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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.

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YouTube Data Harvesting and Warhousing

  • This project aims to harvest data from YouTube using Python scripting and store it in a NoSQL (MongoDB) database as a data lake.

  • The harvested data can then be fetched from the NoSQL database and migrated to a SQL (PostgreSQL) database for further analysis. Additionally, SQL queries can be executed on the postgreSQL database to answer specific questions related to the uploaded channel information.

Prerequisites Before running the scripts, make sure you have the following dependencies installed:

Python 3.9 or later

MongoDB

PostgreSQL

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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.

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python windows youtube query sql mongodb integration nosql scripts youtube-api python3 warehouse rdbms nosql-database youtube-channel cleaning warehousing streamlit postgreq python-sql-integration

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