Después de hacer estos cursos, me siento seguro creando visualizaciones y cuadros de mando profesionales
Shoebur RahmanEspecialista en adquisiciones, Giz Bangladesh
Descripción del curso
Explore streaming data pipeline architectures on Google Cloud. This course covers Pub/Sub, Managed Service for Apache Kafka, Dataflow, and BigQuery for real-time data processing. You'll learn architectural considerations and apply your knowledge through an esports streaming use case.
Requisitos previos
Este curso no tiene requisitos previos
Programa de formación
Esquema del curso
1
Course introduction
This module introduces the fundamentals of building streaming data pipelines on Google Cloud, providing a foundation for the entire course. It begins by outlining the course's overall learning objectives and introducing a practical, hands-on scenario that will be used throughout the content and labs to make the concepts tangible.
2
Streaming use cases and reference architectures
This module provides an introduction to streaming data use cases and architectures. You will learn about the applications and common architectural patterns for real-time data processing across four key scenarios: Streaming ETL, Streaming AI/ML, Streaming Application, and Reverse ETL.
3
Product deep dives
This module provides a comprehensive overview of building streaming data pipelines on Google Cloud, covering the core services for messaging, processing, and analysis. It's designed to give you a hands-on understanding of how these components work together in a cohesive, real-time architecture.
4
Key takeaways
This module provides a comprehensive wrap-up of the course, summarizing the key concepts you've learned for building resilient and robust streaming data pipelines on Google Cloud.
R
Build Streaming Data Pipelines on Google Cloud
Curso
completado
