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Building Resilient Streaming Systems on Google Cloud Platform(으)로 돌아가기

Google 클라우드의 Building Resilient Streaming Systems on Google Cloud Platform 학습자 리뷰 및 피드백

2,011개의 평가
159개의 리뷰

강좌 소개

This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn how to build streaming data pipelines using Google Cloud Pub/Sub and Dataflow to enable real-time decision making. You will also learn how to build dashboards to render tailored output for various stakeholder audience. Prerequisites: • Google Cloud Platform Big Data and Machine Learning Fundamentals (or equivalent experience) • Some knowledge of Java Objectives: • Understand use-cases for real-time streaming analytics • Use Google Cloud PubSub asynchronous messaging service to manage data events • Write streaming pipelines and run transformations where necessary • Get familiar with both sides of a streaming pipeline: production and consumption • Interoperate Dataflow, BigQuery and Cloud Pub/Sub for real-time streaming and analysis...

최상위 리뷰


Aug 25, 2018

This course was very helpful to understand how to built high throughput streaming work flows on google cloud. It described in detail how to model big table for efficient application.


Aug 19, 2017

Course gives nice overview of Bigtable, when to use it compared to bigquery. flowchart describing the when to use which product is really helpful. Thanks Lak for the course.

필터링 기준:

Building Resilient Streaming Systems on Google Cloud Platform의 158개 리뷰 중 101~125

교육 기관: Juan S V

Aug 24, 2019


교육 기관: Gopinath K

Jul 03, 2019


교육 기관: Mnason A P

Feb 16, 2019


교육 기관: Gokula K S

Jul 17, 2019


교육 기관: Chandrasekar B

Feb 27, 2019


교육 기관: Adam E

Feb 06, 2019


교육 기관: Amit K

Dec 28, 2018


교육 기관: Sudeshna D

Dec 20, 2018


교육 기관: David R

Feb 26, 2018

Great class. Topic and information felt comprehensive and well though through. It felt like there was a bit of disorganization in the middle of the class when a lab was described in the lectures - accident alerts, and then a different lab was presented in the formal codelabs documentation - datastudio. Sadly the accident alert lab was never discussed again, though the code is there for experimentation. Not a big deal.

Overall the program was well designed and I felt like I got a lot of very useful highly applicable information from it. Among other things, this certainly makes a strong case for Google Cloud as a highly developer friendly cloud offering.

교육 기관: Don B

Nov 26, 2019

Instructor content is very strong, but they need to invest more effort in keeping the labs relevant and up to date. In some cases the mandatory Qwiklab labs do not work, and in these situations in particular they don't provide value in reinforcing what is presented in the lectures - and ultimately what you need to know to pass the GCP data engineer certification exam.

교육 기관: Rajesh D

Jun 21, 2018

Some labs pertaining to ingesting traffic data kept on throwing errors, which I couldn't resolve. That though spoiled whole of my experience, the course is very well built, informative and was the most interesting among the other 4 I have taken through the specialization

교육 기관: Mananai S

Dec 31, 2018

Excellent course. Cover products in streaming systems. The material in this course is enough to get started a real project. I liked the Dataflow in streaming application part. The labs are very useful and practical. I hope they cover a bit more coding in Bigtable part.

교육 기관: Ajay K

Jun 03, 2019

Very well taught course. The material is well organised. All instructors are extremely patient. I enjoyed the course. I do wish the labs focus a little more on coding exercises. Some concepts are a little difficult to remember

교육 기관: Nguyen V T H

Mar 18, 2019

Like other course by google, the labs part is try to flow some order so the leaner must try harder to learn by themself rather than learn in the course. BTW great source of information about how to do data engineering on GCP.

교육 기관: Scott M

Oct 11, 2017

Content was pretty good but some of the labs definitely require improvements. Hopefully they will implement a similar system to what they have under the Cloud Architecture set of courses and integrate Qwiklabs.

교육 기관: Xiao Y

Jul 02, 2019

Would have given a 5 star rating. Only reason: should have provided some Python examples for the resilient streaming related applications and corresponding labs. Java was good, but its a bit outdated....

교육 기관: Bruno M

May 03, 2018

Very nice content and the teacher is amazing, legendary but code labs have problem with source code and should be updated and quiz are very dumb, because this 4 stars is fine and fare.

교육 기관: Gwen A

Jun 10, 2019

It is a great course and it makes me appreciate the whole architecture. One thing that can be improve is if the programming languages remained consistent in the course if possible.

교육 기관: Anjan S

Dec 06, 2018

fantastic course material. Thank Lak and team.

after going through course I am now excited to work on real time issues. But yes this much is not enough, I have to learn a lot.

교육 기관: Raden M A

Dec 19, 2019

Trying to SSH to the training-vm instance is frustrating. Very laggy, might be better if the location of the training-vm follows where the students are located

교육 기관: Faizan S

Oct 16, 2019

Good course that gives an introduction to GCP products used for stream processing. I would highly recommend following the documentation along the course.

교육 기관: William E D

Jan 24, 2018

Super valuable content, but the labs are not ageing very well. I certainly got to know the content a little better by perform ad-hoc fixes on content.

교육 기관: Harold L M M

Sep 09, 2018

Good intro course on designing streaming systems with GCP technology such as PubSub + Dataflow + BigQuery or BigTable (storage).

Thank you!

교육 기관: Sirisha P

Oct 18, 2018

Interesting when doing with live examples,how it connects to streaming data quickly and give results. A more way to learn

교육 기관: Yuriy K

Jun 17, 2018

2 last labs are broken - scripts fail, suggested fixes don't work. I simply don't have time to debug this stuff.