ETL Pipeline Tutorial on GCP | End-to-End Data Pipeline Using Google Cloud Tools | Part 1

Video Description

Learn how to build a complete ETL (Extract, Transform, Load) pipeline on Google Cloud Platform (GCP) in this step-by-step tutorial! ETL pipelines in GCP: https://www.youtube.com/playlist?list=PL23BLRTuF74qh1Hbvb8v1yYRHK99F8R_I In this video, you'll get hands-on experience creating a fully functional data pipeline using powerful GCP tools like Cloud Storage, Cloud Functions, Cloud Composer, Dataflow, and BigQuery. Whether you're a beginner or looking to sharpen your cloud data engineering skills, this end-to-end walkthrough will give you practical insights into how modern data pipelines are designed and deployed in the cloud. 🔍 What You'll Learn: How to ingest data using Cloud Storage Real-time data transformation with Cloud Dataflow (Apache Beam) Automating workflows with Cloud Functions Loading transformed data into BigQuery for analytics Best practices for scalable and efficient pipelines on GCP 📌 Who Is This For? Aspiring Data Engineers Cloud Architects Developers working with data pipelines Anyone learning GCP for data projects 💡 Tools Used: Google Cloud Storage, Cloud composer, Dataflow, Cloud Functions, BigQuery, Looker Dashboard 📚 No prior experience with GCP? No worries! This tutorial walks you through every step in a beginner-friendly way. Github : https://github.com/srbsnkr/ETL-pipeline-Batch-processing-with-Airflow