Work Hours
Everyday: 北京时间8:00 - 23:59
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 1 of 14
This exam paper must not be removed from the venue
Venue ________
Seat Number _
Student Number ||||||||| Family Name ___________
First Name ________
School of Information Technology and Electrical Engineering
EXAMINATION
Semester One Final Examinations, 2021
DATA7201 Data Analytics at Scale
This paper is for St Lucia Campus students.
Examination Duration: 120 minutes
Reading Time: 10 minutes
Exam Conditions:
This is a Closed Book examination – specified written materials permitted
No calculators permitted
During reading time – write only on the rough paper provided
This examination paper will be released to the Library
Materials Permitted In The Exam Venue:
(No electronic aids are permitted e.g. laptops, phones)
One A4 sheet of handwritten or typed notes single sided is permitted
Materials To Be Supplied To Students:
None
Instructions To Students:
Additional exam materials (e.g. answer booklets, rough paper) will
be provided upon request.
Students to answer Q1-Q7 in the space provided in the question paper.
Total marks = 100
For Examiner Use Only
Question Mark
Total _
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 2 of 14
Question 1. (14 marks)
Explain the benefit of the Shuffle phase in Map/Reduce.
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 3 of 14
Question 2. (14 marks)
Discuss why Apache Spark can be used for different big data problems (e.g.,
volume, variety, velocity).
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 4 of 14
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 5 of 14
Question 3. (14 marks)
Critically compare the functioning of Apache Storm and Apache Kafka.
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 6 of 14
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 7 of 14
Question 4. (14 marks)
Critically compare Apache Giraph and Spark GraphX for large data graph
management.
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 8 of 14
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 9 of 14
Question 5. (14 marks)
Discuss the advantages and disadvantages of unsupervised and supervised opinion
mining approaches also including scalability issues.
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 10 of 14
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 11 of 14
Question 6. (15 marks)
Discuss the following scenario describing the type of data infrastructure you would
adopt and why. The scenario description below does not provide all the necessary
details. You will need to describe your assumptions on the scenario to complement
the information given to you. Describe the assumptions you are making in terms of
data availability, analytics queries of interest, user expertise and requirements. 1)
discuss your assumptions, 2) outline the design of your data infrastructure solution
(i.e., which data, which systems, which users, etc.) and, 3) justify your solution.
Scenario: A metropolitan hospital needs to store data about their patients, staff, and
physical resources like medical equipment, furniture, and other assets. The aim is to
design and deploy a data solution that can support analytics over such data and may
inform decision making processes (e.g., need for more ICU beds, more staff required
to be available at a given point in time).
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 12 of 14
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 13 of 14
Question 7. (15 marks)
Discuss the following scenario describing the type of data infrastructure you would
adopt and why. The scenario description below does not provide all the necessary
details. You will need to describe your assumptions on the scenario to complement
the information given to you. Describe the assumptions you are making in terms of
data availability, analytics queries of interest, user expertise and requirements. 1)
discuss your assumptions, 2) outline the design of your data infrastructure solution
(i.e., which data, which systems, which users, etc.) and, 3) justify your solution.
Scenario: A national government needs to decide an investment strategy to
support public health; they are looking for data that can inform their decision
about how much to invest from a fixed budget into a) hospital infrastructure; b)
healthy lifestyle campaigns (prevention); c) research on new treatments
(correction).
Semester One Final Examinations, 2021 DATA7201 Data Analytics at Scale
Page 14 of 14
END OF EXAMINATION
https://my.uq.edu.au/programs-courses/course.html?course_code=DATA7201
