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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

4.7
1,936개의 평가
152개의 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

PG

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.

CC

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 150개 리뷰 중 26~50

교육 기관: Carlos G

Jul 09, 2017

Enhorabuena por facilitar formación de esta manera. El curso está perfectamente estructurado y los contenidos (tanto videos como labs) funcionan perfectamente y son totalmente didacticos. Se agradecería en castellano pero , incluso en Inglés, se entiende perfectamente.

교육 기관: Mohit G

Apr 12, 2018

Very informative. I learnt a lot. Thanks to course team.

교육 기관: Andrei Z

Jun 30, 2018

like it very much due to more deep dive in implementation

교육 기관: Abhishek Y

Apr 26, 2018

Excellent. All important components for streaming are thoroughly covered.

교육 기관: XIAO N

Dec 29, 2017

Good introduction to Google Cloud Products

교육 기관: Narasimharao K

Jul 10, 2017

Great content. Totally worth it

교육 기관: Yoann R

Dec 31, 2017

I recommand this course!

교육 기관: isaac30tsai

Aug 01, 2017

Great course with lots of useful information.

교육 기관: Gonzalo

Feb 04, 2018

Useful exercises and a the instructor delivered very clear and useful lessons

교육 기관: Gianluca B

Jan 28, 2018

Clear, well organized

교육 기관: Daniel M

Jan 14, 2018

Very interesting.

교육 기관: Cổ N T

Jul 07, 2018

very great

교육 기관: Jaskarandeep P

Oct 16, 2018

great Learning Experience

교육 기관: harada h

Sep 26, 2018

This has been a great course. All the theory and practical content I find useful to get me started in the field of machine learning

교육 기관: Girish O

Oct 19, 2018

Thank you Lak for a wonderful journey through GCP, ML and Big Data

교육 기관: Zoran B

Oct 24, 2018

Lak is awesome!

교육 기관: Parag G

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.

교육 기관: Onur U

Nov 26, 2018

Streaming pull on Pub/Sub can also be added.

How to get publish time and message id those are added on Pub/Sub on Dataflow can also be mentioned.

교육 기관: Flavio d R

Nov 20, 2018

Good overview of streaming architecture, coupled with realistic use cases in the labs.

교육 기관: Rambabu A

Sep 15, 2018

Wonderful and powerful features in google ... Ultimate Powerful cloud Platform

교육 기관: Soumya R B

Sep 15, 2018

Awesome

교육 기관: chander b s

May 10, 2019

Excellent.

교육 기관: Oscar L

Apr 27, 2019

Great course, it would be great if the volume of the videos are slighty higher, thanks

교육 기관: Victor C

Apr 18, 2019

muy bueno

교육 기관: Widiarto A

Jun 16, 2019

Awesome course! Very inspiring for new users of GCP to make their own streaming data pipeline!