Build Streaming Data Pipelines on Google Cloud

This course is part of multiple programs.

Instructor: Google Cloud Training

Access provided by Veriff

38,631 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

1,264 reviews

Intermediate level

Some related experience required

Flexible schedule

8 hours to complete

Learn at your own pace

69%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

1,264 reviews

Intermediate level

Some related experience required

Flexible schedule

8 hours to complete

Learn at your own pace

69%

Most learners liked this course

What you'll learn

Ingest and manage streaming data using Pub/Sub and Managed Service for Apache Kafka
Build and deploy streaming data pipelines with Dataflow
Implement streaming data solutions for real-time analytics and application serving with BigQuery and Bigtable

Skills you'll gain

Tools you'll learn

Apache Kafka

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

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There are 4 modules in this course

In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.

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.

What's included

1 plugin

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.

What's included

1 plugin

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.

What's included

4 assignments4 app items6 plugins

4 assignments Total 26 minutes

Quiz 1: Pub/Sub and Managed Service for Apache Kafka 6 minutes
Quiz 2: Dataflow 6 minutes
Quiz 3: BigQuery 8 minutes
Quiz 4: Bigtable 6 minutes

4 app items Total 330 minutes

Lab 1: Stream Data with Pipelines - Esports Use Case 90 minutes
Lab 2: Use Apache Beam and Bigtable to Enrich Esports DLC Data 90 minutes
Lab 3: Stream Esports Data with Pub/Sub and BigQuery 60 minutes
Lab: Monitor Esports Chat with Streamlit 90 minutes

6 plugins Total 90 minutes

Understanding the products 15 minutes
Architectural considerations for Pub/Sub and Managed Service for Apache Kafka 15 minutes
Accessing and completing labs 15 minutes
Dataflow: The processing powerhouse 15 minutes
BigQuery: The analytical engine 15 minutes
Bigtable: The solution for operational data 15 minutes

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.