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.
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About this Course
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Try Coursera for BusinessWhat 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.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Introduction
Introduction to Data Engineering
Building a Data Lake
Building a data warehouse
Summary
Reviews
- 5 stars72.75%
- 4 stars22.84%
- 3 stars3.30%
- 2 stars0.75%
- 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.
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.
The labs were awesome! The trainers in the video and in the demo were well prepared. The quizes however were short and not well thoughtful.
This is an excellent course to understand about Data Lakes and Data Warehouses, and how to implement them with GCP. It takes you from zero to a level where you can move confidently in GCP.
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