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.
Modernizing Data Lakes and Data Warehouses with Google Cloud
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Modernizing Data Lakes and Data Warehouses with Google Cloud
This course is part of multiple programs.
Instructor: Google Cloud Training
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Gain insight into a topic and learn the fundamentals.
4.7
(2,892 reviews)
Intermediate level
Some related experience required
Flexible schedule
1 week at 10 hours a week
Learn at your own pace
83%
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What you'll 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.
Skills you'll gain
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Assessments
4 assignments
Taught in English
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There are 7 modules in this course
Introduce the learner to the topics that will be covered in the course and the skills they will learn.
What's included
1 plugin
This module introduces the foundational concepts of data lakes and data warehouses, setting the stage for modern architectures on Google Cloud.
What's included
1 assignment4 plugins
This module details the concept of a lakehouse and introduces the Google Cloud products most commonly used to build a modern data lakehouse using open-source formats.
What's included
1 assignment1 app item8 plugins
This module explores BigQuery as the cornerstone of a modern data warehouse and introduces BigLake for unifying access across the data lake and warehouse.
What's included
1 assignment1 app item4 plugins
This module focuses on advanced architectural patterns for the lakehouse, including data processing, orchestration, and comprehensive data governance across BigQuery, Cloud Storage, and BigLake.
What's included
1 assignment5 plugins
This module provides labs to deepen skills in the tools and technologies used by a lakehouse on Google Cloud and an overview of best practices, common mistakes, and future trends
What's included
2 app items2 plugins
Summarize the architectural and operational capabilities of the BigQuery-centric data lakehouse, covering governance, advanced analytics, and machine learning
What's included
1 plugin
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Instructor
Instructor ratings
4.6 (559 ratings)Offered by
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4.7
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Showing 3 of 2892
NN
5
Reviewed on Jan 3, 2022
Great!!! Key to understand how to take advantage of the resources offered by the Google cloud to a modern way to build and process your data.
LG
5
Reviewed on Apr 25, 2022
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.
SG
5
Reviewed on Jul 19, 2020
This is a great course for people wishing to make a career in Data Engineering on the Google Cloud Platform. Highly recommended! Its simply superb!
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
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