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学生对 Google 云端平台 提供的 Achieving Advanced Insights with BigQuery 的评价和反馈

4.7
442 个评分
51 个审阅

课程概述

The third course in this specialization is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<...

热门审阅

KF

Sep 18, 2018

Useful practical course, especially about performance optimization. Window functions have many options, it would be nice to add window size description with practical examples or links to them.

LM

Aug 11, 2018

Excellent course; I only wish there were a much longer and more robust lab on optimizing query performance, after all the tips we learned in the corresponding lessons.

筛选依据:

1 - Achieving Advanced Insights with BigQuery 的 25 个评论(共 51 个)

创建者 Fernando E

Dec 04, 2018

Really helpful with enough theory background and practical exercises

创建者 Ridhima S

Mar 25, 2019

Absolutely important topics such as handling nested fields, query optimization techniques and advanced functions are covered. Excellent content!

创建者 Ngo D V

Mar 30, 2019

good for Data Analyst

创建者 Michael T

Jan 08, 2019

I learned lots about the structs and arrays and how it could be used to improve performance by creating parent child relationships instead of doing expensive joins

创建者 Juan D O

Jul 13, 2018

Very interesting and nice to follow

创建者 Jose L C V

Aug 26, 2018

Muy buen curso

创建者 LIJUN L

Aug 10, 2018

Super GREAT job Evan! This is the most valuable BigQuery courses I've ever learned!

创建者 Lawrence M

Aug 11, 2018

Excellent course; I only wish there were a much longer and more robust lab on optimizing query performance, after all the tips we learned in the corresponding lessons.

创建者 Rommel J P

Oct 11, 2018

Some useful insights here that I can immediately apply to my work in BigQuery.

创建者 Nguyen V T H

Nov 13, 2018

Good but lack of sql example and sql questions

创建者 Oleg Z

Nov 20, 2018

nice course

创建者 Ekta M

Aug 21, 2018

good

创建者 José R P

Feb 02, 2018

Greath

创建者 Harold L M M

Feb 17, 2018

Excellent course on BigQuery, Dataprep, DataStudio and Dataset Secure Access topics. Hoped to have more on Datalab and Bigquery, and also more difficult labs, but it's ok.

Overall this was a great course with great material.

Thanks!

创建者 michal.krasowski@gmail.com

Jan 18, 2018

Awesome. This part of specialization is worth time and money spent.

创建者 Kaushik D

May 27, 2018

Course provides a high level understanding of what can be achieved through GCP.

创建者 Scott M

Mar 11, 2018

Great course in understanding more advanced topics in BQ

创建者 Timothy W

Dec 01, 2017

Lots of in-depth material covered in this course, including nesting of data structures. Also provides high-level introductions to Google Data Studio and Cloud DataLab.

创建者 Christopher C

Feb 13, 2018

Very helpful to know advanced SQL querying even if I don't really have to do it myself.

创建者 Kristina F

Jan 22, 2018

Very informative and valuable learning. Enjoyed both the Google specific content as well as the general data analyst content.

创建者 Izzy L

Dec 04, 2017

Fantastic course with great focus on advanced subjects.

创建者 Rian P

Mar 07, 2018

Thanks for the course, the lab practices are very useful, would be great if there are any project assignments

创建者 Lorenço G A

Jun 03, 2018

Excellent course, material and labs. Congrats for Google professionals and Coursera staff. Keep rockking, cheers!

创建者 Yaakov M

Jan 25, 2018

Great insights!

创建者 Konstantin F

Sep 18, 2018

Useful practical course, especially about performance optimization. Window functions have many options, it would be nice to add window size description with practical examples or links to them.