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.
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)
par Srinivas B•
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par Mayank c•
par Lisbeth R S•
par boulealam c•
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par Drew G•
The information provided is solid, but this entire specialization has issues with the peer-graded assignments. The assignments themselves are good, open-ended questions designed to test your grasp of the concept being taught. The problem is the grading rubrics and the peer-review aspect. Where the questions are open-ended, the rubric often is not, demanding that only one of the possible answers be reached, or that a conclusion be reached in their specified manner. This leads to submitting the assignment, review other assignments to see what the rubric actually wants you to do, then resubmitting your assignment after you've reverse engineered the "right way" to do it to pass peer-review.
But there's only one or two of those per course, and are a relatively minor annoyance compared the good information being communicated.
par Aleksandar R•
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.
par Wayne S•
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.
par Bhanu H•
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.
par Johannes V•
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.
par Nikhil C•
Overall a good course to get the basics of what the difference is between managing Big Data system, versus your more traditional systems. I really like both instructors.
I took one star off because one of the twitter API assignments that we were supposed to do in the VM didn't work. Plus there's no one to support you in case an issue like this occurs.
par Don M•
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.