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Вернуться к Building Resilient Streaming Systems on Google Cloud Platform

Отзывы учащихся о курсе Building Resilient Streaming Systems on Google Cloud Platform от партнера Google Cloud

4.7
Оценки: 1,936
Рецензии: 152

О курсе

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...

Лучшие рецензии

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.

Фильтр по:

1–25 из 150 отзывов о курсе Building Resilient Streaming Systems on Google Cloud Platform

автор: Javier R

Jan 16, 2019

Very useful.

автор: Raja R G

Dec 29, 2018

Very Good content...

автор: Preetish K D

Jan 09, 2019

All concept explained nicely.

автор: Mnason A P

Feb 16, 2019

great

автор: 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.

автор: Alejandro J A

Feb 27, 2019

Un curso maravilloso.

автор: Chandrasekar B

Feb 27, 2019

good

автор: Brian C G

Mar 04, 2019

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

автор: 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!

автор: Vicente G d S

Mar 19, 2019

Excelent way of learning Pub Sub.

автор: Morgan G

Mar 24, 2019

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

автор: Peter S

Dec 20, 2018

Very interesting!!

автор: Agha A A

Mar 31, 2019

Thorough and challenging.

автор: Jumpod P

Apr 01, 2019

Very goods course

автор: Peeya I

Apr 06, 2019

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

автор: Adam E

Feb 06, 2019

Sick

автор: Amit K

Dec 28, 2018

Good

автор: Michael F

Jul 14, 2017

loved it

автор: Manuel P Z

May 21, 2018

Good introduction to gcp workflow (pub/sub, dataflow, bigquery, bigtabale and data studio). This course gives you the tool to start the long journey in the data engineer path.

автор: Roque R

Jan 08, 2018

Excellent!

автор: Sterlaydy

May 06, 2018

Very good way to explain about streaming, made it simple.

автор: Moses O M

Nov 10, 2017

The course breaks down the steps of building streaming data pipelines with very clear examples. I had to do some editing in some part of the code because the PubSub Libraries have been updated and the backward compatibility broken from the code used in the course.

Overall, thank you Lak!

автор: Bing A

Jul 08, 2018

Learned a lot from this course! Great job!

автор: Nguyen D P

May 07, 2018

The great course.

автор: Serhii Y

Jun 14, 2018

Very useful and interesting. Promising from tech standpoint. Lack of Python code version in some labs.