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Вернуться к Big Data Integration and Processing

Отзывы учащихся о курсе Big Data Integration and Processing от партнера Калифорнийский университет в Сан-Диего

Оценки: 2,341
Рецензии: 507

О курсе

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+....

Лучшие рецензии


21 окт. 2020 г.

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 мар. 2018 г.

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.

Фильтр по:

351–375 из 496 отзывов о курсе Big Data Integration and Processing

автор: Guillem C M

1 нояб. 2018 г.

The final week is quite difficult

автор: SHUBHAM T

2 мая 2022 г.

quite interesting and futuristic

автор: Soham G

1 мар. 2020 г.

little bit drastic and lengthy.

автор: Deleted A

25 дек. 2020 г.

Spark is not an easy language

автор: Mehul P

30 дек. 2017 г.

Nice overview to get into it.

автор: prasanth

28 окт. 2021 г.

Good content on the basics

автор: Hector G R

10 янв. 2019 г.

Pretty well course

автор: Muhammad N S

8 апр. 2021 г.

Thankyu coursera

автор: LINGAM S

10 июля 2020 г.

Good Experience

автор: Vidit K

20 мар. 2021 г.

I learnt a lot

автор: Jürgen B

31 окт. 2018 г.

Good overview.

автор: Alejandro S M

23 апр. 2020 г.

Great for db

автор: Mario L

6 авг. 2017 г.

has bugs

автор: Rohit K S

12 окт. 2020 г.


автор: HONGWEI Z

18 окт. 2017 г.


автор: Johan A P O

10 нояб. 2019 г.

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.

автор: Sarwar A

7 окт. 2020 г.

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.

автор: Dana B

14 июля 2021 г.

I really enjoy working on the topic of Big Data. I also think that the course structure and theoretical content as such is very useful and logical. Hence the 3 stars. However, hands on assignments and packages provided are outdated and getting the environment to run properly takes a lot of time and programming knowledge that I, for one, do not have. Also, data in the hands on assignements have changed, hence it is not always possible to reproduce results from assignments, which is really annoying if these results are part of a quiz. Generally, I do not think that solutions to circumvent errors due to outdated packages and data should be sourced and applied by the student through the forum. It should be in the interest of Coursera and / or the instructors to test the environment and provide updates where necessary. I really have to consider whether I want to continue with the next modules and Coursera in general given that most of my time is spent on getting the environment to run the hands on assignments running.

автор: Tina L

16 янв. 2018 г.

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.

автор: ZHE C

7 мая 2017 г.

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.

автор: Lomiarz

4 февр. 2017 г.

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 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 :)

автор: To P H

24 дек. 2018 г.

Too many software issues/installation bugs hampering the learning process. The setup procedures for every quiz takes up around 80% of the time and only 20% actually answering the quiz. Please reduce the number of quiz or consolidate them for learners do that we only need to do setup once. Mentor/Instructor presence in various discussions in which students encounter setup/installation issues are next to full absence and many sudents are left figuring out the problems themselves

автор: Gustavo V

12 окт. 2020 г.

This course gives an introductory overview in Bigdata processing and explain a variety of tools with little depth, concepts are well explained but the workshops take extra effort to complete due to the fact that the tools versions are outdated, some questionnaires don’t match python workbooks and some assignments for the final project don’t have practical examples in the lessons, so you have to use other learning resources.

автор: Bojan N

11 мая 2020 г.

Good content, good instructors - they have a nice way of conveying a message, making it easy to follow. I'm rating this course as 3 stars as the content is not kept up to date at all: materials, files, technical dependencies, versioning of the tools - it consumes MUCH, MUCH more time to get the tools setup in place correctly (so that you are able to run the hands-on exercises) compared to the actual time spent studying

автор: Tomas M

27 июля 2017 г.

While the contents are very interesting and the lectures very thorough the practical side has many draw backs. For instance: Connections to PostgresSql did not work even reading the FAQs, same with streaming data in spark. There are not enough examples on syntax and coding to correctly do the assignments. Overall I am happy with the course but it needs some improvements.