Hadoop
Big Data Systems and Analytics
Coursework Exercises on the design of (big data) system architectureslength: 2,000 words equivalent)
Exercise 001 Big Data Systems
Each group will define a data-rich topic for which data resources are benchmarked or evidenced availability. The topic should be captured in a problem statement that will describe data resource(s) and data capture, storage and processing challenges.
This will be a combined group exercise with each member of the group taking one system for critical assessment, and then the group will provide a critical review of the state of the art big data solutions relevant for the topic of choice, and a critical evaluation of each individual work into a comparative summary document.
Each group member is required to review one of the (big data) systems available for the big data applications nowadays (such as in the Kovacs comparison
(https://kkovacs.eu/cassandra–vs–mongodb–vs–couchdb–vs–redis) and relevant for the group topic.
Requirements: A non-exclusive list of areas to be covered would be:
Problem statement and specifications;
Architecture, platforms and availability of the system;
Language(s) it is available in and can work with;
Existing users and use areas;
Critical Review of documentation and support for the system;
Review of others comments/experiences of the system;
Your own experience of downloading/building the system and using it with a data set that shows big data features (with evidence).
Any other issues such as: ethical, security, data protection features and coverage.
Examples and facts could be attached as appendices.
COS7006-B Big Data Systems and Analysis CW001 Marking Scheme
Criteria
A: 70-100%
B: 60-70%
C: 50-60%
D: 40-50%
E: 0-40%
Specifications,
Background, Introduction, literature
[10]
Excellent report structure, review of the problem domain.
Good structure. Well-performed review of the problem domain.
Sensible structure. review of the problem domain.
Reasonable structure.
Some review of the problem domain.
Weak review of the problem domain.
Details of each system
[40]
Evidencebased system approach
[10]
Excellent and consistent
critical evaluation of strengths and weaknesses including own and others assessments.
Good and consistent critical evaluation of strengths and weaknesses including own and others assessments.
Some
evaluation of strengths and weaknesses including own and others assessments. Less consistent approaches across systems
Some
coverage of system design, deployment and any issues.
Inconsistent approaches across systems
Poor coverage of system design, deployment and any issues. Inconsistent approaches across systems
Comparative
Evaluation
[20]
Excellent comparison of the systems.
Good comparison of the systems.
Some
comparison of the systems.
Limited comparison of the systems.
Weak or no comparison of the systems.
Other
Academic or
Industry
(White) Paper
Writing
Features
[10]
Excellent conclusion and references.
Good conclusion and references.
Some conclusion and references
Weak conclusion and references.
No conclusion or references.
Other TeamBased Issues
[10]
Excellent contribution and engagement.
Good
contribution and engagement.
Some
contribution and engagement.
Weak
contribution and engagement.
No evidence of contribution and engagement.
2
Data is from kaggle.com and the medical cost personal datasets.
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