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Python scripting, data collection, MongoDB, Streamlit, API integration, and data management with SQL and MongoDB are the main areas of interest for this project. The project's objective is to create a Streamlit application that enables users to view and examine data from different YouTube channels.

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Logambal05/YouTube-Data-Harvesting-and-Warehousing

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YouTube-Data-Harvesting-and-Warehousing

The project's primary areas of interest are Python scripting, data collection, MongoDB, Streamlit, API integration, and data management with MongoDB and SQL. The area of social media data analysis is covered. Project overview The project's goal is to develop a Streamlit app that lets users access and analyse data from various YouTube channels. It has the following essential characteristics:

  1. Ability to input a YouTube channel ID and retrieve relevant data (Channel name, subscribers, total video count, playlist ID, video ID, likes, dislikes, comments of each video) using the Google API.
  2. Possibility of data lake storage in a MongoDB database.
  3. The ability to click a button to quickly gather data from various YouTube channels and store it in the data lake.
  4. There is an option to choose a channel name and move the data contained in it from the data lake to a SQL database as tables.
  5. the capacity to perform various types of searches on the SQL database, including joining tables to get channel

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Python scripting, data collection, MongoDB, Streamlit, API integration, and data management with SQL and MongoDB are the main areas of interest for this project. The project's objective is to create a Streamlit application that enables users to view and examine data from different YouTube channels.

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