Students
MGNT837 – Big Data and Decision Analysis
2019 – Term 2 North Ryde
General Information
Download as PDF
| Unit convenor and teaching staff |
Unit convenor and teaching staff
PhD - Lecturer
Viken Kortian
|
|---|---|
| Credit points |
Credit points
4
|
| Prerequisites |
Prerequisites
32cp including MGNT604
|
| Corequisites |
Corequisites
|
| Co-badged status |
Co-badged status
|
| Unit description |
Unit description
This unit is a bridge between business and information technology and will equip students with the knowledge and skills required to help them utilise big data on projects. Specifically, the unit focuses on big data applications at both strategic and operational levels. More importantly, it focuses on transforming business processes and business models through big data and analytics, the impact of big data on companies’ IT infrastructure, the use of resources (especially human resources) to conduct big data analyses, and identifying the necessary technological underpinnings of big data and analytics. The unit is especially tailored for Masters of Management students with a primary focus on managerial discussions surrounding big data employment and decision-making using big data and analytics insights. The technical aspects of the unit are on a comprehensible and applicable level for management students.
|
Important Academic Dates
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
Learning Outcomes
On successful completion of this unit, you will be able to:
- Frame a research question based on an issue for a firm for which data is needed to make a decision
- Identify and select appropriate research methods to answer the research question
- Design and carry out a research project for a given business unit and make a recommendation based on data they collect and analyse
- Critically evaluate research proposals and results so that they are useful for business practice
Assessment Tasks
| Name | Weighting | Hurdle | Due |
|---|---|---|---|
| Contribution to class | 10% | No | All sessions |
| Group case study analysis 1 | 20% | No | 23:59 (Syd), 23 April 2019 |
| Group case study analysis 2 | 20% | No | 23:59 (Syd), 4 June 2019 |
| Final examination | 50% | No | Exam week: 10 - 15 June 2019 |
Contribution to class
Due: All sessions
Weighting: 10%
Contribution to class requires students to be actively engaged in class discussions of the cases and examples and lecturer’s presented material. To this end, students should be prepared in advanced so that they will be part of the active learning in the classroom. Class discussions by the students should be relevant to the topic and add value to the overall lecture quality. Sharing experiences from students’ working environment and extra-curricular activities relevant to class topics will have extra bonus points.
The marking criteria for this assessment will be made available in iLearn.
On successful completion you will be able to:
- Frame a research question based on an issue for a firm for which data is needed to make a decision
Group case study analysis 1
Due: 23:59 (Syd), 23 April 2019
Weighting: 20%
The assignment will involve using the methods and models discussed in lectures to solve decision-making problems that arise in the business context. Regarding the assessment criteria, students should demonstrate sufficient understanding of the theoretical principles in this unit, including data collection, model selection and design, application, and the ability to draw meaningful inferences based on the data and model output.
This group assessment will have 50% of the marks allocated to individual performance. The assignments may involve data analysis using computer tools, as well as draw on theoretical material from lectures. Students need to self enroll in groups of no more than five in the first week. There might be minor changes to group assignments by the end of session 3.
Students are to submit their assignment through iLearn on or before the due date. Further instructions on how to do this will be provided to students via iLearn.
Your submission should include:
- Responses to the questions should be included in one word document (including all relevant tables and figures and their explanations) and one excel (if necessary) file containing the decision tree and additional requested calculations discussed in class using Palisade software package.
- The word document above should also include in its first page a clear, written indication of the contribution of each group member to the project, i.e., by student name, exact contribution of each member.Your report will be graded only if this page is provided.
- No appendices are accepted.
The marking criteria for this assessment will be made available in iLearn.
Extensions and penalties:
No extensions will be granted. There will be a deduction of 10% of the total available marks made from the total awarded mark for each 24 hour period or part thereof that the submission is late (for example, 25 hours late in submission – 20% penalty). This penalty does not apply for cases in which an application for disruption of studies is made and approved. No submission will be accepted after solutions have been posted.
On successful completion you will be able to:
- Frame a research question based on an issue for a firm for which data is needed to make a decision
- Design and carry out a research project for a given business unit and make a recommendation based on data they collect and analyse
- Critically evaluate research proposals and results so that they are useful for business practice
Group case study analysis 2
Due: 23:59 (Syd), 4 June 2019
Weighting: 20%
Students will be given a case study to analyse the decision making process. It will be required to model the decision making process and provide suggestion to the firm based on the performed analysis and findings.
