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学生对 Google 云端平台 提供的 Building Batch Data Pipelines on GCP 的评价和反馈

4.5
1,450 个评分
181 条评论

课程概述

Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs....

热门审阅

UB
May 27, 2020

A great course to help understand the various wonderful options Google Cloud has to offer to move on-premise Hadoop workload to Google Cloud Platform to leverage scalability of clusters.

AD
Jul 16, 2020

Great course learning what it is the big advantages of using GCP for data given they have big implementations and with better performance of what it is today in on premises scenarios

筛选依据:

101 - Building Batch Data Pipelines on GCP 的 125 个评论(共 182 个)

创建者 Dheeraj A

May 11, 2020

A Good One!

创建者 Ryan B

Apr 24, 2021

Thank you!

创建者 Diego S

Jun 12, 2020

Excellent!

创建者 Fatima-zahra K

Mar 22, 2020

magnifique

创建者 Mirelys D

Jun 25, 2020

Excelente

创建者 Neftali M

May 25, 2020

EXCELLENT

创建者 Ömer F B

Jan 24, 2020

Great Job

创建者 Trusha R S

May 5, 2020

good one

创建者 Muhammad Z H

Jun 5, 2020

Thanks

创建者 Ganesh K

May 4, 2020

great

创建者 Felipe A

Jul 19, 2021

good

创建者 Shweta M (

Dec 26, 2020

BEST

创建者 Gerardo F V

Nov 23, 2020

good

创建者 Priyanka C

Jun 14, 2020

Good

创建者 Cristhian R B

May 17, 2020

Thx!

创建者 CH V S

May 6, 2020

Nice

创建者 Santanu R

Apr 27, 2020

Good

创建者 Koushik C

Aug 3, 2020

OK

创建者 Kowsik P

Dec 20, 2020

The course covers the main stuff required to understand the lifecycle of batch processing along with hands-on labs. However, when we have complimentary services offered by GCP which is Data Flow on top of the Data fusion which serves a similar purpose so it's much necessary to explain the use cases holistically when to go for Data flow and Data fusion. Also this 3rd of 6 courses as part of DE certification, it has more code content explained.

创建者 Jeremy G

Dec 21, 2021

I thought this course was good but would have been better if it went a bit deeper into the infrastructure that the different Pipelines tools run on in GCP, particularly for Dataflow. I understand that Dataflow is serverless but a better explanation of what that means as jobs are running would have been helpful.

创建者 Robert L

Apr 23, 2020

Enjoyed the going into the tools to build datapipelines. Watching jobs complete on Dataflow was informative, actually seeing processes start out of sequence. Personally found the Hadoop sections a bit heavy as migrating existing environments isn't a central use case, but good to know in any event.

创建者 Junaid A

Feb 20, 2020

This is a really good course to begin with batch processing using dataproc and dataflow. The student do not need to have any knowledge of these 2 said technologies before hand to take this course. But this course defines a solid foundation for beginners to begin processing batches of data on GCP

创建者 Bhargav D

May 3, 2020

Good course! Week 2 labs should have been more comprehensive so that there is no way to move forward other than to learn the nuts and bolts of Apache Beam and building pipelines from scratch. But other than that, pretty useful course! All concepts related to batch pipelining nicely covered!

创建者 Lin Y

Jul 12, 2020

Love the course, but I feel 2nd week material are bit too much to digest in one week. Also, many topics are covered in short amount of time. I wish there more in-depth exercises (as external resources) to strengthen my learning. The labs are helpful intro but not sufficient on its own.

创建者 Bhushan V W

Jul 2, 2020

Dear Team, Thank you very much for the training

"Building Batch Data Pipelines on GCP"

I would like to appreciate all the time effort and the passion that you put in , to make it so easy to understand . The Labs and the Guides explained a lot . Thank you,

Bhushan