Unit convenor and teaching staff |
Unit convenor and teaching staff
Lecturer
Nejhdeh Ghevondian
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Credit points |
Credit points
4
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Prerequisites |
Prerequisites
MGSM960
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
This unit is a bridge between business and information technology and will equip the students with knowledge and skills required to lead and manage big data projects. Specifically, the unit focuses on big data applications on both a strategic and operational level. More importantly, this unit focuses on how business processes and business models may be transformed 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 identify the necessary technological underpinnings of big data and analytics. The unit is especially tailored for MBA students and business managers with a primary focus on managerial discussions surrounding big data deployment and decision making using big data and analytics insights within large companies. The technical aspect of the unit is on a level comprehensible and applicable by Masters level management students who do not necessarily possess technical training in big data software applications.
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Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Name | Weighting | Hurdle | Due |
---|---|---|---|
Individual Assignment | 25% | No | 11:59pm, 22nd May 2019 |
Group Assignment | 35% | No | 11:59pm, 7th June 2019 |
Final Examination | 40% | No | Exam Week 10 - 15 June, 2019 |
Due: 11:59pm, 22nd May 2019
Weighting: 25%
Length:
Format: Case discussion participation and report
Due: Submission in iLearn on or before 11:59pm (Sydney Time) of Wednesday 22nd May 2019
Weighting:
Students will be required to:
Class contribution: A good class contribution entails active participation in class discussions and adding value and direction to the discussions by sharing student’s insights and work experiences relevant to the subject matter. Moreover, student’s active participation and contribution to group case discussions in class is another aspect of class contribution. Your mere presence in class and/or e-mail exchanges with your lecturer is not construed as components of class contribution. Students should also be fully prepared with the assigned readings for each session before coming to class and lack of preparation would deduct from their class contribution mark.
The date of submission is planned after the end of the course to ensure students have the opportunity to review all of the material covered in the subject. Students are required to select and make use of topics studied in class in order to (1) draw links to a chosen organisation’s function, department or operation, (2) conduct a gap analysis and (3) elaborate a detailed action plan designed to improve the organisation’s application of big data and analytics to gain insights and profits over a period of 6 – 18 months.
It is highly recommended the chosen organisation be the student’s most recent employer to ensure the assignment is kept real and practical. The report should be written in a concise manner and should be structured in the following way:
Report format
Case study reports should be typed single-spaced, with normal margins, and Times New Roman 12pt font. Clarity and structure are critical elements of success. Use the available pages wisely and forego dwelling on defining terms that are obvious and already known. The report should be written as a professional business type of report, reflecting its practicality, applicability and relevance to the business.
Submission details
Students are to submit 1 x soft-copy of their individual report on or before the due date as listed in the box above. The soft-copy submission will be submitted to Turnitin via the MGSM913 iLearn portal, a program used to ensure the originality of the work undertaken by the submitter.
Only ONE single file must be submitted with ALL attachments, displays and charts included within. This can be submitted as a Microsoft Word document (.docx or .doc) or Microsoft PowerPoint presentation (.pptx or .ppt). No file attachments, other than the single Microsoft Word file or single Microsoft PowerPoint presentation will be assessed (please ensure all charts are placed in the one Microsoft Word file).
Please ensure your full name, student number, unit code (MGSM913), unit name (Big Data and Managerial Decisions), and lecturer (Nejhdeh Ghevondian) is clearly visible on the front page of your assignment. No MGSM individual assignment coversheet is necessary.
Late assignments will be penalised 10% per each day delay* unless you have applied for special consideration, and that application is considered acceptable. Applications for extensions must be made before the submission date, and will only be granted in exceptional circumstances.
*For instance if the deadline for submission is 5:00 pm of 1st of June, and the submission happens 5:01 pm of 1st of June, this is considered as one day delay and subject to 10% of total mark deduction.
Due: 11:59pm, 7th June 2019
Weighting: 35%
Length:
Format:
Due:
Weighting:
Please note: Syndicate groups will be assigned by the lecturer on the first day of class. Groups might experience minor changes up until the third week after the start of the term.
Group assignments’ format are similar to industrial thought leadership papers with no more than 6000 words in total including cover page in the beginning and the references and supplementary information at the end of the paper. The formatting and design of the papers are at the discretion of the students. Important: The criteria for marking the papers include: readability of the report, value-adding information, and creativity in delivering the content and generating new knowledge, extent of the cover of the literature, standard formatting based on industrial benchmarks, and design of the paper.
