🚀 Built a complete ETL pipeline using Dataproc + PySpark on GCP!

📌 Video Description In this video, we will build a real-world Data Engineering pipeline using Google Cloud Platform (GCP). 🔹 Services Used: • Cloud Storage (GCS) • Dataproc • PySpark • BigQuery 🔹 What You’ll Learn: ✅ How to create a Dataproc cluster ✅ Upload CSV files to Cloud Storage ✅ Read CSV files using PySpark ✅ Transform and process data ✅ Load data into BigQuery tables ✅ End-to-end ETL workflow on GCP This tutorial is beginner-friendly and useful for anyone preparing for Data Engineering interviews or learning cloud-based big data processing. 📌 Technologies Covered: • GCP Dataproc • Apache Spark • PySpark • Google BigQuery • Cloud Storage 👍 Don’t forget to Like, Share & Subscribe for more Data Engineering and GCP content! #GCP #Dataproc #PySpark #BigQuery #CloudStorage #DataEngineering #ETL #ApacheSpark #GoogleCloud #DataPipeline