Chevron Left
返回到 Big Data Integration and Processing

學生對 加州大学圣地亚哥分校 提供的 Big Data Integration and Processing 的評價和反饋

1,892 個評分
399 條評論


At the end of the course, you will be able to: *Retrieve data from example database and big data management systems *Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications *Identify when a big data problem needs data integration *Execute simple big data integration and processing on Hadoop and Spark platforms This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+....



Mar 06, 2018

It was a good course, it could have been better if some examples of Spark were also provided in other Languages like Java, people without having background of python may find it difficult.


Sep 25, 2016

Best course taking into account the first three. Good material, more in depth than the other ones. Very well explained. Useful to get a sense of various interesting topics and orientative.


301 - Big Data Integration and Processing 的 325 個評論(共 386 個)

創建者 David T

Oct 23, 2016

Good experience of using the big data tools but a total lack of engagement in the forums by the instructors and community mentors make it hard going if anything goes wrong. The final quiz took me over 8 hours mostly because there was no one to ask for hints when I was totally stuck and confused!

創建者 Joren Z

Jul 05, 2017

The course covers interesting materials and seems thorough. It's mostly lectures and reading, and not so much actually working with the technology. Since the latter tends to be the hardest part, the overall difficulty remains on the low end of the scale.

創建者 Rashmi U

Nov 28, 2016

I feel the contents of this course were great, no second thought on it. It makes your concepts crystal clear. But faced lots of issues during practicing the hands on exercises and did not get proper feedback or response on any of the queries.

創建者 shruthi r

Jul 07, 2019

The hands on dataset installation had lots of problems while installing and spark and mongodb hardly worked even after multiple installations and i had tried many ways to get it to work but there was no benifit.

創建者 Ken C

Oct 15, 2017

Lots of technical issues with assignments. Spent a lot of time troubleshooting issues that have been around for 9 months or more and never addressed. Seems like this course has been abandoned by creators.

創建者 Ahmed R

Sep 19, 2019

Content was up to date but practice exercises are limited to Cloudera platform as well as too old. Need to be updated with more use cases and more exercises.

Thanks Coursera :)

創建者 Francesca S

May 06, 2018

the explanation for the hands on exercises are poor. Had to waste a lot of tie and consult forum discussions as well as other inline tutorial a lot.

創建者 Rahul R

Jun 08, 2017

The course material is not sufficient to work out the exercises. For the Spark final quiz you will have to take up another course to pass this one.

創建者 Brandon S

Jan 12, 2017

Programming instructions were not clear, and the version of Python that was installed on my machine did not support the Jupy

創建者 Shalaka M

Oct 16, 2017

I wish that the Spark programming should have been covered in more details as was the MongoDB and Splunk covered.

創建者 Tatiana M

Feb 28, 2017

A little slower than the last ones, not my favorite but great use of hands-on projects and enagagement

創建者 SU C G

Oct 23, 2016

Needs more depth. Instructors should reference more external readings since the lectures are brief.

創建者 Anirudh

Dec 25, 2016

some of the stuff was not mentioned properly, like for last quiz how to expoert data from mongodb

創建者 Nester P

Sep 10, 2017

The last assignment of Week 6 was far more advanced than the rest of the material.

創建者 Luís O

Apr 27, 2020

You could focus more on Spark that is the widely software for Big data Processing

創建者 Erik P

Oct 14, 2017

very nice, just wish the environment was using docker instead of virtual machines

創建者 Silvia C R S

Oct 28, 2017

I think that there should be more exercises for MongoDB and Spark assigments.

創建者 Ramathmika

Apr 02, 2020

Not very efficient hands-on practices but overall good learning experience

創建者 Dev A S

Jan 20, 2020

Good course. But we couldn't relate the theoretical videos with hands-on.

創建者 Vadim C

Nov 05, 2016

The final assessment somewhat not really well designed, imho.

創建者 Ashish J

Aug 25, 2017

spark hands on should have been more instructive.


Aug 05, 2019

Good info, just a lot of info to digest.

創建者 Konstantin K

Mar 01, 2018

All is good except the Splunk case

創建者 Ho S J

Jun 22, 2017

Very difficult final exam.

創建者 Brajesh L S

Apr 27, 2020

Tough one.