What you will learn
Differentiate between data lakes and data warehouses.
Explore use-cases for each type of storage and the available data lake and warehouse solutions on Google Cloud.
Discuss the role of a data engineer and the benefits of a successful data pipeline to business operations.
Examine why data engineering should be done in a cloud environment.
Program Overview
Introduction
⏳ 3 minutes
Introduces the Data Engineering on Google Cloud series and this specific course.
Introduction to Data Engineering
⏳ 1 hour
Discusses the role of data engineering and the rationale for performing data engineering in the cloud.
Building a Data Lake
⏳ 1 hour
Describes what a data lake is and how to use Cloud Storage as your data lake on Google Cloud
Building a Data Warehouse
⏳ 5 hours
Explores BigQuery as a data warehousing solution on Google Cloud.
Summary
⏳ 2 minutes
Summarizes the key learning points from the course.
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Job Outlook
- Proficiency in data lakes and data warehouses is valuable for roles such as Data Engineer, Data Analyst, and Cloud Architect.
- Skills acquired in this course are applicable across various industries, including finance, healthcare, and technology.
- Completing this course can enhance your qualifications for positions that require expertise in cloud-based data storage and processing solutions.
Specification: Modernizing Data Lakes and Data Warehouses with Google Cloud
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