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Voltar para Exploring ​and ​Preparing ​your ​Data with BigQuery

Comentários e feedback de alunos de Exploring ​and ​Preparing ​your ​Data with BigQuery da instituição Google Cloud

4.7
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1,944 classificações
320 avaliações

Sobre o curso

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 <<<...

Melhores avaliações

RS

Jan 16, 2019

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

Apr 06, 2020

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

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301 — 319 de 319 Avaliações para o Exploring ​and ​Preparing ​your ​Data with BigQuery

por Gary T

Sep 04, 2018

The instructions weren't very clear as to how to bring data into the BQ work space.

por Phanita T

May 01, 2019

Very good for the starter. A bit too simple to who already expert in SQL

por Mohamad S

May 11, 2020

A bit salesy. More practice involving key features would be helpful.

por Paripol T

Aug 22, 2019

good concept , but course not update big query ui is already changed

por Mr. S

Jul 07, 2019

How one can deal with job fail in dataprep would be nice. Thanks :)

por Jackson M

Mar 13, 2019

The new UI for google cloud platform changes several things

por 김동호

Mar 17, 2020

This class makes it easy to use the Google Cloud Platform

por Roshan D

Oct 29, 2018

Some of the labs failed because of permission issues

por AKELLA Y S M

Jun 27, 2020

partially satisfied

por Minyoung

May 02, 2020

Too shallow on SQL

por Vladislav K

Jan 16, 2020

Too easy

por haoxin

Jun 22, 2019

too easy

por Weerachai Y

Jul 23, 2020

thanks

por MALLUGALLA B

Jun 27, 2020

good

por Priya D R

May 28, 2020

Good

por Dabblu K S

May 28, 2020

o

por AntoStain

Sep 10, 2020

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

por Michael S

Jun 13, 2018

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.

por Francisco B

Aug 08, 2019

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