Data Mining algorithms for IDMW632C course at IIIT Allahabad, 6th semester
This repository hosts a project that enables efficient YouTube data extraction, storage, and analysis. It leverages SQL, MongoDB, and Streamlit to develop a user-friendly application for collecting and visualizing data from YouTube channels.
Warehauser is an open source warehouse management backend system written in Python using the Django library. It is designed to be simple to understand but powerful enough to handle the most complex business logic.
This project utilises the features of the YouTube Data API to retrieve data from YouTube channels, playlists, videos, and comments and store it in a data lake. It also interacts with a PostgreSQL database to store the retrieved data.
Comprehensive YouTube Data Harvesting and Analysis Project: Utilized Python's API for data extraction, enriched by SQL queries, and stored in MongoDB. Employed Streamlit for streamlined visualization, enabling efficient data collection, storage, and insightful analysis.
Warehousing and distribution
This is a collections of scripts I have been writing to aid QA with investigating and logging issues flagged by the package sortation system.
Add a description, image, and links to the warehousing topic page so that developers can more easily learn about it.
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