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Learner Reviews & Feedback for Building Batch Data Pipelines on Google Cloud by Google Cloud

4.5
stars
1,678 ratings

About the Course

Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) 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 get hands-on experience building data pipeline components on Google Cloud using Qwiklabs....

Top reviews

SV

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Excellent course with appropriate explanation on cloud data fusion, data composer, data proc and cloud data-flow. Must learn course for all aspiring Big Data Engineers.

XZ

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Good contents. Some lab questions do not have answers. Hope provide them to know how I understand the knowledge.

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126 - 150 of 208 Reviews for Building Batch Data Pipelines on Google Cloud

By 大路悠介

Feb 22, 2023

good

By Felipe A

Jul 19, 2021

good

By Shweta M (

Dec 26, 2020

BEST

By Gerardo F V

Nov 23, 2020

good

By Priyanka C

Jun 14, 2020

Good

By Cristhian R B

May 17, 2020

Thx!

By CH V S

May 6, 2020

Nice

By Santanu R

Apr 27, 2020

Good

By Koushik C

Aug 3, 2020

OK

By 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.

By 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.

By 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.

By 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

By 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!

By 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.

By 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

By Shayne L

Feb 21, 2022

Some of the course videos were just speed reading by the narrators, even the transcripts did not insert periods to the sentences. The course feels like it is just introductory material and insufficient to prepare for the certification exam.

By Ajinkya U

May 23, 2020

The course was good. Learned about data pipeline infrastructure.

Feedback: It appeared a bit fast in the second week with the need for more explanation for the concepts and designing labs based on those concepts.

Thank you. :)

By Luciano L

May 17, 2022

Esta bien, me gustaria que haya un poco mas de practica en vez de tanto copiar y pegar codigo. Pero bueno, entiendo que no pueden dejar la plataforma abierta 10 horas para que probemos.

By Arpnik S

Apr 23, 2023

The practical hands on lab can be further improved by making them more interactive rather then just copy pasting the code. Can be re-designed to have more room for experimentation.

By Heidi S

Sep 13, 2020

The pipeline building portion assumes in part that the learner has previous experience with programming. Further break down of the Python pipeline builds would be helpful.

By Deepa R

May 20, 2020

takes time understand , video makes little bore but in practice to enjoy doing but try to mention required time for excuetion or waiting time to task to executeto ece

By Ireneusz P

Nov 10, 2020

Interesting topics, but some of the labs are a waste of time (1 minute of hands-on experience, 30 minutes of provisioning resources and pipeline execution).

By Christian U

Jul 19, 2020

Good, I think pipelines need to have more labs related to some necessities in the industry, such as connect them to other external sources outside GCP

By ESTEBAN D R

May 23, 2020

Some parts of the course where not explained in full detail, especially some qwuick labs where questions were not tested or even provided with answers