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

4.4
stars
2,173 ratings
466 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

SB
Oct 21, 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.

FC
Sep 24, 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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226 - 250 of 454 Reviews for Big Data Integration and Processing

By Suraj P

Jun 13, 2020

Good one

By Harsh D

Oct 11, 2018

nice one

By MR. G L

Jun 28, 2020

amazing

By ASHUTOSH S

Aug 31, 2019

awesome

By Shekh A

Jul 30, 2019

Awesome

By José G d A L N

Dec 4, 2018

Perfect

By Kavita R L

Dec 23, 2020

Good

By GOKUL M B

Sep 25, 2020

good

By RAGHUVEER S D

Jul 25, 2020

good

By Anvitha K Q

Jun 17, 2020

nice

By Aji N J

May 25, 2020

good

By Maansi

May 22, 2020

good

By aleksei a

Mar 20, 2020

good

By Arthur-Lance

Sep 24, 2017

cool

By SHAKTHI S

Jun 3, 2020

Gud

By mostafa r m

Feb 15, 2020

...

By bagiya k

Sep 6, 2020

no

By Mahesh P

Oct 9, 2018

V

By Irfan S

Oct 19, 2017

G

By CHEMAK C

Oct 13, 2016

G

By Santiago V M

Oct 21, 2020

El curso fue muy util e interesante, y mucho de lo aprendido sirve para aplicarlo en el mundo laboral de la sociedad actual. Me gustaron los módulos que tenía y los distintos retos que proponía. Sin embargo, se nota que el curso no está actualizado en términos de las herramientas que pide utilizar lo que frena mucho la fluidez del aprendizaje. Por otro lado, se nota que los mentores y profesores no están pendientes del curso. En el foro hay preguntas que se repiten y se repiten y no hay respuesta por ningún lado de nadie distintas a otros estudiantes que, o tienen las mismas dudas, o que lograron de alguna forma resolver la duda. Pienso que al ser denominado como curso, alguien debe estar pendiente de las dudas que puedan surgir.

By Michael L

Mar 22, 2020

I especially enjoyed the hand-on exercise of week 6 and all-in-all the lectures. They give a good overview on various data integration tools.

Though, I think the virtual machine and some documentation around it needs an update. If you do not finish exercises in one sweep, it is often not obvious how to restore the original settings. I think I've spent almost the same time trying to get the environment on my virtual machine running as with the actual doing in the exercise. I know that this might even reflect the life of a data scientist but some checker scripts which test, if hadoop is running properly, environment variables are set correct, the right version of java is in the path, and so on would be really helpful.

By Misha

Jul 12, 2020

Serious problems with the hands-on assignments. I consider myself a fairly seasoned programmer, with quite a few years of Python under my belt. I still spent many hours on the final project, searching around CentOS forums for ways to troubleshoot Pyspark (the last assignment takes place in a virtual machine). I would recommend not taking this class until you have a very solid understanding of Python and, be aware, this requires bravery in the face of the command line. Not for the faint of heart. I learned A LOT about MongoDB, Linux, PySpark, Hadoop, and conceptual big data as a whole.

By Anurag S

Sep 13, 2018

The course content is very well thought out and presented.

Hands-on exercises remain a challenge as many things don't work. It takes the mindset of problem-solving (not just in big data, but also in debugging, figuring out how to get different scripts to run, how to set environment variables etc.) to be able to complete all exercises in this course. I suspect that many people might get discouraged and quit the course midway.

The final week's exercises did test my programming skills to a very large extent but gave me a good understanding of the course concepts.

A very good course overall.

By Nikhil C

Aug 20, 2020

Overall very solid course, for the last week, I really enjoyed the fact that it was hands on and made you think and challenge yourself.

For the final project, the data was difficult to process. I was able to do all the major steps, but some minor issues made the task needlessly difficult. Still, I think these kinds of hands on experiences are very important since processing data IRL is not easy and you run into tons of issues.