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Introduction to Data Engineering on Google Cloud

Name: Introduction to Data Engineering on Google Cloud
Availability: InStock
Rating: 4.6 (5878 reviews)

In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.

4.6 out of 5 rating
Last updated : 23/07/2026
English

Available as Instructor Led Training, Live Online & In Person at your Offices or Ours.

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Duration:

8.00 hours

6.5 CPD hours

Overview:

Description:

Course Outline:

Module 1 - Data Engineering Tasks and Components

Topics:

- The role of a data engineer
- Data sources versus data sinks
- Data formats
- Storage solution options on Google Cloud
- Metadata management options on Google Cloud
- Sharing datasets using Analytics Hub
Objectives:

- Explain the role of a data engineer.
- Understand the differences between a data source and a data sink.
- Explain the different types of data formats.
- Explain the storage solution options on Google Cloud.
- Learn about the metadata management options on Google Cloud.
- Understand how to share datasets with ease using Analytics Hub.
- Understand how to load data into BigQuery using the Google Cloud console or the gcloud CLI.
Activities:

- Lab: Loading Data into BigQuery
- Quiz
Module 2 - Data Replication and Migration

Topics:

- Replication and migration architecture
- The gcloud command-line tool
- Moving datasets
- Datastream
Objectives:

- Explain the baseline Google Cloud data replication and migration architecture.
- Understand the options and use cases for the gcloud command-line tool.
- Explain the functionality and use cases for Storage Transfer Service.
- Explain the functionality and use cases for Transfer Appliance.
- Understand the features and deployment of Datastream.
Activities:

- Lab: Datastream: PostgreSQL Replication to BigQuery (optional for ILT)
- Quiz
Module 3 - The Extract and Load Data Pipeline Pattern

Topics:

- Extract and load architecture
- The bq command-line tool
- BigQuery Data Transfer Service
- BigLake
Objectives:

- Explain the baseline extract and load architecture diagram.
- Understand the options of the bq command-line tool.
- Explain the functionality and use cases for BigQuery Data Transfer Service.
- Explain the functionality and use cases for BigLake as a non-extract-load pattern.
Activities:

- Lab: BigLake: Qwik Start
- Quiz
Module 4 - The Extract, Load, and Transform Data Pipeline Pattern

Topics:

- Extract, and transform (ELT) architecture
- SQL scripting and scheduling with BigQuery
- Dataform
Objectives:

- Explain the baseline extract, and transform architecture diagram.
- Understand a common ELT pipeline on Google Cloud.
- Learn about BigQuery’s SQL scripting and scheduling capabilities.
- Explain the functionality and use cases for Dataform.
Activities:

- Lab: Create and Execute a SQL Workflow in Dataform
- Quiz
Module 5 - The Extract, Transform, and Load Data Pipeline Pattern

Topics:

- Extract, and load (ETL) architecture
- Google Cloud GUI tools for ETL data pipelines
- Batch data processing using Dataproc
- Streaming data processing options
- Bigtable and data pipelines
Objectives:

- Explain the baseline extract, and load architecture diagram.
- Learn about the GUI tools on Google Cloud used for ETL data pipelines.
- Explain batch data processing using Dataproc.
- Learn how to use Dataproc Serverless for Spark for ETL.
- Explain streaming data processing options.
- Explain the role Bigtable plays in data pipelines.
Activities:

- Lab: Use Dataproc Serverless for Spark to Load BigQuery (optional for ILT)
- Lab: Creating a Streaming Data Pipeline for a Real-Time Dashboard with Dataflow
- Quiz
Module 6 - Automation Techniques

Topics:

- Automation patterns and options for pipelines
- Cloud Scheduler and Workflows
- Cloud Composer
- Cloud Run Functions
- Eventarc
Objectives:

- Explain the automation patterns and options available for pipelines.
- Learn about Cloud Scheduler and Workflows.
- Learn about Cloud Composer.
- Learn about Cloud Run functions.
- Explain the functionality and automation use cases for Eventarc.
Activities:

- Lab: Use Cloud Run Functions to Load BigQuery (optional for ILT)
- Quiz, Data Engineering Tasks and Components, Data Replication and Migration, The Extract and Load Data Pipeline Pattern, The Extract, and Transform Data Pipeline Pattern, and Load Data Pipeline Pattern, Automation Techniques

Available Delivery Options for Introduction to Data Engineering on Google Cloud

Live Instructor Led Classroom Online (Live Online)
Traditional Instructor Led Classroom training (TILT/ILT)
Delivery at your offices in United Kingdom
Private dedicated course for your staff

How many CPD hours does Introduction to Data Engineering on Google Cloud provide?

The 1 day Introduction to Data Engineering on Google Cloud course gives you up to 6.5 CPD hours/structured learning hours.

Who is the correct audience for Introduction to Data Engineering on Google Cloud?

- Data engineers
- Database administrators
- System administrators

Do you provide training for Introduction to Data Engineering on Google Cloud?

Yes, we provide corporate training, dedicated training and closed classes for Introduction to Data Engineering on Google Cloud. This can take place anywhere in United Kingdom including London, Manchester, Birmingham, Edinburgh or live online.

What is the duration of Introduction to Data Engineering on Google Cloud?

The Introduction to Data Engineering on Google Cloud training takes place over 1 day(s), with each day lasting approximately 8.00 hours including breaks.

What other terms do people search for?

Popular related searches include: Introduction to Data Engineering on Google Cloud, Data Engineering, IDEG, Google Cloud, vILT

Why are Nexus Human the best provider for Introduction to Data Engineering on Google Cloud?

Nexus Human are recognised as one of the best training companies. Our trainers have won awards including Small Firms Best Trainer, national training partner of the year for Ireland, and global top 30 instructor awards in 2012, 2019 and 2021.

Is there a discount code for Introduction to Data Engineering on Google Cloud?

Yes, the discount code PENPAL5 is currently available for Introduction to Data Engineering on Google Cloud training. Only one discount code can be used per booking.

DURATION 8.00 Hours

No scheduled classes available at this time.

Training Insurance Included!

When you organise training, we understand that there is a risk that some people may fall ill, become unavailable.

To mitigate the risk we include training insurance for each delegate enrolled on our public schedule, they are welcome to sit on the same Public class within 6 months at no charge, if the case arises.