This group assessment will have 50% of the marks allocated to individual performance. Students will be evaluated based on their ability to justify the models applied, solve the problem under consideration, explain the findings and present their findings in a brief answer format. Group members for both assignments are the same.
Students are to submit their assignment through iLearn on or before the due date. Further instructions on how to do this will be provided to students via iLearn.
Your submission should include:
- Task responses containing discussion of the case, gap analysis, and recommendations in one word document (no more than 10 pages - including all relevant tables and figures and their explanations) and one excel file (if necessary) containing the decision tree and additional requested calculations discussed in class using Microsoft Azure software package.
- The word document above should also include in its first page a clear, written indication of the contribution of each group member to the project, i.e., by student name, exact contribution of each member.Your report will be graded only if this page is provided
The marking criteria for this assessment will be made available in iLearn.
Extensions and penalties:
No extensions will be granted. There will be a deduction of 10% of the total available marks made from the total awarded mark for each 24 hour period or part thereof that the submission is late (for example, 25 hours late in submission – 20% penalty). This penalty does not apply for cases in which an application for disruption of studies is made and approved. No submission will be accepted after solutions have been posted.
On successful completion you will be able to:
- Identify and select appropriate research methods to answer the research question
- Design and carry out a research project for a given business unit and make a recommendation based on data they collect and analyse
- Critically evaluate research proposals and results so that they are useful for business practice
Final examination
Due: Exam week: 10 - 15 June 2019
Weighting: 50%
At the conclusion of the unit, there will be an open book examination of 3 hours plus 10 minutes reading time. The final examination will concern all the material (class lectures, simulations and classroom discussions) from the entire unit. More details on the exam will be provided in class.
You are expected to present yourself for examination at the time and place designated in the MGSM examination timetable. The timetable will be available on 17 April 2019 at https://students.mgsm.edu.au/sydney-students/units/exams/
On successful completion you will be able to:
- Critically evaluate research proposals and results so that they are useful for business practice
Delivery and Resources
Required text
Lake P., Drake R. (2014). Information Systems Management in the Big Data Era. Springer International Publishing, ISBN (Hardcover): 9783319135021, ISBN (Softcover): 9783319355078, DOI: 10.1007/978-3-319-13503-8
Please note: The Coop Bookshop has advised us that this textbook has a 2-3 week delivery turnaround time from the time the order is made. It is highly recommended that students place their order of this textbook in advance.
Laptop and Azure software package
Students should go to the Microsoft Azure website and access the free Microsoft Azure AI & ML studio.
https://azure.microsoft.com/en-au/services/machine-learning-studio/
You should bring your laptop to every lecture.
Where to purchase textbook?
The Coop Bookshop
The Coop Bookshop is our main retailer for textbooks and other related academic material. For information on textbook prices and online ordering, please refer to The Co-Op Bookshop webpage at http://www.coop.com.au
Springer Online Website – Online store
This textbook is also available for order via the publisher’s online store. For information on textbook prices and online ordering, please refer to the Springer Online Website store at https://www.springer.com/gp/book/9783319135021.
eBook disclaimer
Please note that although this unit has an open book final examination, only hard-copy versions of this textbook will be allowed into the examination room. eBooks will not be allowed in the examination room, but you can however print your eBook out and bring the printed copy into the examination room. Students who wish purchase the eBook and have it printed must do so at their own expense. MGSM will not be providing printing services of eBooks.
Disclaimer: MGSM does not take responsibility for the stock levels of required textbooks from preferred retail outlets and other book retailers. While we advise our preferred book retail outlet, The Co-op Bookshop, of our maximum expected number of students purchasing specific required text each term, The Co-op Bookshop and other book retailers will make their own judgement in regards to their physical holding stock levels. To prevent disappointment if a textbook is out-of-stock, we highly advise students to order their textbooks as early as possible, or if the required textbook is currently out-of-stock, place an order with the book retailer as soon as possible so that these book retailers can monitor demand and supply, and adjust their stock orders accordingly.
