. datastore-setup.md -> Explains how MongoDB is set up using Docker. data-ingestion.md -> Explains how data is created and stored. visualization.md -> Describes how the dashboard works and what it shows. dashboard.png -> Screenshot of the live dashboard UI.

How to Run It

Make sure Docker is installed, then run: docker-compose up Our dashboard will be available at: http://localhost:8501

Submission Info

GitHub Repo shared with: patrick@linqapp.com careers@linqapp.com

Subject: Linq Intern Take-Home Submission