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學生對 Google 云端平台 提供的 Serverless Data Analysis with Google BigQuery and Cloud Dataflow 的評價和反饋

4.5
3,137 個評分
312 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 instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing. Prerequisites: • Google Cloud Platform Big Data and Machine Learning Fundamentals • Experience using a SQL-like query language to analyze data • Knowledge of either Python or Java Google Account Notes: • Google services are currently unavailable in China....

熱門審閱

EL

Dec 12, 2018

The combination of Java and python is sometimes a bit confusing. Maybe it would be better to split the course in a java and a python version so all the Beam concepts are taught in a single language.

MB

Jul 21, 2019

Thanks for designing such a wonderful course outline. I learned valuabe BigQuery and Cloud Dataflow concepts. Best part was to learn how to write data pipelines and execute on cloud using Dataflow.

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51 - Serverless Data Analysis with Google BigQuery and Cloud Dataflow 的 75 個評論(共 312 個)

創建者 Riebeeck v N

Feb 19, 2018

I enjoyed the detail. I think providing some options (interactive choose your own path type approach) around the examples which could be provided would be great.

創建者 Kalyan K

Sep 18, 2017

very good for google cloud learners

創建者 basuki r

Apr 21, 2018

Nice tutorial for my upscale abilities

創建者 srinivasarao p

May 30, 2018

e

創建者 Marcus J H

Jun 04, 2018

Nice course. Needed options for python codes in the end of the course. In the beginning you had options to look at both python and java, but this were not the case in the later stages.

創建者 Anton G

Oct 05, 2017

Great overview of BigQuery and Pcollection processing

創建者 hongseungwoo

Feb 21, 2018

It was good to be provided with very useful information.

創建者 Nataraj P

Dec 11, 2017

Great course, but i taught that you could take the datapile integration which is critical in more detailed manner.

創建者 Guy W

May 26, 2018

The course is very good, easy to understand. Lak is a good lecturer and teacher.

創建者 Michael F

Jul 14, 2017

loved it

創建者 Harold L M M

Mar 11, 2018

I think this course must be transformed and stop using codelabs in favor of quiklabs, which would be better for all students, as there would not be billing constraints on the people's accounts.

Overall, this was a great course.

Thank you.

創建者 Moses O M

Oct 20, 2017

Clear and Practical

This course brought everything about Ingestion, Transformation and Loading of data together in a very clear and practical way. It also reveals the power of Google Cloud Platform in handling both Streaming and Batch data using the same Dataflow pipeline. Great Course!

創建者 Li F

Aug 11, 2017

good. Hope Course slides can be provided for refresh knowledge since too much short videos.

創建者 Scott C

Jul 30, 2017

excellent! I definitely like the more technical review of the code that we are running to so I know why I am running the scripts I am running. I would suggest that the code not be complete and require the student to modify it.

創建者 Ajit K

Nov 12, 2017

Good one.

創建者 Doni R

Dec 05, 2017

Need more Python example, with new Python3 . Overall is great

創建者 Jared M

Apr 01, 2018

Good class

創建者 Manuel A

Sep 18, 2017

Lak rocks!

創建者 Yoann R

Dec 30, 2017

I recommande this course!

創建者 Manuel P Z

May 09, 2018

Good starting point to learn about bigquery and dataflow, I would like the course include a final project to apply all we learned.

創建者 Abhishek Y

Apr 26, 2018

A must for aspiring Data Engineers. Very good lectures and labs.

創建者 George P

Jul 28, 2017

Material and teacher are excellent. Explanations are clear and a pleasure to learn from this teacher.

創建者 Daniel S d A

Nov 05, 2017

Great!

創建者 Akashdeep H

Aug 29, 2017

Awesome

創建者 Scott v K

Jul 09, 2017

Nice description with example code for how to programmaticly build and use dataflow plus an good overview of simple and complex BigQuery queries and optimization methods.