4.7
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2,674 ratings

Google Cloud Training

45,172 already enrolled

Offered By

Google Cloud

About this Course

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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.
This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.

Flexible deadlines

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Intermediate Level

Approx. 7 hours to complete

English

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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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Intermediate Level

Approx. 7 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.63/5 (503 Ratings)

Google Cloud Training

1,912,959 Learners

1,033 Courses

Offered by

Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.

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Syllabus - What you will learn from this course

Content Rating83%(3,186 ratings)

Week1

Week 1

4 minutes to complete

Introduction

4 minutes to complete

2 videos (Total 4 min)

2 hours to complete

Introduction to Data Engineering

2 hours to complete

14 videos (Total 41 min)

14 videos

Module introduction1mThe role of a data engineer4mData engineering challenges5mIntroduction to BigQuery2mData lakes and data warehouses4mTransactional databases versus data warehouses4mPartner effectively with other data teams5mManage data access and governance1mDemo: Finding PII in your dataset with the DLP API1mBuild production-ready pipelines2mGoogle Cloud customer case study1mRecap1mLab Intro: Using BigQuery to do Analysis13sGetting Started with Google Cloud and Qwiklabs4m

1 practice exercise

Introduction to Data Engineering4m

2 hours to complete

Building a Data Lake

2 hours to complete

8 videos (Total 42 min)

Week2

Week 2

4 hours to complete

Building a data warehouse

4 hours to complete

16 videos (Total 91 min)

16 videos

Module Introduction1mThe modern data warehouse3mIntroduction to BigQuery6mDemo: Querying TB of data in seconds7mGet started with BigQuery11mLoad data into BigQuery11mLab Intro: Loading Data into BigQuery25sExplore schemas27sDemo: Exploring Schemas10mSchema design3mNested and repeated fields9mDemo: Nested and repeated fields15mDesign the optimal schema for BigQuery1mLab Intro: Working with JSON and Array data in BigQuery17sOptimize with partitioning and clustering6mReview2m

1 practice exercise

Building a Data Warehouse4m

2 minutes to complete

Summary

2 minutes to complete

1 video (Total 2 min)

Reviews

4.7

333 reviews

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3 stars
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TOP REVIEWS FROM MODERNIZING DATA LAKES AND DATA WAREHOUSES WITH GOOGLE CLOUD

by ATMay 4, 2020

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.

by TGFeb 4, 2020

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

by FMApr 16, 2020

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.

by JNDec 5, 2020

Really well put together with interesting content and good examples. The labs allow really good practice and help to build confidence.

View all reviews

Frequently Asked Questions

Can I preview a course before enrolling?
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.
When will I have access to the lectures and assignments?
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.
What will I get when I enroll?
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.
When will I receive my Course Certificate?
If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.
Why can’t I audit this course?
This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.
What is the refund policy?
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Modernizing Data Lakes and Data Warehouses with Google Cloud

About this Course

What you will learn