Each syndicate group will be assigned a topic by the lecturer once the groups have been formed. A list of some possible topics for investigation is included in the table below.
The deadline for submitting the thought leadership paper is the final exam.
Only one PDF file should be submitted through Turnitin platform in iLearn by the group representative.
Each syndicate group will be required to present the summary of their thought leadership paper in class: (1) the duration of the presentation is no more than 20 minutes with Q&A from the class, and (2) there is no need to submit the hard or soft copy of the presentation. Important: The criteria for marking the presentations are: engaging the audience, introduction to the problem, and seamless flow of presentation (What? Why? How?), maintaining eye contact, satisfactory response to the questions asked by the audience, effective time management in presenting the slides and in Q&A, and design and animations used in the slides. There are no limitations in the number of slides. **All members of the group are required to present**
Syndicate
group
Examples of big data and analytics topics for the group assignment
1
Big data applications in marketing processes
2
Big data and the future of supply chain management
3
Big data and optimizing quantitative decision-making models
4
Big data analytics and re-defining current statistical models
5
Big data and banking and finance
6
Big data and healthcare
7
Big data and customer relationship management
8
Big data and business process management
9
Big data and text mining applications
10
Big data and predictive maintenance
Late assignments will be penalised 10% per each day delay* unless you have applied for special consideration, and that application is considered acceptable. Applications for extensions must be made before the submission date, and will only be granted in exceptional circumstances.
*For instance if the deadline for submission is 5:00 pm of 1st of June, and the submission happens 5:01 pm of 1st of June, this is considered as one day delay and subject to 10% of total mark deduction.
Due: Exam Week 10 - 15 June, 2019
Weighting: 40%
The final examination will concern all the material (assigned readings, class lectures, group presentations and classroom discussions) from the entire unit. The specific format of the exam will be case studies as well as essay questions.
The MGSM examination period in Term 2 2019 is from 10 – 15 June 2019.
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 26 April 2019 at https://students.mgsm.edu.au/sydney-students/units/exams/
EXCEPTIONAL CIRCUMSTANCES: Alternate exam date
Students are expected to sit their examinations on the specified date and time during the examination period.
Only in exceptional circumstances (i.e. in the event of serious illness, injury or death of a close family member, unavoidable pre-scheduled overseas/interstate work trip) will alternative arrangements be considered. In the event of illness, students must submit a medical certificate within 48 hours of the date of the missed exam.
For the purpose of adhering to the Master Degree Regulations, Academic Senate will also treat as unavoidable disruption cases where the student has been prevented from attending an examination for the following reasons:
As a member of the armed forces involved in compulsory exercises
As a person in full-time employment required to be overseas by his or her employer
As a person representing their country at an international sporting or cultural competition
Students, who for any of the reasons set out above, cannot sit in the exam period, must advise their lecturer and submit a Request for an Alternate Exam Date form which can be downloaded from the student website at https://students.mgsm.edu.au/media/documents/ss-forms/Request-Alternate-Exam-Date.pdf.
Full supporting documentation must be attached to any request proposing to sit an exam outside of the scheduled time. Upon approval, an alternate exam date will be advised.
If an alternate exam date is granted, the examination will be scheduled after the conclusion of the official examination period. You are advised that it is Macquarie University policy not to set early examinations for individuals or groups of students. All students are expected to ensure that they are available until the end of the teaching term that is the final day of the official examination period.
Lake P., Drake R. (2014). Information Systems Management in the Big Data Era. Springer International Publishing, ISBN (Hardcover): 978-3-319-13502-1, ISBN (Softcover): 978-3-319-35507-8, DOI: 10.1007/978-3-319-13503-8
For information on textbook prices and online ordering, please refer to the Co-Op Bookshop webpage at http://www.coop.com.au
(HBR) Big Data: The Management Revolution (2012)
Mini-case: WALMART: How Big Data Is Used to Drive Supermarket Performance
(MIS Quarterly) Business Intelligence and Analytics: From Big Data to Big Impact (2012)
(HBS) An Introduction to NoSQL Database Design (2016)
Mini-case: How Netflix Used Big Data To Give Us The Programmes We Want
(HBS) Big Data Dreams: A Framework for Corporate Strategy (2017)
Case Study: (HBS) Neighbourhood Watch: The Rise of Zillow (2017)
Discussion: How has the rise of big data and analytics affected business models and strategic frameworks of industries and services in Australia
(HBR) How Big Data Explosion has Changed Decision Making (2016)
Mini-case: BBC: How Big Data Is Used in The Media1
(HBR) Data Scientist: The Sexiest Job of the 21st Century (2012)
(MIT Sloan) Should You Outsource Analytics? (2014)
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
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
(HBS) Alibaba Group: Technology, Strategy and Sustainability (2016)
(HBS) Netguardians: Beating Fraud from The Inside (2016)
(HBS) Shotspotter: Public Safety, IoT, and Big Data (2017)
(MIT Sloan) Building A More Intelligent Enterprise (2017)
McKinsey Global Institute Report: The Age of Analytics: Competing in a Data-Driven World (2016)
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
Pearson Education Australia – 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 Pearson Education Australia online store at http://www.pearson.com.au/9781292098678.
