CONTENT
Designing data processing systemsIn this track, the focus will be on what it takes to become a Google Cloud Data Engineer, navigating the Google Cloud platform, building data structures, and planning data pipelines.
Courses:
- GCP Data Engineer Pro: Becoming a Google Cloud Data Engineer
- GCP Data Engineer Pro: Navigating the Google Cloud Platform
- GCP Data Engineer Pro: Building Robust Data Structures
- GCP Data Engineer Pro: Creating a Pipeline of Services
Ingesting and processing the data
In this track, the focus will be on unstructured and structured data, data storage, and BigQuery data warehouse.
Courses:
- GCP Data Engineer Pro: Google Cloud Unstructured Data
- GCP Data Engineer Pro: Google Cloud OLTP Structured Data Storage
- GCP Data Engineer Pro: Google Cloud Semi-structured Data
- GCP Data Engineer Pro: BigQuery Data Warehouse
Storing the data
In this track, the focus will be on using Google data stream, messaging, dataset processing, and exploring machine learning and AI with Google.
Courses:
- GCP Data Engineer Pro: Messaging with Pub/Sub
- GCP Data Engineer Pro: Using Google DataStream
- GCP Data Engineer Pro: Dataset Processing
- GCP Data Engineer Pro: Google Machine Learning and AI
Preparing and using data for analysis
In this track, the focus will be on optimizing, monitoring, and troubleshooting data warehouses, and you will also explore data migrations.
Courses:
- GCP Data Engineer Pro: Optimizing a Google Data Warehouse
- GCP Data Engineer Pro: Monitoring and Troubleshooting Data Warehouses
- GCP Data Engineer Pro: Data Migrations