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返回到 Building Resilient Streaming Systems on Google Cloud Platform

學生對 Google 云端平台 提供的 Building Resilient Streaming Systems on Google Cloud Platform 的評價和反饋

4.7
1,790 個評分
137 個審閱

課程概述

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...

熱門審閱

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.

篩選依據:

1 - Building Resilient Streaming Systems on Google Cloud Platform 的 25 個評論(共 137 個)

創建者 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.

創建者 Peter S

Dec 20, 2018

Very interesting!!

創建者 Sudeshna D

Dec 20, 2018

good

創建者 Preetish K D

Jan 09, 2019

All concept explained nicely.

創建者 Raja R G

Dec 29, 2018

Very Good content...

創建者 Amit K

Dec 28, 2018

Good

創建者 Javier R

Jan 16, 2019

Very useful.

創建者 Christof G v R

Feb 16, 2019

Though the subject was the most obscure and least relevant to me of all 5 courses in the specialization, I think I learned the most during this one.

創建者 Mnason A P

Feb 16, 2019

great

創建者 Adam E

Feb 06, 2019

Sick

創建者 Vicente G d S

Mar 19, 2019

Excelent way of learning Pub Sub.

創建者 Chandrasekar B

Feb 27, 2019

good

創建者 Alejandro J A

Feb 27, 2019

Un curso maravilloso.

創建者 Morgan G

Mar 24, 2019

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

創建者 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.

創建者 Jumpod P

Apr 01, 2019

Very goods course

創建者 William M

Jan 31, 2019

I recommend this course to learn the fundamentals of Building Resilient Streaming Systems on Google Cloud Platform

創建者 Peeya I

Apr 06, 2019

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

創建者 Agha A A

Mar 31, 2019

Thorough and challenging.

創建者 Brian C G

Mar 04, 2019

Excellent course! Great exercises and a solid background on how to build resilient streaming systems with GCP

創建者 Julian K

Mar 06, 2019

This was a pleasure to attend. Some minor frustrations when tests failed or just stopped, but support was excellent and by revisiting your site 2 stopped tests resulted in a pass! Note that some of the current web pages have changed since the course was created - so the tests are more real-world as you have to figure stuff out yourself - not such a bad thing!

創建者 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

創建者 Rambabu A

Sep 15, 2018

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

創建者 Soumya R B

Sep 15, 2018

Awesome

創建者 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.