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 stars72.75%
- 4 stars22.84%
- 3 stars3.32%
- 2 stars0.74%
- 1 star0.33%
TOP REVIEWS FROM MODERNIZING DATA LAKES AND DATA WAREHOUSES WITH GOOGLE CLOUD
We can see how fast, useful and pragmatic are moder data lakes and dataware houses. And of course some hands on experience to have fun.
Course material spends a little too much time promoting the benefits of GCP when it could be focusing on the technical aspects of using 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.
Really well put together with interesting content and good examples. The labs allow really good practice and help to build confidence.
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