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Exploring ​and ​Preparing ​your ​Data with BigQuery(으)로 돌아가기

Google 클라우드의 Exploring ​and ​Preparing ​your ​Data with BigQuery 학습자 리뷰 및 피드백

4.7
별점
2,946개의 평가
440개의 리뷰

강좌 소개

Welcome to the Coursera specialization, From Data to Insights with Google Cloud Platform brought to you by the Google Cloud team. I’m Evan Jones (a data enthusiast) and I’m going to be your guide. This first course in this specialization is Exploring and Preparing your Data with BigQuery. Here we will see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud Platform. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Cloud Dataprep to analyze and transform your datasets. This course should take about one week to complete, 5-7 total hours of work. By the end of this course, you’ll be able to query and draw insight from millions of records in our BigQuery public datasets. You’ll learn how to assess the quality of your datasets and develop an automated data cleansing pipeline that will output to BigQuery. Lastly, you’ll get to practice writing and troubleshooting SQL on a real Google Analytics e-commerce dataset to drive marketing insights. >>> 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 <<<...

최상위 리뷰

RS
2019년 1월 15일

I love how this course was well structured. The labs helped excellently in getting hands-on experience with the tools. I highly recommend this one for starting out any analyzing with BigQuery

AR
2020년 4월 5일

I thoroughly enjoyed learning about BigQuery and using the Google Data Prep blew my mind! I am planning to use it for my day to day work and also take up more courses about Data prep

필터링 기준:

Exploring ​and ​Preparing ​your ​Data with BigQuery의 444개 리뷰 중 426~444

교육 기관: AKELLA Y S M

2020년 6월 27일

partially satisfied

교육 기관: Minyoung

2020년 5월 2일

Too shallow on SQL

교육 기관: Kirill K

2021년 4월 19일

good but brief

교육 기관: Vladislav K

2020년 1월 16일

Too easy

교육 기관: xin h

2019년 6월 22일

too easy

교육 기관: Weerachai Y

2020년 7월 22일

thanks

교육 기관: MALLUGALLA B

2020년 6월 27일

good

교육 기관: Jay D R

2020년 5월 28일

Good

교육 기관: Nuril F R

2021년 4월 7일

ok

교육 기관: 1110 - V S

2021년 3월 31일

-

교육 기관: Dabblu K S

2020년 5월 28일

o

교육 기관: Dmitry S

2021년 3월 19일

Very outdated material. The course reference GCP as it was 4 (four) years ago and GCP is a very rapidly changing platform with the interface that had numerous changes since 2017. Material of the course is not always consistent, the sequence of individual sections does not always present a coherent content. Not sure I understand how the labs are combined with the detail review of the lab being after the lab is completed - should it be the other way around? Or better of - should those videos be embedded in the lab instructions??

교육 기관: Henry W

2021년 6월 1일

The content is great, but there are three problems: 1. The links to the datasets don't work. This is a major issue on the timed labs, as you spend half the time trying to figure out where the info is to get started, instead of doing the labs.

2. Signing in to the cloud console to access things is confusing (particularly if you are signing into Coursera via Google) 3. The UI of google cloud has all been updated since the videos were taken.

교육 기관: Jerry H

2021년 5월 14일

Not worth the money in my mind. I have experience so I was bored, and if I didn't I'd likely be lost. They essentially give you queries to run, after introducing you to basic syntax, without you needing to build from scratch. I'm hoping that the next couple classes are better.

교육 기관: AntoStain

2020년 9월 10일

The topic is interesting but it would be better to have more challenging graded exercises and more practice without guidance.

교육 기관: Sovandeb B

2021년 11월 1일

The course was very one dimensional. Not a lot of hands on training.

교육 기관: Michael S

2018년 6월 13일

I have many issues with this course. I'd like to start by saying it was a good overview of BigQuery and really helpful in understanding what I can do with it. So, it accomplished its task. First, there are multiple modules that are out of order, so it randomly jumps hugely in difficulty, and then all of the sudden he "introduces" SQL. This happens a couple times, with different datasets. This is a huge problem and frustrating.Second, a bunch of the course is essentially an advertisement for Google. Which is fine, but it means the course skirts around cost (it's in there, but it's hugely vague and basically just says to look at the website. Why not say the cost of all the queries run in the course? It feels like an afterthought). Also probably about a third of the course is just talking about how great Google is - once again, I get it, but tone it down. Fully understanding cost is important and the length of the course could be considerably reduced by removing redundant Google info. Third, it only made me more confused about what data science IS. The first task of a data scientist, according to the slides, is to analyze, while the first task of a data analyst is to derive. Does the analyst not analyze?? That's a small example but this pattern repeats. I do not understand the dividing line. Data engineering makes more sense.Additionally - the labs didn't give me credit for completion a couple times making me redo them. Also, the SQL data is badly formatted and promotes bad practices IMO - why fix data with queries instead of fixing the schema, the root of the problem, which would save cost and time? I get the point is that data scientists need to cleanse the data, but like I said, that is a ducktape on a leaky pipe. At least mentioning that would be good.Once again, I did get value from the course. However, I think it needs a serious overhaul.

교육 기관: Francisco B

2019년 8월 8일

No puedo finalizar el curso, ya que no existe el laboratorio "Lab: Explore and Create an Ecommerce Analytics Pipeline with Cloud Dataprep" en QwikLABS

교육 기관: Juan J R V

2021년 6월 24일

increible, maravilloso, no sé de que trata pero se movian cosas de google