Welcome to the Visualization Course in Master of Science in Business Analytics Program. The aim of this assessment is to develop your ability to appraise a detailed body of knowledge of recent developments in data visualization and utilize highly developed specialist communication and information technology skills to present, explain and/or critique highly complex matters related to data visualization. Additionally, this assessment will develop your critical awareness of knowledge issues in data visualization. You also will be able to experiment with advanced problem-solving to analyze high complex issues with data.
In this assessment, you should be able to:
CLO1: Critically appraise a detailed body of knowledge of recent developments in data visualization and utilize highly developed specialist communication and information technology skills to present, explain and/or critique highly complex matters.
CLO2: Develop a critical awareness of knowledge issues in data visualization as the basis for original thinking; encompassing current processes of knowledge production
CLO3: Build advanced skills required in research, analysis, evaluation of complex ideas, information, concepts and/or activities related to data visualization.
The Course Learning Outcomes (CLOs) indicated above are mapped to your overall (MSQBE) Program Learning Outcomes (PLOs). This assessment tests your achievement in the program with reference to the following PLOs:
PLO1: Demonstrate a critical awareness of current issues in Business Analytics. PLO5: Appraise the application of business analytics in solving business issue
Please see Annex C for the detailed description. Knowledge: KN1, KN2, KN3, KN4.
Skills: SK1, SK3, SK4.
Areas of Competency: AR1, AR3, RC1, RC2, SD1, SD3.
The assessment will test the acquisition by the student of Core Life Skill (CLS) indicated by the CAA within the teaching framework of the overall course. CLS acquired on this course are the following:
Information Collecting, analysing, organising and applying information in a given context
Mathematical/Problem Solving Solving problems including using mathematical ideas and techniques
Technology (ICT) Applying information and communication techniques
6. Assessment Requirement
Data Visualization is important step in analytics, because it allows trends and patterns to be more easily seen. With the rise of big data upon us, we need to be able to interpret increasingly larger batches of data The students are requested to collect their own data from appropriate data sources. Once collected, the students are asked to do the following:
1. Appraise your chosen data set by providing full description of its business domain. Clear citation on your source of the information is necessary. (CLO1,5 marks)
2. Develop two different business scenarios that describe alternative perspectives on your chosen data set. These scenarios should emphasize your understanding on exploratory and explanation analysis used. (CLO1,5 marks/CLO2,5 marks)
3. Construct two different visualizations on each scenario developed in part 2. Your proposal should evaluate the effective use of the in-class taught concepts such as calculated field and condition field. You must also include either pattern detection or prediction. (CLO2,20 marks)
4. Construct a dashboard to show all previously developed visualizations. With clear justification, critically evaluate the design concept/s used in your proposal (CLO3,10 marks)
5. With reference to scenarios and findings provided in your above answers, appraise literature review on similar cases to compare the different visualization method/s used by these cases against your above answers. (include your citation). ( CLO3,15 marks)
As a GUIDE ONLY, this section outlines some of the aspects you may consider significant given the brief shown above. Your report should include:
1. Executive Summary
2. Answers to the previous questions (1 to 5)
3. Conclusion
One (electronic) copy to be submitted. Please use a front sheet, (Annex A) and include a blank assessment discussion form (Annex B). (State method: online submission portal)
• You will be allocated 3 hours to complete this assessment.
• Insert your name and surname in the file name. Save the file as: First name Surname S1/S2 Course Name – e.g. Muhammad Usman S2 OM. NB: Please ensure that you use the name that appears in your student profile on the LMS.
• Write your complete Student ID number, your complete name as per registration, course name, instructor’s name, and date.
• Write your assignment using Microsoft word document and upload on the LMS Turnitin before the deadline.
• Note that the plagiarism limit is 15%.
Standard academic presentation is required, including:
• Concise and appropriate language
• Fully referenced using the (APA) method, containing all sources used for each piece of work (if applicable)
• Avoid unnecessary cutting and overwriting where applicable.
Wilke, C. O. (2019). Fundamentals of data visualization: a primer on making informative and compelling figures. O'Reilly Media
1. Enter below the Student Name, Student ID Number, Cohort & Section, Course code, Course Name, Instructor’s Name, and Term in which the course was taken e.g. Spring 2020.
2. Attach this Cover Sheet as the front page of the assessment.
3. Remember to keep a copy of this assessment.
By submitting this coversheet electronically, I confirm that the assessment I am uploading is work that I have completed, with the exception of the work of others that I have referenced. This assessment, or major parts of it, has not been submitted for any other academic studies I have undertaken. I also confirm that I am aware of what constitutes plagiarism, and I understand the penalties imposed should plagiarism be detected. The format of submitted files must be in compliance with the Turnitin requirements.
In recognition of the above, I verify that I am aware of ADSM’s Academic Integrity Policy and pledge to fully comply with its principles.
Plagiarism is a form of academic dishonesty. It is taking and using someone else’s thoughts, writings or inventions and representing them as your own without giving credit to the original author(s).
If you have any doubts about how to refer to the work of others in your assessment, please consult your instructor or contact Academic Support for relevant referencing guidelines. The intentional copying of someone else’s work as one’s own is a serious offence and may result in penalties including deduction of marks, or failing the course. Refer to the course syllabus and ADSM P418 Student Academic Integrity Policy for further information on plagiarism and associated penalties.
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