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.
Top academic management and information systems outlets (some suggestions)
Useful academic databases (DB), search engines (SE), and publishers (PB)
Useful Industry databases
Writing resources
If you lack confidence in writing in English, particularly academic writing and/or business reports, The Macquarie University Library provides three excellent web sites covering writing skills, researching online and a guide to citations and referencing http://www.students.mq.edu.au/support/learning_skills/
http://www.mq.edu.au/about/campus-services-and-facilities/library
The web page for this unit can be found at: https://ilearn.mq.edu.au/login/MGSM
Students are required to attend all classes. No delays are allowed in coming to the class unless it has been permitted by the lecturer at least a day before class.
The unit will be presented over 10 weeks as follows:
Wednesdays 6 pm to 10 pm (unless specified otherwise below)
Session |
Date |
Topic |
Required Readings |
---|---|---|---|
1 |
3 April 2019 |
Introduction to Big Data & Analytics (Part 1)
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1. Textbook: Chapter 1 2. The Management Revolution 3. WALMART: How Big Data Is Used to Drive Supermarket Performance |
2 |
10 April 2019 |
Introduction to Big Data & Analytics (Part 2)
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1. Textbook: Chapter 1 2. From Big Data to Big Impact 3. An Introduction to NoSQL Database Design 4. How Netflix Used Big Data To Give Us The Programmes We Want |
3 |
17 April 2019 |
Big Data Strategy & Azure Platform Introduction Workshop #1
Discussion:
Workshop #1
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1. Textbook: Chapter 2 2. Big Data Dreams: A Framework for Corporate Strategy 3. Case Study: Neighbourhood Watch: The Rise of Zillow |
4 |
24 April 2019 |
Big Data Structure, Style & Data Science Hands-on Workshop #2
Workshop #2
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1. Textbook: Chapters 3-4 2. How Big Data Explosion Has Changed Decision Making 3. BBC: How Big Data Is Used in The Media |
5 |
1 May 2019 |
Big Data Staff, Synthesis & Data Science Hands-on Workshop #3
Discussion:
Workshop #3
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1. Textbook: Chapters 5 and 7 2. Data Scientist: The Sexiest Job of the 21st Century 3. Should You Outsource Analytics? |
6 |
8 May 2019 |
Big Data Statistical Thinking & Data Science Hands-on Workshop #4
Workshop #4
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1. Textbook: Chapter 6 2. Statistical Challenges with Big Data in Management Science 3. Managing Large-Scale Standardized Electronic Health Records |
7 |
15 May 2019 |
Big Data Systems, Sources & Data Science Hands-on Workshop #5
Workshop #5
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1. Textbook: Chapters 8-9 2. Alibaba Group: Technology, Strategy and Sustainability |
8 |
22 May 2019 |
Big Data Systems, Security & Group Presentation #1
Group Presentations |
1. Textbook: Chapters 10-11 2. Netguardians: Beating Fraud from The Inside |
9 |
29 May 2019 |
Big Data Applications, Disruptive Technologies & Group Presentation #2
Group Presentations |
1. Textbook: Chapter 12 2. Shotspotter: Public Safety, IoT, and Big Data |
10 |
5 June 2019 |
Further Discussion, Case Studies & Exam
Group Presentations – if required |
1. Textbook: Chapter 1 – 12 2. Building A More Intelligent Enterprise 3. The Age of Analytics: Competing in a Data-Driven World |
10 - 15 June 2019 |
Final exam week |
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:
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).
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 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
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
For all student enquiries, visit Student Connect at ask.mq.edu.au
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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.
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This graduate capability is supported by:
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This graduate capability is supported by:
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This graduate capability is supported by:
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This graduate capability is supported by:
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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.
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.