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.
About this Course
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.
Syllabus - What you will learn from this course
Introduction to Data Engineering
Building a Data Lake
Building a data warehouse
- 5 stars72.76%
- 4 stars22.83%
- 3 stars3.32%
- 2 stars0.74%
- 1 star0.33%
TOP REVIEWS FROM MODERNIZING DATA LAKES AND DATA WAREHOUSES WITH GOOGLE CLOUD
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.
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.
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.
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.
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