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

2,097 個評分
448 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+....



Oct 22, 2020

Hello Gentlemen,\n\nThis course was very helpful foe me. It enhanced my knowledge about Big Data Integration. Thank you so much for providing me such important knowledge. Thank you once again.


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.


126 - Big Data Integration and Processing 的 150 個評論(共 435 個)

創建者 roopesh d

Aug 22, 2017

very nice. easy to understand and great hands on exercises.


Sep 25, 2018

This was very challenging and very rewarding. What fun wra

創建者 Ravi V A

May 08, 2020

This course was designed very well with practical info.

創建者 Leandro R

May 12, 2017

Excellent course and very demanding! I really enjoyed.

創建者 Yogesh P

Mar 27, 2018

Good Course covering many concepts and fundamentals.


Feb 05, 2017

Lots of learning of programming Spark and MongoDB

創建者 Miguel d l S T

Jan 13, 2017

interesting course, I learned a lot about MongoDB

創建者 Shipra G

Apr 27, 2018

One of the best course fro beginners in Big data

創建者 An D

Apr 02, 2017

Thank you. Spark in this course is very helpful.


Feb 13, 2017

Very good course and professors. I recommend it.


Jul 12, 2019

This course is very interactive and practical.

創建者 Srishti R

Mar 05, 2019

Great experience towards learning this course

創建者 Nick B

Nov 28, 2018

Enjoyed the class. It was very enlightening.

創建者 Darius T

Jan 01, 2018

Great course for learning MongoDB and pySpark


Jul 29, 2020

very interesting course for big data fans :)

創建者 Zhi Q

Jan 12, 2017

a wide spectrum of tools practiced. awesome!

創建者 Assaduzzaman N

Sep 26, 2017

This is a very good course in most aspects.

創建者 Snehdip y S

Jun 05, 2020

Excellant Great exeperince learning course

創建者 Tanuj P

Mar 01, 2018

Good assignments at the end of the course.


May 26, 2020

Very interesting and informative course.

創建者 Jose L R

Oct 13, 2018

Great course! Please update the HandsOn.

創建者 Rajesh P

Nov 10, 2017

Very good course for understanding spark

創建者 Ian M

Feb 02, 2017

Lots of good hands-on and explanation...

創建者 Suhail M

Jul 17, 2020

Need More Hands on except that all good


Jan 23, 2018

Very good basic for further learning!!!