MBAX9135 Business Analytics - 2020

Blended, Sydney CBD
Weekly, Online
Intensive, Sydney CBD
MBAX9135
Postgraduate
Term 1
6 Units of Credit
AGSM

Offering Selection
This course outline is provided in advance of offering to guide student course selection. Please note that while accurate at time of publication, changes may be required prior to the start of the teaching session. To view other versions, visit the archives .

1. Course Details

Summary of Course

Business analytics enables organisations to make quicker, better and more intelligent decisions to create business value in the broadest sense - potentially the difference between survival and extinction in an increasingly competitive world. Evidence-based decision-making supported by a data-driven culture is essential to the management of organisations.

Davenport and Harris (2007) define business analytics as 'the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions'. A key aspect of this definition is that analytics ultimately provides insight that is actioned - not just descriptions (e.g. customer segmentation) or predictive models (e.g. which customers are likely to churn). Analytic methods are being used in many and varied ways - for example, to predict consumer choices, to predict the likelihood of a medical condition, to analyse social networks and social media, to better manage traffic networks. There are many ways of creating value from data, especially when an organisation's internal data is combined with external and open data.

This course addresses the context of business analytics and the management actions required for organisations to manage business analytics such that they can create value from their data and make progress on the transformational journey to becoming data-driven. The course comprises three core areas: (1) managing data and sources of value, (2) the business analytics process, (3) navigating the organisational context.

As part of the business analytics process, you will build predictive models. This requires a basic understanding of statistics and therefore you will be required to study the material on regression provided by the Harvard Quantitative Methods online course during the first five weeks of the course. Information about the Harvard course and how to enrol in it will be provided to you in Moodle. Your regression knowledge will be assessed by a multiple-choice quiz.

Reference:

Davenport, T & Harris, J 2007, Competing on analytics: The new science of winning, Harvard Business Press, Boston

Teaching Times and Locations

Please note that teaching times and locations are subject to change. Students are strongly advised to refer to the Class Timetable website for the most up-to-date teaching times and locations.

View course timetable

Course Policies & Support

Course Aims and Relationship to Other Courses

As part of the business analytics process, you will build predictive models. This requires a basic understanding of statistics and you will therefore be required to study the material on regression provided by the Harvard Quantitative Methods online course during the first five weeks of the course. Information about this course and how to enrol in it will be provided to you in Moodle. Your regression knowledge will be assessed by a multiple-choice quiz.

Additonal Course Details

2. Staff Contact Details

Position Name Email Location Phone Consultation Times
Course CoordinatorRichard Vidgen
Course CoordinatorRichard Vidgen
Course CoordinatorRichard Vidgen
+61 2 9385 7125

Course Coordinator

Each course has a Course Coordinator who is responsible for the academic leadership and overall academic integrity of the course. The Course Coordinator selects content and sets assessment tasks, and takes responsibility for specific academic and administrative issues related to the course when it is being offered. Course Coordinators oversee Class Facilitators and ensure that the ongoing standard of facilitation in the course is consistent with the quality requirements of the program.

Class Facilitator

The role of your Class Facilitator is to support the learning process by encouraging interaction among participants, providing direction in understanding the course content, assessing participant progress through the course and providing feedback on work submitted. Class Facilitators comprise academics and industry practitioners with relevant backgrounds.

3. Learning and Teaching Activities

Approach to Learning and Teaching in the Course

Learning Activities and Teaching Strategies

Course Structure

The course will use the following prescribed textbook, drawing written and video content from it, as well as activities:

Vidgen, R, Kirshner, S & Tan, F 2019, Business analytics for managers, Red Globe Press, London.

Note: Students will be given access to an e-version of the textbook.


