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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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.
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Lehrplan - Was Sie in diesem Kurs lernen werden
Introduction
Introduction to Data Engineering
Building a Data Lake
Building a data warehouse
Summary
Bewertungen
- 5 stars72,72 %
- 4 stars22,87 %
- 3 stars3,30 %
- 2 stars0,75 %
- 1 star0,33 %
Top-Bewertungen von 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.
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.
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.
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