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 Platform 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. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.
Offered By
Google CloudAbout this Course
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Intermediate Level
Approx. 9 hours to complete
English
Subtitles: English, Spanish
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 9 hours to complete
English
Subtitles: English, Spanish
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.
Syllabus - What you will learn from this course
7 minutes to complete
Introduction
This module gives an introduction of the Data Engineering specialization and the course.
7 minutes to complete
2 videos (Total 7 min)
2 hours to complete
Introduction to Data Engineering
This module describes the role of a data engineer and motivates the claim why data engineering should be done in the Cloud
2 hours to complete
13 videos (Total 55 min)
13 videos
Analyze data engineering challenges8m
Intro to BigQuery3m
Data Lakes and Data Warehouses5m
Demo: Federated Queries with BigQuery6m
Transactional Databases vs Data Warehouses4m
Partner effectively with other data teams6m
Manage data access and governance2m
Demo: Finding PII in your dataset with DLP API1m
Build production-ready pipelines2m
Review GCP customer case study3m
Recap1m
Lab Intro: Using BigQuery to do Analysis17s
1 practice exercise
Introduction to Data Engineering30m
2 hours to complete
Building a Data Lake
In this module, we describe what data lake is and how to use Google Cloud Storage as you data lake on GCP
2 hours to complete
10 videos (Total 58 min)
10 videos
Data Storage and ETL options on GCP4m
Building a Data Lake using Cloud Storage10m
Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions7m
Securing Cloud Storage5m
Storing All Sorts of Data Types5m
Demo: Running federated queries on Parquet and ORC files in BigQuery4m
Storing Relational Data in the Cloud1m
Cloud SQL as a relational Data Lake7m
Lab: Loading Taxi Data into Cloud SQL27s
1 practice exercise
Building a Data Lake4m
4 hours to complete
Building a data warehouse
In this module, we talk about BigQuery as a data warehousing option on GCP
4 hours to complete
20 videos (Total 112 min), 1 reading, 3 quizzes
20 videos
Intro to BigQuery1m
Demo: Querying TB of Data in seconds7m
Getting Started9m
Loading Data11m
Lab Intro: Loading Data into BigQuery21s
Exploring Schemas24s
Demo: Exploring Schemas10m
Schema Design3m
Nested and Repeated Fields8m
Demo: Nested and Repeated Fields15m
Lab Intro: Working with JSON and Array Data in BigQuery13s
Optimizing with Partitioning and Clustering5m
Demo: Creating Partitioned Tables7m
Demo: Partitioning and Clustering6m
Preview: Transforming Batch and Streaming Data2m
Recap1m
Monitoring BigQuery usage and reservations5m
Intro to BigQuery System Table Reports6m
Demo: BigQuery System Tables with Data Studio7m
1 reading
BigQuery Pricing 10m
1 practice exercise
Building a Data Warehouse4m
2 minutes to complete
Summary
This module reviews all the topics covered in the course
2 minutes to complete
1 video (Total 2 min)
1 video
Reviews
TOP REVIEWS FROM MODERNIZING DATA LAKES AND DATA WAREHOUSES WITH GCP
by AAFeb 14, 2020
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.
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 BAFeb 8, 2020
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.
by MEAug 29, 2020
I really like how the Google courses do not overwhelm the learner with too much information. The information was presented well and the labs were very practical with clear instructions.
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.
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.
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