Build a data pipeline on Google Cloud using an event-driven architecture, leveraging GCS, Cloud Run functions, and BigQuery. Explore both VM and Composer options for Airflow management, and utilize Logging & Monitoring for pipeline health. Discover how SQL-based BigQuery ML can be used for initial ML implementation in specific scenarios.

Project contains a flask app that queries google big query storage (holds two arima models and etl of NYT Covid19 dataset) and returns latest cases/deaths stats for US and territories, along with prediction for cases/deaths 30 days out.

Streamlit dashboard for student analytics powered by Google BigQuery. Features ML-driven dropout prediction (Random Forest), student clustering (K-means), and satisfaction analysis (Boosted Trees) with interactive visualizations and CSV export capabilities. Live demo available at the provided link.