ITECH7407 REAL TIME ANALYTICS

ITECH7407 REAL TIME ANALYTICS

Semester 2019/17 TEAM ASSIGNMENTS

1. TASKS, DUE DATES AND WEIGHTINGS

Assessment Attribute	Task 2: Research Report Presentation (Team)	Task 3: Research Report (Team)
Due Date	Week 8 (During tutorials/lab)	15 Sept 2019, 5pm
Learning                       outcomes assessed	K4, K5, S1, A1, A2, V1, V2	K1, K2, K3, K4, S1, A1, A2, V1, V2
Weighting	10%	15%

Details of the intended learning outcomes assessed can be found in the course description.

B.      INSTRUCTIONS

Under the leadership of the lecturer or/and tutor, students are expected to work on this two-part project or assignment (i.e. Task 2 and Task 3) in teams of 3 to 5 members. Each team shall choose one of the topics listed in Section C of this document. Both the team presentation and the team research report shall be based on the same topic. The following are the deliverables in this project:

1. Each team is expected to choose one of the topics listed in the next section, research thoroughly on it and write a research report of about 3000 words.
   1. Each report should reference a minimum of 15 peer-reviewed journal articles and conference papers.
   1. The report should be well researched and written in accordance with APA referencing style.
   1. Each team should clearly discuss different aspects of the chosen topic and how these aspects collectively enhance the theoretical and practical knowledge.
   1. Final deliverable consists of a presentation and a research report following the schedule above.
   1. Presentation of your findings in this project would be of about 20-minute

duration.

• Declaration of contributions: Each student must speak during the presentation part of the assignment. Also, each team must clearly state on the second page of the submission (after the cover page) the contributions of each team member in the project in a tabular form according to the format:

Student ID	Student Name	Contrib utions to Project

Lecturers/tutors reserve the right to reduce a student’s mark if their contribution to

their team project is deemed insubstantial.

• You are reminded to read the “Plagiarism” section of the course description. Your submission should be a synthesis of ideas from a variety of sources expressed in your own words.
  • All reports must use the APA referencing style. Federation University has published a style guide to help students correctly reference and cite information they use in assignments (American Psychological Association or APA) citation style, which can be found at http://www.ballarat.edu.au/aasp/student/learning_support/generalguide/ print/ch06s04.shtmlor Australian citation style.
  • Both power point slides for the team presentation and the team report must be submitted on Moodle by the respective due dates. Reports should use Arial Font with size 12pt and double spaced. Your report should include a list of references used in the essay and a bibliography of the wider reading you have done to familiarize yourself on the topic.
  • A passing grade will be awarded to assignments adequately addressing all assessment criteria. Higher grades require better quality and more effort. For example, a minimum is set on the wider reading required. A student reading vastly more than this minimum will be better prepared to discuss the issues in depth and consequently their report is likely to be of a higher quality. So before submitting, please read through the assessment criteria very carefully.

C.      ASSIGNMENTS TOPICS

Each team is expected to choose ONLY one of the following topics for both parts of the assignment:

1. A relevant industry application of real-time analytics
   1. Challenges and potential solutions in real-time big data analytics
   1. Real-time Big Data privacy
   1. Real-time Big data governance
   1. Strategic issues stemming from business intelligence, business analytics and big data
   1. Change management issues stemming from business intelligence, business analytics and big data

D.      REFERENCES AND RELATED WORK

Each team is expected to source and cite appropriately at least 15 journal and conference papers related to their chosen topic. Below are some references which can be of help:

1. Tseng, F-H., Hsueh, J.-H., Tseng, C.-W., Yang, Y.-T., Chao, H.-C., & Chou, L.-

D. (2018). Congestion Prediction With Big Data for Real-Time Highway Traffic. IEEE Access, 2018(6), 57311 – 57323.

• Ranjitha, P. (2015). Streaming Analytics over Real-Time Big Data. Global Journal of Computer Science and Technology: Software & Data Engineering, 15(5), 26-30.
  • He, Y., Yu, F.R, Zhao, N., Yin, H., Yao, H., & Qiu, R.C. (2016).                                                                                                   Data Analytics in Mobile Cellular Networks. IEEE Access, 2016(4), 1985–1996.
  • Constantiou, I. D., & Kallinikos, J. (2015). New games, new rules: big data and the changing context of strategy. Journal of Information Technology, 30(1), 44-57.
  • Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly, 36(4), 1165-1188.
  • Ketter, W., Peters, M., Collins, J., & Gupta, A. (2015). Competitive Benchmarking: An IS Research Approach to Address Wicked Problems with Big Data and Analytics. MIS Quarterly. (forthcoming)
  • McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data. The management revolution. Harvard Business Review, 90(10), 61-67.
  • Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., and

Byers, A. H. 2011. “Big Data: The Next Frontier for Innovation, Competition,                      and                         Productivity,”               McKinsey    Global                         Institute. http://www.mckinsey.com/business-functions/business- technology/ourinsights/big-data-the-next-frontier-for-innovation; access on 4 March 2016.

