Very nIce

very good

Excelent.

very good

muito bom

Excellent

Excellent

Very Good

Muy bien

Perfect

Great!

G

r

e

a

t

great

good

Not as good as the first course in the big data specialization. The big data modeling part of the course was excellent in my opinion because it contained both theory and practice. However, the management systems were not covered adequately, with only one week in the course allocated to cover those topics. I remember how a few management systems are called and what they're good for, but I wouldn't feel confident to perform any practical tasks with big data management systems after finishing this course.

Still, I'd say it's worth taking the course if you want an overview of the most common big data models and management systems.

This material in this course seems to be based on a belief that the student has significantly more knowledge than assumed for the first course in the Big Data series. Because of this unfounded assumption, without regard to explanation, I have marked it down to four stars vice the five for the first course.

I think by providing the student with an adequate background, or additional resources, this course could easily be ranked as a five-star course.

In short, for no apparent reason, it quickly becomes more difficult than the first course; and instead, I wish it had been more of a natural transition from the first course.

Course material is very good. Instructors are great and talk clearly and explain well.

My only difficulty is with peer reviewed assignments. There is no answer key. So how one grades depends on what he/she thinks is the right answer. I understand there is no easy solution to this problem for online courses. It is not a show stopper though since you can submit multiple times. But why not just grade using Assistant or by instructor themselves.

All in all the course was very good as the first one. However it is not clear for me what I can do, if I feel myself unfairly graded by my peers at the Peer-Reviews. Furthermore it would be helpful, if the peers had to justify their grading by giving helpful comments to their grades. It is pretty discouraging doing the extra effort, when grading and receiving no constructive feedback at all. Therefore you should be able to challenge grading.

This course is a valuable introduction to Big Data Models and Management Systems for a variety of data types. The hands on exercises and company use case examples provide helpful context and application of the concepts. This knowledge also provides the learner with more confidence in navigating big data conversations in a professional environment.

I loved how it built on knowledge obtained from the previous course and even had a recap video as a reminder of what was covered then. My only real gripe is how the felt like a bit of a curved ball - it was tricky to understand what was required of us. Overall, the course content is solid and I would recommend it to anyone

The lectures and hands on material for this course deserve 5 stars. I did not like the peer review assignment as I thought it was unclear and that the review process is very inconsistent. That being said I have not liked peer review projects for any classes I have take on coursera so I would still recommend this class.

I enjoyed the lectures and liked the topics. Although I would like little bit more hands-on quizes. The "Designing a Big Data Management System for an Online Game" questions where unclear, probably if we had had more hands-on exercises throughout we would not be as confused as gain confidence.

This course captures the overview of Big data modelling concept in a very simple way. I found this course very useful. Instructors are good to explain the concepts. Though it would be good to add one or two (add-on or optional hands on exercises) handson for graph and tree data modelling.

Excellent intro to the subject. The instructors explain the material well. I deducted one star for the grading treatment of the Peer-Graded Assignment (Catch the Pink Flamingo). It's understood that there is no one "right" answer, but peers should be given a range of possible answers.

Another excellent course.

The only thing I would have liked (and maybe this comes later in the upcoming courses) is for the course to take a look inside the python and Lucence scripts so that we could be talked through how these are actually processing the data with guidance.