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Build Streaming Data Pipelines on Google Cloud

IntermediateSkill Level
Updated 05/2026
Design and operate batch data pipelines on Google Cloud using Dataflow, Serverless Spark, Cloud Composer, and data validation techniques.
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3 hr 32 min
25 Exercises
1,450 XP
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Course Description

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.

Prerequisites

There are no prerequisites for this course
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.
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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.
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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.
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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.
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Build Streaming Data Pipelines on Google Cloud
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