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

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+.

RL
As a undergraduate data analytics student, this course was an enlightening experience that complemented my more theoretical, less-applicational on campus course very well.
RM
Interesting. Sometimes a little bit overwhelmed by a lot of information within a single video but it gives you an overview of what is big data modeling and management systems.
BR
It was a difficult module, although trainer tried to convey but seems it is more complex it took time for me to understand the concept and apply the same while doing my assignment.
DN
Pretty good overall, although some exercises are a bit difficult to understand from the descriptions and instructions given, some graphs and initial reference documentation for exercises might help
VC
The course provided me a good understanding of the tools and insights on how data could be modeled and managed. I feel confident that I can use the knowledge at work.
CJ
Great overview of a few databases and what they are good at. Would have liked actual hands-on like installing a database and demonstrating the key feature the database is good at.
MP
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.
BN
Was a very hands-on experience with the Hadoop ecosystem streaming and analysis of live tweets from twitter gave a general outlook on how to perform simple operations with the HDFS
SM
Gives us a very good understanding on Big data modeling and various data models like Graph Data model, Vector Space model (TF-IDF), Vertica, AsterixDB, Aerospike etc.
YG
Overall relevant and clear presentations. Course material quite general, but I guess this is expected from an introductory-level course.Peer-reviewed assignment's instructions can be clearer.
PP
If you have the fundamental knowledge of database and json, the only valuable videos for you are in week 5. As it says in next course(course 3), the course 2 is not required.
RP
This was an comprehensive learning experience that improved my technical skills and offered hands-on learning experience. The learning experience was truly worth it.