Chevron Left
Back to Big Data Modeling and Management Systems

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

4.4
2,127 ratings
347 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)

Filter by:

301 - 325 of 336 Reviews for Big Data Modeling and Management Systems

By Stanislav D

Jan 24, 2019

Final task has numerous problems ranging from Coursera site formatting limitations that have not been accounted for to lack of master-answer to peers (e.g. peers unfamiliar with industry can't grade what they don' know)

By Enric P C

Feb 08, 2019

I have found this course less attractive to follow than other Big Data courses

By Raivis J

Feb 11, 2019

Some topics swing wildly from high level to very technical or in-depth math, which in my opinion is not needed, this is not a DB administrator course.

The hands-on exercises seemed loosely connected to the course topics. I would have liked to see practical tasks based on real-life problems and situations in big data applications.

The final graded assignment is for someone completely new to the concept of databases, and has no relation to big data, or tools used in big data, which is unfortunate.

By Lucas A H

Jan 19, 2019

Too simple for a persona that's already in the BI industry

By Izabelle A

Apr 11, 2019

Cannot finish Twitter activities as commands shown in the video apparently don´t work with the most recent pyhton version. I am very disappointed about it, since I am mostly focused on Twitter-related data.

By Zaher A H

Jun 22, 2017

The course is not structured well. I hope if the course provides the skills needed to build noSQL data models such as Columnar - KV - Graphical etc. but the course keeps jumping from notion to notion with no clear and smooth structure.

The lecturer presentation style is terrible.

By Kaddoum R

Nov 16, 2016

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

By Isaac L

May 07, 2018

The quizzes tested superficial knowledge, and basically just required you to memorize bullet points from the slides. The final project had incredibly confusing instructions, and the discussion forums didn't really clear anything up. The course materials seem to be about 5 years old, and I'm sure a lot has changed in terms of tools and technologies since then.

I've learned some useful information from this series of classes, but it doesn't seem like much effort was put into the content beyond the lecture videos.

By Erik P

Oct 03, 2017

I think some real polish needs to be applied to the final assignment in this course. Some of the questions are not formatted well for the coursera web site.. and even on my macbook pro retina I am seeing text overrunning the text box. Really want to see UCSD represented better

By David S

Feb 03, 2017

I don't feel this course is always very clear. I Feel that I usually am missing the big picture. I follow it in details, but the pace does not match in terms of how you can view the big picture of it.

By Nimal J K

Jan 10, 2017

The course content was not very appealing. Explanations were not that engaging. What I really missed was the actual practical aspect where you don't work with command prompt but an much more user friendly interface that is more up to date with current standards.

By Riccardo P

Apr 20, 2018

Barely an introduction, it could be somehow merged with the course #1

By Robert H

Sep 09, 2017

Tedious exercises through VM where instructions oftentimes do not work out of the box. It is a hassle to download the slides in small sets and their design awful. Definitely one of the worse courses I have taken.

By Jens L

Nov 17, 2017

It's too superficial and the required skill level and required background knowledge is changing from video to video. Especially the walkthrough of different named database systems, was to deep, and I didnt get much out of that. I was like if you just like trying to teach me how to operate my tv by walking through the complete manual from start to end. I was often wondering, how is this relevant in this module...

By Francisco J

Aug 06, 2017

Lectures are not really useful for real examples. Indeed final task related to the graphs is not explained in the lectures about how to declare properties for nodes/edges in a graph.

By akhil r k

Oct 24, 2016

I wish the courses are more project oriented. This is a very good introduction but, atleast you could provide some optional projects or some tasks.

By Guillaume V

Jun 16, 2017

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

By James K

Feb 11, 2017

Too simple, no programming, just theory.

By Ryan H

Jun 07, 2017

My primary concern with this course are the mentors and the final assignment. The final assignment was particularly vague in exactly what it wanted and when asked on the forum, mentors would respond with comments like "you should just understand it." The mentors through each week were altogether unhelpful and that culminated in a vague final assignment with little way to understand it without a bit of guessing.

By Hendrik B

Dec 17, 2017

Sorry, but I don't think this is a very good course. Here are some reasons why: The time said to be needed for the course is artificially increased, because there are ten minutes appraised for each set of lecture slides. At the end, there is almost no reading material, which is not obvious when looking at the course at the start. I think this is almost fraud. Ultimately, there are basically only lectures, no other media to learn, except for some multiple-choice quizzes. There are Coursera courses which are way more diverse. Additionally, the lectures are not particularly good (not speaking of the horrible design and colouring). Especially, when talking about some examples for BDMS, it is difficult to follow because some of the concepts have not been explained properly prior to that. The quizzes are not very good, and it is very obvious that there is not much thought behind the answer options. Also, for the quizzes you almost exclusively need to memorize learned stuff, but not to transfer knowledge or to apply knowledge). The final exam was a joke, because there was NO attempt by the supervisors to give students some intuition about the right answers after they submitted. Still, they were expected to rate others’ submissions. Meaning, when you didn't know how to answer a question, you were still expected to rate others submissions. Seriously? In general, so far it feels like the lecturers attempted to make a shallow course for a big topic, meaning big data, in order to get some money (after all: it is expensive to earn a course certificate). There are courses on other topics (e.g. “Game Theory” by Stanford University, where the quizzes are relatively hard but you get a feeling that you learn something, “Improving your statistical inferences” by Eindhoven University, which has many different media to learn, not just lectures, and has exceptionally good quizzes, as well as “Bayesian Statistics: From Concept to Data Analysis” by Santa Cruz University, which has very modern style of presenting the lecture). Sorry, but I think this course needs improvement, especially since the topic is so important.

By Othmane B

Nov 12, 2016

The course a materials are interesting and with significant value, same comment on the teachers, this would be perfect if the third party(the VM) is working fine, I can't say I'm happy about the course where the frustration is probably the right word describing my feeling right now, wish me luck for this week, I might pass might not ......

By Irfan S

Sep 26, 2017

Very basic and lack real time

By NOVELLA P

Oct 12, 2017

Course content clear and concise- but assignment directions were too open to interpretation. Also presentation of the assignment results for review where the answer was requested in table format the table overrides the scoring section and the visibility of the responses appeared scrambled. Peer review on week 6 assignment needs a rethink-this need some process of challenge where a mentor or instructor can intervene to correct faulty peer reviews

By Joaquim P

Jun 11, 2019

Too simple.

By Deleted A

Aug 30, 2018

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