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Learner Reviews & Feedback for Big Data Integration and Processing by University of California San Diego

4.4
stars
2,055 ratings
435 reviews

About the Course

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+....

Top reviews

AA

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.

FC

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.

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301 - 325 of 422 Reviews for Big Data Integration and Processing

By YU-CHIA, H

Jul 10, 2018

A great tutorial for beginner, it is better if there is more practice

By Frank C

Dec 21, 2016

Very well explained!! This course and specialization are really good!

By Siddhartha

Apr 29, 2020

Very interesting course. It was good working with MongoDb platform

By Sabawoon S

Jan 23, 2018

Very good content, The last quiz was more about python than spark.

By Pradhyumn A

Jun 04, 2020

some of the working files created mischief so it ruined the swing

By NFOTABONG F Q

May 31, 2017

Very interesting course, and a good practical exercise at the end

By Liliana d C C M

Jul 09, 2019

Muy bueno, aprendí mucho, sobre todo en el trabajo de curso

By Ranjan K G

Apr 28, 2019

Good course to start learning Mongo DB and spark basically.

By Juan H B S

Mar 29, 2018

Helpful and really cutting edge all the contents!

By Giovanny F F F

Aug 04, 2020

Need to explain more about the syntax in spark.

By Chika E

Aug 02, 2020

Had some analysis issues at the end.

By Kajal N

Mar 03, 2019

Great experience towards this course

By Guillem C M

Nov 01, 2018

The final week is quite difficult

By Soham G

Mar 01, 2020

little bit drastic and lengthy.

By Mehul P

Dec 31, 2017

Nice overview to get into it.

By Hector G R

Jan 10, 2019

Pretty well course

By LINGAM S

Jul 10, 2020

Good Experience

By Jürgen B

Oct 31, 2018

Good overview.

By Alejandro S M

Apr 23, 2020

Great for db

By Mario L

Aug 06, 2017

has bugs

By HONGWEI Z

Oct 18, 2017

G

By Johan A P O

Nov 10, 2019

Last week was a disaster in terms of giving the necessary educational resources. I found it extremely hard to finish the assignment because I couldn't understand the knowledge set required to do it.

I think you must work on making sure students are getting tailored to the functions that you will request them at the end. It was tremendously underwhelming to me to find such interesting tasks and finding myself unable to understand any clear path to perform even the first actions.

I had to research a lot out of the platform and dig up old replies in the forum just to have hints about what I had to do to find the answers you were requesting. If you consider that it's sufficient with what you explained, you're applying an unfair filter to students.

If you didn't mean that, please adjust either this whole module to focus on

* pyspark syntaxis

* clear use cases in Data retrieval and analysis

* evaluating the syntaxis of each function that you will request later

Or just change the last module to make it according to what you've taught. Thanks, even though I found these struggles, I was able to learn.

By Tina L

Jan 16, 2018

The elaborations in video lecture sometimes are too complicated to understand. It should consider all students comes from different industry. For example, the disease/gene relationships, actually it can replaced by GeneA, DiseaseA, etc. Also, the slides are not clear enough for students to capture the outstanding points. It's not good for students to review since it's truly vague of the relationships between the list items. Overall, the lecture is just different to understand, even causing confusion sometimes.

By ZHE C

May 07, 2017

the course content is critical and as it appears in many interviews, and the fundamental understanding is important for beginners to learn this new area. however I think the software (spark or mongoDB) can be taught in a more systematic way (at least point out some resources that can help people learn them based on individual needs). I understand this course is for beginners and people supposed to learn deeper on themselves. but a road map will be helpful and reduce the pain finishing the tests.

By Lomiarz

Feb 04, 2017

The course was good enough...but exercises were very simple. Only the final course was little bit challenging. For a guy that sits in IT business for a while it's rather too simple. Besides, I've learned spark basics which is super cool...so thanks for that

Maybe you could consider to build docker image instead of using virtual machines. VM is ok, but I think that docker can simplify all the stuff without necessary downloading, installations etc.

Looking forward to the next spark challenges :)