Build a complete real-time traffic analytics project on Databricks and GCP with PySpark, Medallion architecture, Auto Loader, and CI/CD.
Language: English | Duration: 19 lectures (5h 35m) | Size: 2.64 GB Last updated: 9/2025
Want to master Databricks on Google Cloud through a practical, real-world project? This course gives you hands-on experience with a highly sought-after data engineering skill: building scalable data pipelines with Databricks, PySpark, and Medallion architecture.
Take on the role of a state transportation agency analyzing road traffic data. Learn to manage infrastructure datasets, process sensor data, and generate insights such as the busiest regions, electric vehicle adoption trends, and yearly traffic patterns.
Start by setting up Databricks on GCP, creating storage buckets, external locations, and Unity Catalog. Then work through the Bronze, Silver, and Gold layers with Auto Loader and Structured Streaming.
What you'll learn:
- Set up Databricks on Google Cloud, including a workspace, Unity Catalog, clusters, and GCS integration.
- Implement Medallion architecture with Bronze, Silver, and Gold layers using PySpark and Databricks Auto Loader for structured streaming.
- Build end-to-end ETL pipelines that load raw data, transform it, and generate analytics-ready Gold tables.
- Automate workflows and orchestrate pipelines in Databricks with parameterized jobs and file-arrival triggers.
- Integrate GitHub with Databricks and promote code through Dev, UAT, and PRD environments using pull requests.
- Analyze real road traffic data to inform decisions about busy regions, EV trends, and annual traffic volumes.
Requirements:
- Basic knowledge of SQL, PySpark, and database concepts.
- An interest in learning through a real project. Previous Databricks experience is not required.
Who this course is for:
- Aspiring data engineers who want practical experience for job interviews.
- Cloud professionals working with GCP, Azure, or AWS who want to add Databricks and Medallion architecture to their skills.
- Students and new data engineers who want a complete hands-on portfolio project.
Download links:
MEGA
MEDIAFIRE
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