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 stars72.72%
- 4 stars22.87%
- 3 stars3.30%
- 2 stars0.75%
- 1 star0.33%
TOP REVIEWS FROM MODERNIZING DATA LAKES AND DATA WAREHOUSES WITH GOOGLE CLOUD
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.
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
Good course but perhaps to make things stick, we would have used one project and built upon it. I felt like I was being tossed all over the place in terms of subjects and topics.
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