Po ukończeniu tych kursów czuję się pewnie w tworzeniu profesjonalnych wizualizacji i pulpitów nawigacyjnych
Shoebur RahmanSpecjalista ds. zakupów, Giz Bangladesh
Opis kursu
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.
Wymagania wstępne
Ten kurs nie ma żadnych wymagań wstępnych
Program nauczania
Plan kursu
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
Kurs
ukończony
