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 Platform 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. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.
About this Course
Learner Career Outcomes
20%
29%
20%
Learner Career Outcomes
20%
29%
20%
Offered by

Google Cloud
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Syllabus - What you will learn from this course
Introduction
This module gives an introduction of the Data Engineering specialization and the course.
Introduction to Data Engineering
This module describes the role of a data engineer 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 Google Cloud Storage as you data lake on GCP
Building a data warehouse
In this module, we talk about BigQuery as a data warehousing option on GCP
Summary
This module reviews all the topics covered in the course
Reviews
TOP REVIEWS FROM MODERNIZING DATA LAKES AND DATA WAREHOUSES WITH GCP
Good introduction and overview of the field of data engineering, data lakes and modern data warehouses and a hands-on walkthrough of all the technologies related to solving these problems on GCP.
A better understanding of BigQuery starts here. A vital resource for consultants, data analysts, and product managers, and an important reference source for engineers and data scientists.
The course offers a nice description of what modern DWH means, which are the differences between classic DWH and cloud DWH. You have the chance to work with the new cloud concept on GCP.
I really like how the Google courses do not overwhelm the learner with too much information. The information was presented well and the labs were very practical with clear instructions.
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