MGSM iLearn
The web page for this unit can be found at: https://ilearn.mq.edu.au/login/MGSM
Unit Schedule
Students are required to attend all classes. Please only attend the class you are enrolled in as reflected in your e-Student account. This unit will be presented over 10 sessions as follows (The proposed program might be subject to some minor changes as the term progresses (TBA)).
| Class sessions are scheduled from: 6pm to 10pm of every Tuesday starting from 2 April 2019 (session 1) until 4 June 2019 (session 10). | ||
| Final exam week: 12 - 17 June 2019 (The exam timetable will be available on 17 April 2019 at https://students.mgsm.edu.au/sydney-students/units/exams/) |
|
Session |
Topics covered |
Required readings |
|---|---|---|
|
1 |
- Introduction to Big Data and Analytics (I) - Big Data Analytics Software and Platforms (I) |
Required textbook reading before class:
Allocated supplementary readings:
[1] Marr, Bernard. Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results (Kindle Location 659). Wiley. Kindle Edition. |
|
2 |
- The 9S Framework: Big Data and Strategy - Introduction to Data Science Framework |
Required textbook reading before class:
Allocated supplementary readings:
|
|
3 |
- The 9S Framework: Big Data and Strategy - Introduction to Data Science Framework |
Required textbook reading before class:
Allocated supplementary readings:
Class discussion question:
|
|
4 |
- The 9S Framework: Big Data, Structure and Style - Introduction to Microsoft Azure Platform - Microsoft Azure Case:
|
Required textbook reading before class:
Allocated supplementary readings:
|
|
5 |
- The 9S Framework: Big Data, Staff and Synthesis - Microsoft Azure Case:
|
Required textbook reading before class:
Allocated supplementary readings:
Class discussion questions:
|
|
6 |
- The 9S Framework: Big Data and Statistical Thinking - Microsoft Azure Case:
|
Required textbook reading before class:
Allocated supplementary readings:
[1] Laha A. (2016) Statistical Challenges with Big Data in Management Science. In: Pyne S., Rao B., Rao S. (eds) Big Data Analytics. Springer, New Delhi [2] Batra S., Sachdeva S. (2016) Managing Large-Scale Standardized Electronic Health Records. In: Pyne S., Rao B., Rao S. (eds) Big Data Analytics. Springer, New Delhi |
|
7 |
- The 9S Framework: Big Data, Systems and Sources - Microsoft Azure Case:
|
Required textbook reading before class:
Allocated supplementary readings:
|
|
8 |
- The 9S Framework: Big Data, Systems and IS (Information Security) - Technical Insights - Group Presentations |
Required textbook reading before class:
Allocated supplementary readings:
|
|
9 |
- Big Data Applications with Disruptive Technologies - Group Presentations |
Required textbook reading before class:
Allocated supplementary readings:
|
|
10 |
- Big Data Applications with Disruptive Technologies - Exam Preparation - Group Presentations |
Required textbook reading before class:
Allocated supplementary readings:
|
Policies and Procedures
Macquarie University policies and procedures are accessible from Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central). Students should be aware of the following policies in particular with regard to Learning and Teaching:
- Academic Appeals Policy
- Academic Integrity Policy
- Academic Progression Policy
- Assessment Policy
- Fitness to Practice Procedure
- Grade Appeal Policy
- Complaint Management Procedure for Students and Members of the Public
- Special Consideration Policy (Note: The Special Consideration Policy is effective from 4 December 2017 and replaces the Disruption to Studies Policy.)
Undergraduate students seeking more policy resources can visit the Student Policy Gateway (https://students.mq.edu.au/support/study/student-policy-gateway). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
If you would like to see all the policies relevant to Learning and Teaching visit Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central).
Student Code of Conduct
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/study/getting-started/student-conduct
Results
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
Student Support
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Student Services and Support
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
Student Enquiries
For all student enquiries, visit Student Connect at ask.mq.edu.au
If you are a Global MBA student contact globalmba.support@mq.edu.au
IT Help
For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.
When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
Graduate Capabilities
PG - Capable of Professional and Personal Judgment and Initiative
Our postgraduates will demonstrate a high standard of discernment and common sense in their professional and personal judgment. They will have the ability to make informed choices and decisions that reflect both the nature of their professional work and their personal perspectives.
This graduate capability is supported by:
Learning outcomes
- Design and carry out a research project for a given business unit and make a recommendation based on data they collect and analyse
- Critically evaluate research proposals and results so that they are useful for business practice
Assessment tasks
- Group case study analysis 1
- Group case study analysis 2
- Final examination
PG - Discipline Knowledge and Skills
Our postgraduates will be able to demonstrate a significantly enhanced depth and breadth of knowledge, scholarly understanding, and specific subject content knowledge in their chosen fields.
