Chevron Left
返回到 Building Resilient Streaming Systems on Google Cloud Platform

学生对 Google 云端平台 提供的 Building Resilient Streaming Systems on Google Cloud Platform 的评价和反馈

1,790 个评分
137 个审阅


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...



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.


51 - Building Resilient Streaming Systems on Google Cloud Platform 的 75 个评论(共 137 个)

创建者 Gonzalo

Feb 04, 2018

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

创建者 Gianluca B

Jan 28, 2018

Clear, well organized

创建者 Daniel M

Jan 14, 2018

Very interesting.

创建者 Cổ N T

Jul 07, 2018

very great

创建者 Keith A

Apr 30, 2019

Excellent course.

创建者 Victor C

Apr 18, 2019

muy bueno

创建者 Oscar L

Apr 27, 2019

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

创建者 Jumpod P

Apr 01, 2019

Very goods course

创建者 Agha A A

Mar 31, 2019

Thorough and challenging.

创建者 Peeya I

Apr 06, 2019

Great course to combined and test the knowledge from other modules.

创建者 Morgan G

Mar 24, 2019

I understand how bigtable works and how to design a good table. That is the biggest take for me!

创建者 Mohammed A M F S

Mar 27, 2019

Thanks Lak and the team for detailed information. The way of teaching is best which will clears the doubts of the everyone.

创建者 Dylan H

May 17, 2019

This course did a great job in pulling it all together. It had more interesting labs for that reason as well. It would be great to get a code summary of the pieces that are really helpful when setting up a pipeline... sort of like a cheatsheet

创建者 DOLA K S

May 19, 2019

Ce cours est très bien fait, et conduit l’étudiant à atteindre peu a peu la maîtrise du contenu a travers des exemples concrets et pratique

创建者 Jose L C V

Jun 02, 2019

Good Module, I learn a lot from it

创建者 Monish K

Jun 02, 2019

Good learning experience

创建者 Shrikant L K

Jun 03, 2019

Excellent GCP platform and superb training course, Lak conducted it with lots of interest. Lab sessions are really good. Looking forward to takeup the certification soon


Jun 04, 2019

Very simple way of presenting the problem and solving through GCP Streaming and Bigtable

创建者 Nitesh J S

Jun 06, 2019

I am very happy and highly impressed with the content of the GCP.

创建者 Widiarto A

Jun 16, 2019

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

创建者 Gopinath K

Jul 03, 2019


创建者 Raja S D

Jul 06, 2019

Great course to get started with GCP and Data Engineering.

创建者 Jafed E

Jul 06, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

创建者 Gokula K S

Jul 17, 2019


创建者 Simon H

Jul 22, 2019

I learnt a lot! thanks