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Вернуться к Big Data Modeling and Management Systems

Отзывы учащихся о курсе Big Data Modeling and Management Systems от партнера Калифорнийский университет в Сан-Диего

4.3
Оценки: 2,093
Рецензии: 340

О курсе

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+....

Лучшие рецензии

MP

Oct 17, 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

Mar 28, 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)

Фильтр по:

1–25 из 329 отзывов о курсе Big Data Modeling and Management Systems

автор: Nishant U

Feb 18, 2019

informative, descriptive with hands-on experience on updated tools.

автор: Sandeep D

Jul 16, 2019

Just a basic overview. Not much hands on

автор: Tejprakash U

Dec 10, 2018

course is well designed and structured.

автор: Luis A R

Nov 28, 2018

Excelente curso, falta un poco mas de uso práctico de las herramientas para manejo de Big Data.

автор: Esteban E C

Nov 30, 2018

I learnt a lot of things with this course, It doesn't matter we are at 2018, stills pretty asertive with the topics. :)

автор: SANJEEVE K G

Dec 19, 2018

Thanks lot to Coursera

given me new life to me

I want to go further in this course

автор: Panagiotis T

Jan 16, 2019

Very useful, although some concepts (especially week 5) are a bit condensed and hard to remember without further practice.

автор: Guilherme S

Jan 17, 2019

Excelent course

автор: Dilara B

Feb 24, 2019

thank you

автор: VIJAY M

Jan 18, 2019

Great course, great Faculty....

автор: Mayank C

Apr 10, 2019

G

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e

a

t

автор: Routhana L

Apr 10, 2019

As a undergraduate data analytics student, this course was an enlightening experience that complemented my more theoretical, less-applicational on campus course very well.

автор: Andrea C

Mar 14, 2019

Excellent course

автор: Wiboon O

Mar 06, 2019

Very good lessons

автор: Duc D

Dec 10, 2018

Good content!

автор: María B O S

Sep 26, 2018

An appropriate course for neophytes in Big Data

автор: Jamiil T A

Sep 26, 2018

An interesting course on BDMS and DBMS you will real learn more about the velocity and volume aspect of the big data. Good luck !

автор: Vikas K S

Sep 28, 2018

I liked the course. Everything was good at its part.

автор: Savitha R

Sep 15, 2018

Bit tough concepts. The concepts get evaporated in sometime. Still trying to hold onto it :).

автор: John C

Aug 19, 2018

A very nice introduction to the subject. Like in any other discipline one needs to practice in order to verify that you know the theory. Will continue signing up for more courses and specialitations. Very happy with the way things are going.

автор: Jude O

Oct 25, 2018

Excellent introductory material

автор: Gustavo I M

Nov 14, 2018

that was more difficult than last one, but its so important to take an overview about every think

автор: José G d A L N

Nov 16, 2018

Incredible

автор: Nick B

Nov 19, 2018

This is a good course to learn more about the big data environment and how things work within it.

автор: André G P

Nov 07, 2018

The course presents a conceptual basis behind each of the tools demonstrated. It is important to know the best options when designing a project.