• Kallinikos, J., & Constantiou, I. D. (2015). Big data revisited: a rejoinder. Journal of Information Technology, 30(1), 70-74.
  • McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data. The management revolution. Harvard Business Review, 90(10), 61-67.
  • Kallinikos, J., & Constantiou, I. D. (2015). Big data revisited: a rejoinder. Journal of Information Technology, 30(1), 70-74.
  • Sharma, R., Mithas, S., & Kankanhalli, A. (2014). Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations. European Journal of Information Systems, 23(4), 433-441.

Assessment Criteria for Team Report – 100 Marks (15%

Weighting)

Student IDs:

Score	Very Good	Good	Satisfactory	Unsatisfactory (0)
Presentation	Information is well	Information is	Information is somewhat	Information is
/Layout	organized, well written,	organized, well written,	organized, proper	organized, but proper
	and proper grammar	with proper grammar	grammar and	grammar and
	and punctuation are	and punctuation.	punctuation mostly	punctuation not always
	used throughout.	Correct layout used.	used. Correct layout	used. Some elements
/05 marks	Correct layout used.		used.	layout incorrect.
Structure	Structure guidelines	Structure guidelines	Structure guidelines	Some elements of
/10 marks	Enhanced	followed exactly	mostly followed.	structure omitted
Introduction	Introduces the topic of	Introduces the topic of	Satisfactorily introduces	Introduces the topic of
	the report in an	the report in an	the topic of the report.	the report, but omits a
	extremely engaging	engaging manner which	Gives a general	general background of
	manner which arouses	arouses the reader’s	background.	the topic and/or the
	the reader’s interest.	interest.	Indicates the overall	overall “plan” of the
	Gives a detailed general	Gives some general	“plan” of the paper.	paper.
	background and	background and
	indicates the overall	indicates the overall
/10 marks	“plan” of the paper.	“plan” of the paper.
Discussion of	All topics discussed in	Consistently detailed	Most topics are	Inadequate discussion
Topics	depth. Displays deep	discussion. Displays	adequately discussed.	of issues Little/no
	analysis of issues with	sound understanding	Displays some	demonstrated
	no irrelevant info.	with some analysis of	understanding and	understanding or
		issues and no irrelevant	analysis of issues.	analysis of most issues
		Information		and/or some irrelevant
/50 marks				information.
Conclusion	An interesting, well	A good summary of the	Satisfactory summary of	Poor/no summary of the
	written summary of the	main points.	the main points.	main points.
	main points.	A good final comment	A final comment on the	A poor final comment
	An excellent final	on the subject, based	subject, but introduced	the subject and/or new
	comment on the	on the information	new material.	material introduced.
	subject, based on the	provided.
/15 marks	information provided.
Referencing	Correct referencing	Mostly correct	Mostly correct	Not all material correctly
	(APA). All quoted	referencing (APA). All	referencing (APA )	acknowledged.
	material in quotes and	quoted material in	Some problems with	Some problems with
	acknowledged. All	Quotes & acknowledged.	quoted material and	reference list.
	paraphrased material	All paraphrased material	paraphrased material
	acknowledged.	acknowledged.	Some problems with the
	Correctly set out	Mostly correct setting	reference list.
/10 marks	reference list.	out reference list.
SubTotal-/100 marks
Total out of 15

Assessment Criteria for

Team Report Presentation – 100 Marks (10% Weighting)

Student IDs:

Each team report presentation shall last 10-20 minutes. The following shall be used to assess and grade the presentations.

Criteria	Marks
Introduction	/10
Content	/40
Conclusion	/10
Presentation Style e.g. clarity, engagement	/20
Team participation	/10
Timing (10-15 minutes)	/10
SubTotal-2	/100
General Comments:

Team assignment Total = SubTotal-1 + SubTotal-2.