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Volver a Big Data Modeling and Management Systems

Opiniones y comentarios de aprendices correspondientes a Big Data Modeling and Management Systems por parte de Universidad de California en San Diego

4.4
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2,905 calificaciones
494 reseña

Acerca del Curso

Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources. At the end of this course, you will be able to: * Recognize different data elements in your own work and in everyday life problems * Explain why your team needs to design a Big Data Infrastructure Plan and Information System Design * Identify the frequent data operations required for various types of data * Select a data model to suit the characteristics of your data * Apply techniques to handle streaming data * Differentiate between a traditional Database Management System and a Big Data Management System * Appreciate why there are so many data management systems * Design a big data information system for an online game company 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+....

Principales reseñas

MP
16 de oct. de 2017

Good Explanations of Concepts and Nice Tests. I got a trilling experience in completing the peer Assignments with keen observation and Analyzing of Concepts learned.Thanq for your course very much.

VG
27 de mar. de 2017

Nice course to describe the traditional data modeling (RDBMS) as well as various semi-structured and un-structured data modeling and management of the systems (Batch and Streaming data processing)

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26 - 50 de 484 revisiones para Big Data Modeling and Management Systems

por Guillaume V

16 de jun. de 2017

Disappointing course. Poor language level, many mistakes (grammar, words, in examples shown). Poorly explained and confusing final assignment

por Andrew C

11 de dic. de 2018

Level of content between week four and five is vastly gapped. Too big of a jump. No explanation of BDMS and DBMS in between

por Kaddoum R

16 de nov. de 2016

Too high level. Last assignment too ambiguous, peer assessment was completely random and not reliable to pass the course.

por James K

11 de feb. de 2017

Too simple, no programming, just theory.

por Irfan S

26 de sep. de 2017

Very basic and lack real time

por J H

30 de ago. de 2021

The cloudera vm used by the course requires login credentials (which students do not have) in order to correctly update and install the software using the commands given. Looking at the forum, there have been problems with software updates for quite some time, but as of Feb this year students are unable to do the updates needed outright per https://docs.cloudera.com/documentation/enterprise/release-notes/topics/cm-retrofit-auth-downloads.html. The short version, you will notice you are asked to use librasheets and will how no ability to do so.

por Marshall

5 de ago. de 2021

The state of this course is unacceptable for anyone not familiar with troubleshooting LInux. The software is woefully outdated. I do not recommend this course until the instructors apply the needed updates. Coursera should probably remove this course, considering it's a paid service.

por Leslie X

23 de jun. de 2016

hard to follow not because it is difficult, but the lecture is only slides, texts, reading slides, very boring and not so many hand-on instruction. only thing i remember is the instructor's face after finish this class. Dont know why you add this into such a good specialist.

por Robert P

25 de sep. de 2016

Poorly designed assignment on data modeling did little to expand my knowledge on the topic. Which is a shame since the individual lectures were well done and very interesting. The "Pink Flamingo" peer-peer-reveiwed exercise needs to go.

por Kjell L

12 de sep. de 2016

The last peer review is really hard to do. Hard is because the wording is very ambiguous and not all understand how to review. There was a guy who answered with SQL query. This is hardcore since we have not learned that yet...

por John F

10 de ago. de 2020

Maybe this course would have made more sense at the end of the specialization. But here it just seems like an unnecessary spike in difficulty to understand (not necessarily difficulty to pass) due to the poor lecturing style.

por William R

5 de oct. de 2016

As a manager in an IT consultancy, I can't justify sending my personnel through this course, even at $69 per course. The amount of information gained is very thin and does not move one toward being productive.

por Niti G

5 de nov. de 2017

The content is only intended for people who have a background in this field. The peer graded assignment is completely unclear on instructions . the test is not at all well devised. I am regretting.

por Rafael M

6 de ene. de 2021

constant problem during every exercise, Prepare to spend more time troubleshooting virtual machine problems and CentOS 6 issues than learning about BIG Data

por Deleted A

30 de ago. de 2018

Disastrous set-up of grading assignment. Waiting for 7 days to get rated. No possibility to contact any Coursera staff directly.

por Avazeh G

18 de oct. de 2020

Boring, impractical, very broad, 4 years out of date. Trains you on a bunch of clunky definitions but no useful substance

por Piyush P

29 de sep. de 2017

This course is the worst course on Coursera. I can't understand what it is trying to achieve.

por Seth D

18 de ago. de 2016

Very basic, the 'hands on' exercises are not very hands on and do not actually add much value

por Santosh P

15 de sep. de 2021

The vm provided is not working and no support. I have to stop learning this course.

por Kari S

13 de feb. de 2017

Course material is very poor and did not give much support for doing assignments.

por Nick G

10 de mar. de 2020

This course is SERIOUSLY out dated and hasn't been updated in several years.

por Qian H

10 de jul. de 2017

Bad course without many useful info

por andreh m

6 de nov. de 2016

The course gives an extensive overview of the topic. I have particularly appreciated the hands on section.

My recommendation to all the students is to not overlook the hands on and create some personal notes and code archive to quickly review those topics.

Some particular good learning for myself: lucene. I have used lucene at work both directly and wrapped within elastic search: in both cases I was not going deep in understanding the data model behind lucene and concepts like similarity. You can leave like that in the vast majority of the current jobs where lucene is a third party system invoked upon needs but understanding the model behind was simply much more easy than I expected.

por Joydeep S

18 de jul. de 2017

This course was really nice and very well put together. I learned a lot and more so, learned in a structured manner. For people like me who come from traditional data background and new to big data concepts this way of presenting the course is very important and fruitful. I hoping to complete the rest of the courses in this series and end up with a good depth in knowledge of big data

por José A R N

13 de sep. de 2017

My name is Jose Antonio. I am looking for a new Data Scientist career ( https://www.linkedin.com/in/joseantonio11)

I did this course to get new knowledge about Big Data and better understand the technology and your practical applications.

The course was excellent and the classes well taught by the Teachers.

Congratulations to Coursera team and Teachers.