Modernizing Data Lakes and Data Warehouses with Google Cloud

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.

• 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