This graduate capability is supported by:
Learning outcomes
- Identify and select appropriate research methods to answer the research question
- Design and carry out a research project for a given business unit and make a recommendation based on data they collect and analyse
- Critically evaluate research proposals and results so that they are useful for business practice
Assessment tasks
- Group case study analysis 1
- Group case study analysis 2
- Final examination
PG - Critical, Analytical and Integrative Thinking
Our postgraduates will be capable of utilising and reflecting on prior knowledge and experience, of applying higher level critical thinking skills, and of integrating and synthesising learning and knowledge from a range of sources and environments. A characteristic of this form of thinking is the generation of new, professionally oriented knowledge through personal or group-based critique of practice and theory.
This graduate capability is supported by:
Learning outcomes
- Frame a research question based on an issue for a firm for which data is needed to make a decision
- Identify and select appropriate research methods to answer the research question
- Design and carry out a research project for a given business unit and make a recommendation based on data they collect and analyse
- Critically evaluate research proposals and results so that they are useful for business practice
Assessment tasks
- Contribution to class
- Group case study analysis 1
- Group case study analysis 2
- Final examination
PG - Research and Problem Solving Capability
Our postgraduates will be capable of systematic enquiry; able to use research skills to create new knowledge that can be applied to real world issues, or contribute to a field of study or practice to enhance society. They will be capable of creative questioning, problem finding and problem solving.
This graduate capability is supported by:
Learning outcomes
- Frame a research question based on an issue for a firm for which data is needed to make a decision
- Identify and select appropriate research methods to answer the research question
- Design and carry out a research project for a given business unit and make a recommendation based on data they collect and analyse
- Critically evaluate research proposals and results so that they are useful for business practice
Assessment tasks
- Contribution to class
- Group case study analysis 1
- Group case study analysis 2
- Final examination
PG - Effective Communication
Our postgraduates will be able to communicate effectively and convey their views to different social, cultural, and professional audiences. They will be able to use a variety of technologically supported media to communicate with empathy using a range of written, spoken or visual formats.
This graduate capability is supported by:
Learning outcomes
- Frame a research question based on an issue for a firm for which data is needed to make a decision
- Critically evaluate research proposals and results so that they are useful for business practice
Assessment tasks
- Contribution to class
- Group case study analysis 1
- Group case study analysis 2
- Final examination
PG - Engaged and Responsible, Active and Ethical Citizens
Our postgraduates will be ethically aware and capable of confident transformative action in relation to their professional responsibilities and the wider community. They will have a sense of connectedness with others and country and have a sense of mutual obligation. They will be able to appreciate the impact of their professional roles for social justice and inclusion related to national and global issues
This graduate capability is supported by:
Learning outcome
- Design and carry out a research project for a given business unit and make a recommendation based on data they collect and analyse
Assessment tasks
- Group case study analysis 1
- Group case study analysis 2
Changes from Previous Offering
Assessment tasks: None
Delivery and resources: None
Unit schedule: None
Alignment with MGSM's mission-driven attributes
Leadership: The unit develops quantitative skills required of leaders with respect to the wide range of techniques available to deal with array of information in order to make well-informed and robust strategic decisions.
Global mindset: The unit facilitates assessing the implications of strategic decisions from a whole of entity perspective, across of a national and international spectrum of stakeholders.
Citizenship: The unit applies an accurate and fair approach to deriving business strategies and disclosure of any difficulties or ethical issues that may arise from them.
Creating sustainable value: The unit promotes the adoption of a forward-looking perspective on the impact of qualitative decisions and how they may be readily adapted if parameters change in the future.
Attendance Policy (MGSM)
The interactive environment of the classroom is central to the MGSM experience. Students are required to attend the full duration of all classes for the units in which they are enrolled. We recognise that exceptional circumstances may occur, such as unavoidable travel on behalf of your organization or the serious illness or injury of you or a close family member.
Special consideration may be given for a maximum of 20% non-attendance for such circumstances as long as lecturers are contacted in advance, and supporting documentation provided, to request exemption from attendance. Failure to abide by these conditions may result in automatic withdrawal, with academic and/or financial penalty. The full Student Attendance Policy is published in the MGSM Student Handbook at https://students.mgsm.edu.au/handbook
Content Disclaimer
These unit materials and the content of this unit are provided for educational purposes only and no decision should be made based on the material without obtaining independent professional advice relating to the particular circumstances involved.