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Learner Reviews & Feedback for Big Data Modeling and Management Systems by University of California San Diego

4.4
2,158 ratings
352 reviews

About the Course

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+....

Top reviews

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)

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76 - 100 of 342 Reviews for Big Data Modeling and Management Systems

By Sayed T S

Apr 13, 2017

It was a great course from the best place in the world and best instructors .

By laksh b

Feb 19, 2017

excellent course

By Jose R O

Jun 29, 2018

Very nIce

By Arindam B

Mar 14, 2018

Very well defined course curriculum and easy to follow.

All the different aspects of big data modeling has been well discussed and presented with examples.

By igor s

Dec 18, 2016

Simply another great course within Coursera courses, thank you very much.

By Tamás B

Aug 14, 2016

Interesting course :)

By Samir G

Nov 21, 2016

Very helpful

By jose l

Feb 15, 2017

Very Good course

By Guillermo A A N

Jun 28, 2017

Well done and explained

By Divya A P

Jul 08, 2018

Enjoyed the Learning experience. The Hands on Ex

By Mars W

Feb 23, 2017

good course

By Ashenafi

Jul 06, 2017

well organized and precise hands on exercises that helped me to understand the subject in detail.

By Ali A

Mar 01, 2018

It was an informative course, contents of the course were good

By Fernando M

Apr 20, 2017

Excellent course, clear explanations and attention to details.

By andrehmerli

Nov 06, 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.

By Mohamed F

Mar 14, 2017

very nice and interesting course i recommend it for anyone start new in big data

By Sita R P G

Oct 24, 2016

Modeling is the start and gives an insight how to choose the correct model for a big data project. The correct choice of the model spells success for the project. Many data models were introduced and the hands-on exercises were helpful in better understanding of the concepts.

By Raunak S

Mar 14, 2018

great course for those who wish to go beyond the basics of big data.

By Akshay V

Jul 17, 2017

The Course was Awesome. It enhanced and enriched my knowledge and was overall fruitful in learning the nuances of Big Data.

By Jitender S V

Jun 21, 2017

GREAT COURSE!!

By Selim S

Nov 02, 2016

LEarned a lot, wasn't easy but it was manageble for someone like me who has no IT background

By Pankaj G

Dec 19, 2017

Good course, fairly detailed.

By YEVHEN K

Jan 16, 2018

I like it!

By Ben W

Nov 11, 2016

Excellent

By DONGMO M

Aug 08, 2017

Very useful course.

Needed only one week to finish the course even though I'm working full time.