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Avis et commentaires pour d'étudiants pour Big Data Integration and Processing par Université de Californie à San Diego

2,212 évaluations
475 avis

À propos du cours

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+....

Meilleurs avis

21 oct. 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.

5 mars 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.

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326 - 350 sur 461 Avis pour Big Data Integration and Processing

par Pradhyumn A

4 juin 2020

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


30 mai 2017

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

par Liliana d C C M

9 juil. 2019

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

par Ranjan K G

28 avr. 2019

Good course to start learning Mongo DB and spark basically.

par Ing. J H B S

29 mars 2018

Helpful and really cutting edge all the contents!

par Giovanny F F F

3 août 2020

Need to explain more about the syntax in spark.

par Puneeth K R

1 nov. 2020

it's very intresting to learn this course

par Chika E

2 août 2020

Had some analysis issues at the end.

par Kajal N

2 mars 2019

Great experience towards this course

par Guillem C M

1 nov. 2018

The final week is quite difficult

par Soham G

1 mars 2020

little bit drastic and lengthy.

par Shamel D

25 déc. 2020

Spark is not an easy language

par Mehul P

30 déc. 2017

Nice overview to get into it.

par Hector G R

10 janv. 2019

Pretty well course

par Muhammad N S

8 avr. 2021

Thankyu coursera


10 juil. 2020

Good Experience

par Vidit K

20 mars 2021

I learnt a lot

par Jürgen B

31 oct. 2018

Good overview.

par Alejandro S M

23 avr. 2020

Great for db

par Mario L

6 août 2017

has bugs

par Rohit K S

12 oct. 2020



18 oct. 2017


par Johan A P O

10 nov. 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.

par Sarwar A

7 oct. 2020

I am writing a review for not only for this course but for the previous two courses as well.

The points that I want to make:

The first two courses were okay as far as the theory is concerned but I am very much disappoint with this course because of the following reasons:

1.Not enough exercises for MongoDB

2.That means we have to go further to learn more about MongoDB

3. Too many tools outlined in this course but in return, only a few quizzes comprise hardly more than six questions each.

4.The instructors could have opted for more quizzes on Apache Spark, SparkSQL, MongoDB, Spark Streaming.

5.The creator of this specialization should add two more courses down the line namely " Querying Databases using SparkSQL and MongoDB" and another course could be on "Spark streaming and Splunk"

Overall I didn't like this course at all.

I would like to tell the future learners don't register for this course if you want to take lessons on MongoDB, spark SQL, spark streaming, and Splunk. Look for the courses on COURSERA if you want to take lessons on the above frameworks.

par Tina L

16 janv. 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.