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 Cloud
About this Course
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Intermediate Level
Approx. 12 hours to complete
Suggested: 22 hours/week
English
Subtitles: English
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
17 videos (Total 93 min)
17 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
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
4.6
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 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 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 SMMar 21, 2020
Very detailed course on using BigQuery. Gives clarity on different services offered in GCP. Need to attend this for detailed understanding
by PUMar 18, 2020
Really good course for beginners this will help them to understand about Data Lakes, Data Warehouses, BigQuery,Google Storage & Cloud SQL.
by SBFeb 15, 2020
Very valuable information about data lakes, data warehouses, using Arrays and Structs to store data in BigQuery. Loved the course.
by DZMar 29, 2020
Very informative and good level of detail as I progress through the specialization. The hands-on learning is very appreciated.
by TTFeb 17, 2020
Simply Extraordinary !! The way course took made me finish entire course with a continuous flow.Kudos to course faculty.
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?
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