YouTube Data Harvesting and Warehousing using SQL and Streamlit

Domain: Social Media

YouTube Data Harvesting and Warehousing is a project aimed at developing a user-friendly Streamlit application that leverages the power of the Google API to extract valuable information from YouTube channels. The extracted data is then migrated to a SQL data warehouse, and made accessible for analysis and exploration within the Streamlit app.

Step-by-Step Process:

Data Collection: Utilized the YouTube API to retrieve various data points including channel information, video details, playlists, and comments.

Data Storage: Transformed the retrieved YouTube data into pandas dataframes, created corresponding SQL tables, and used SQL scripts to insert the collected data into a SQL database, functioning as a data warehouse.

Data Analysis: Developed a Streamlit application to interact with the SQL database, enabling dynamic display and analysis of the harvested data.

Skill Takeaways:

Python scripting, data collection, API integration, data management using SQL, and creating interactive applications with Streamlit.