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4.6
1,075 Bewertungen
180 Bewertungen

Über den Kurs

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 <<<...

Top-Bewertungen

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

LL

Aug 08, 2018

This is the best course I've ever taken from Coursera! Lecture/Demo/Lab instruction are VERY CLEAR! and I love the humor. :) Hope to have another course by the same teacher.

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151 - 175 von 179 Bewertungen für Exploring ​and ​Preparing ​your ​Data with BigQuery

von Alex O

Oct 03, 2019

A few questions in the labs and the quizzes could be answered differently depending on your SQL level. Yet, you HAVE to answer them exactly as they want you to answer. The videos need to be updated so to reflect the current UI of BigQuery and not how it was a few years ago.

von ONG K S

Oct 04, 2019

I get to know a new BI tool for data pre-processing and analytics, other than Alteryx.

von Hoda M

Oct 07, 2019

A good start with BIGQUERY!

von Jonathan S

Oct 08, 2019

Good. Too many videos just watching others do their own SQL. A lot to take in

von Jackson M

Mar 13, 2019

The new UI for google cloud platform changes several things

von Danis N G

Jul 12, 2018

The speaker's voice is not one of the easiest to listen to, especially for extended periods of time; moreover, he often lacks in clear pronunciation and timing. I understand the possibility of using subtitles, but it's one more effort on the part of the student, while we should focus on the content and draw conclusions. The quizzes are too short and easy; the labs seem to be focused on SQL (which could be taken for granted, at this level) instead of building up familiarity with BigQuery itself. It seems like most of the first labs are just fill-ups, it gets a little better in the labs about DataPrep. Shifting the attention from SQL to the two frameworks and their integration may be a better idea for the future, in my opinion.

von Roger S

Dec 04, 2017

Very basic in some parts. I wonder if you really have to learn about SQL or about the advantages of cloud vs on premise computing when you are taking this specialization

von ChenXiao

Nov 13, 2017

The video is too long, I recommend people just finished the Quiz and labs and lad solutions. That is enough.

von vincent p

Jun 26, 2018

Basic introduction to SQL analytics queries.About half of the videos just give the explanation of the Lab.

von Daniel M

Nov 30, 2017

Starts out as mostly a product pitch, is fairly light on actual BigQuery / SQL skill-building & mental model-forming. Last piece of last module (on DataPrep) is entirely different, with much longer & more extensive lab exercises. Feels very uneven overall, and wouldn't be my preferred intro to GBQ (it wasn't). Despite these shortcomings, is a fairly decent intro. Will see how subsequent courses in the specialization are.

von Vasi V

Jan 29, 2018

the labs can be little bit more clear. they are not updated to the new cloud dataprep environment, and some situations I could not find the correct data-insight data. That is frustrating.

von Guy R

Mar 04, 2018

The contents are interesting and engaging, however the intonation of the narrator in many of the videos (e.g. "Compare Big Data On-Premise vs. on the Cloud" is terrible - sounds like he's tired or losing air towards the end of every sentence. Simply impossible to listen to.

von N J

Apr 05, 2018

Good course, but I was plagued by Qwiklabs issues, otherwise 4 stars due to sometimes strange jumps between topics.

von Arun A

May 15, 2018

One of the main reason I am giving it a 3 star is because the labs are very disorganized and not clear clarity on why the system is broken with linking with coursera after specific labs are complete. The knowledge gained about BigQuery and how data transformation can be done is good. However, the quizes arent hard or challenging at all. I feel it can use a bit of more logical questions which may cause you to think. Plus it kind of sounds promotional for google itself with this course where they talk a lot about the features and how overly impressive this. Come on Google. Let us decide that.

von Gary T

Sep 04, 2018

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

von Roshan D

Oct 29, 2018

Some of the labs failed because of permission issues

von Phanita T

May 01, 2019

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

von haoxin

Jun 22, 2019

too easy

von Paripol T

Aug 22, 2019

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

von Md. S S H

Jul 07, 2019

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

von Radosław O

Dec 21, 2018

Last lab was interesting. Previous lessons where boring for someone who knows SQL.

von Frank S

Feb 19, 2018

Unclear if I will continue given the difficulties with Quicklabs integration. This class is overall pretty interesting but IAM needs to be much simpler. There must be a way to provide a provisional account for the enitrety of the course instead of having to get temp logins .. It is just so cumbersome and the time constraint on labs is not practical/required. The goal is to learn about GCP not race through the labs to meet a time quota.

von Chun M N

Feb 24, 2018

lots of system error in lab 4

von Nils K

Mar 12, 2018

This is essentially an ad for Google services you have to pay for.

von 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.