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Part 2 - https://youtu.be/kxV4_xDchCc Source Code - https://github.com/vishal-bulbule/etl-pipeline-datafusion-airflow Creating an ETL Data Pipeline on Google Cloud with Cloud Data Fusion & Airflow Explore the magic of building an ETL pipeline in Google Cloud with this comprehensive tutorial. Learn how to craft a seamless process for extracting, transforming, and loading data into BigQuery, then visualize it effortlessly in Looker Studio. Step 1: Begin by extracting dummy employee data using the Python Faker library, seamlessly storing it in a designated Google Cloud Storage (GCS) bucket. Step 2: Dive into the creation of a Cloud Fusion instance, setting up the groundwork for your data pipeline journey. Step 3: Unveil the magic of Data Fusion as you craft a robust pipeline. Witness the transformation of data while ensuring sensitive information remains masked, ultimately loading it into BigQuery for further analysis. Step 4: Elevate your data visualization game as you harness the power of Looker Studio, bringing your insights to life in a visually compelling manner. Join me on this illuminating journey through the intricacies of ETL pipelines, empowering you to master data orchestration and visualization in the Google Cloud ecosystem. Playlists Google Agent Development Kit (ADK) https://www.youtube.com/playlist?list=PLLrA_pU9-Gz2HwepRUVpq1TEPuYWo_fSi Learn Airflow https://www.youtube.com/playlist?list=PLLrA_pU9-Gz3i8qw6yakrfJzx75W_vVaH Learn Google Cloud in 2025 https://youtube.com/playlist?list=PLLrA_pU9-Gz2OnBoICkewd9-Fc9Mi0nm7&si=8kkB3ct5wDHCMkoi Data Engineering Hands-on Projects https://www.youtube.com/playlist?list=PLLrA_pU9-Gz2DaQDcY5g9aYczmipBQ_Ek Looking to get in touch? Drop me a line at [email protected] Linkedin https://www.linkedin.com/in/vishal-bulbule/ Medium Blog https://medium.com/@VishalBulbule Github Source Code https://github.com/vishal-bulbule 💬 Join Our WhatsApp Community for Discussions and Updates: https://chat.whatsapp.com/I7omzvh5BZrILaBCPL8pPq #googlecloud #gcp #airflow #dataengineeringessentials #dataengineering #bigquery #dataengineeringprojects
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