Training Google Cloud

Training goals

code: G-BSDPGC | version: 3.0

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.

 

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

 

Audience

This course is designed for Data Engineers, Data Analysts and Data Architects.

Conspect Show list

  • Module 01
    • Topics
      • 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.
    • Objectives
      • Introduce the course learning objectives, and the scenario that will be used to bring hands on learning to building streaming data pipelines.
      • Describe the concept of streaming data pipelines, challenges associated with it, and the role of these pipelines within the data engineering process.
  • Module 02
    • Topics
      • 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.
    • Objectives
      • Learn about the various streaming use cases and their applications, including Streaming ETL, Streaming AI/ML, Streaming Application, and Reverse ETL.
      • Identify and describe common sampe architectures for streaming data including Streaming ETL, Streaming AI/ML, Streaming Application, and Reverse ETL.
  • Module 03
    • Topics
      • 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.
    • Objectives
      • Define messaging concepts
      • Use the console to create various PS and Kafka elements
      • Know when to use Pub/Sub or Managed Service for Apache Kafka
      • Describe the DF service and challenges with streaming data
      • Build and deploy a streaming pipeline
      • Explore various data ingestion methods into BQ
      • Learn about BigQuery continuous queries and using BigQuery ETL and reverse ETL
      • Configure Pub/Sub to BigQuery streaming
      • Architecting BigQuery into your streaming pipelines
      • Describe the big picture of data movement and interaction
      • Establish a streaming pipeline from Dataflow to Bigtable
      • Analyze the BT continuous data stream for trends using BQ
      • Synchronize the trends analysis back into the user-facing application
  • Module 04
    • Topics
      • 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.
    • Objectives
      • Summarize the course and what you learned about the various Google products, what you achieved throughout the course, and what you're enabled to do next as a result of completing the course.
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Additional information

Prerequisites
  • Proficiency in a common programming language like Python
  • A strong understanding of SQL
  • Data fundamentals like data modeling, formats, and ETL/ELT processes
  • Familiarity with the Google Cloud Platform (GCP)
Difficulty level
Duration 1 day
Certificate

The participants will obtain certificates signed by Google Cloud (course completion).
Trainer

Authorized Google Cloud Trainer

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