The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.
Overview
Syllabus
- Introduction
- This module introduces the Data Engineering on Google Cloud source series and this Modernizing Data Lakes and Data Warehouses with Google Cloud course.
- Introduction to Data Engineering
- This module discusses the role of data engineering and motivates the claim why data engineering should be done in the Cloud
- Building a Data Lake
- In this module, we describe what data lake is and how to use Cloud Storage as your data lake on Google Cloud.
- Building a data warehouse
- In this module, we talk about BigQuery as a data warehousing option on Google Cloud
- Summary
- A summary of the key learning points
Taught by
Google Cloud Training
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