The course has 10 Units as follows:

Unit 1: Introduction to business analytics

Unit 2: Business analytics development

Unit 3: Data and information

Unit 4: Data exploration

Unit 5: Predictive modelling with regression

Unit 6: Predictive modelling with classification and regression tress (CART)

Unit 7: Automated machine learning

Unit 8: Business analytics methodology

Unit 9: Design and agile thinking

Unit 10: Ethical aspects of business analytics

5. Course Resources

You have four major resources to help you learn:

  1. The course materials, comprising the 10 study Units with readings, references, insights and commentary - also incorporating the Harvard Quantitative Methods course. You will do much of your learning outside the classroom by working through the course materials, and by completing the activities as they arise.
  2. Your classes with your Class Facilitator, who will guide your learning by conducting class discussion, answering questions that might arise in relation to the course materials, providing insights from his or her practical experience and understanding of theory, providing you with feedback on your assessments, and directing discussions and debates that will occur between you and your co-participants in the classroom.
  3. Your co-participants. Your colleagues in the classroom are an invaluable potential source of learning for you. Their work and life, and their willingness to question and argue with the course materials, the facilitator and your views, represent a great learning opportunity. They bring much valuable insight to the learning experience.
  4. In addition to course-based resources, please also refer to the AGSM Learning Toolkit(available in Moodle) for tutorials and guides that will help you learn more about effective study practices and techniques.

Prescribed textbook

Vidgen, R, Kirshner, S & Tan, F 2019, Business analytics for managers, Red Globe Press, London.

Enrolled students will be given access to the e-version of this text in their Moodle class site.

Other resources

BusinessThink

BusinessThink is UNSW's free, online business publication. It is a platform for business research, analysis and opinion. If you would like to subscribe to BusinessThink, and receive the free monthly e-newsletter with the latest in research, opinion and business then go here.

6. Course Evaluation & Development

Continual Course Improvement

AGSM courses are revised each time they run, with updated course outlines and assessment tasks developed. Changes relating to any industry developments will also be included.

Additionally, the AGSM surveys students each time a course is offered. The data collected provides anonymous feedback from students on the quality of course content and materials, class facilitation, student support services and the program in general. This student feedback is considered during all course revisions.

Student Response

Concerns were raised that IBM's Watson Analytics was out of date and cumbersome software and no longer relevant in business.

Business analytics is a fast-moving field and there were some comments about the recency of the course material, which is now three years old.

Although students found the full Harvard quantitative methods course useful some students noted that this is a substantial workload (around 20 hours).

Response to Student Feedback

We have retired IBM Watson and replaced it with SAS VA

The course material has been comprehensively updated and is now based on a 2019 textbook by Vidgen et al.

We have now reduced the Harvard material to focus on regression and therefore on predictive analytics rather than statistics in general.

7. Course Schedule

For AGSM academic calendars and key dates please visit https://www.business.unsw.edu.au/agsm/students/resources/timetables-and-key-dates
Week Activity Topic Detail/Engagement Assessment Task
Week 1 Participation; Complete Unit 1Introduction to business analytics

Assessment 1: Participation Assessment begins (10%)

Assessment 1 : Participation and engagement
Week 2 Complete Unit 2Business analytics development
Week 3 Complete Asst 1 (Analytics software) and Unit 3Data and information

Assessment 1: Participation (Analytics software) 5% due

Assessment 1 : Analytics software familiarisation (SAS VA)
Week 4 Participation feedback, Complete Unit 4Data exploration

Receive feedback on participation at the end of Week 4

Assessment 1 : Participation and engagement
Week 5 Submit Assessment 2, Complete Unit 5Predictive modelling with regression
Assessment 2 : Quantitative Methods Online Course: Regression Section
Week 6 Complete Unit 6Predictive modeling with classification and regression trees (CART)
Week 7 Complete Unit 7Automated machine learning
Week 8 Complete Unit 8Business analytics methodology
Week 9 Submit Assessment 3, Complete Unit 9Design and agile thinking
Assessment 3 : Predictive Modelling - Written report and oral presentation
Week 10 Complete Unit 10Ethical aspects of business analytics
Week 11 -
Week 12 Complete and submit Assessment 4
Assessment 4 : Business analytics capability development - Written report
Week 1 Participation; Complete Unit 1Introduction to business analytics

Assessment 1: Participation Assessment begins (10%)

Assessment 1 : Participation and engagement
Week 2 Complete Unit 2Business analytics development
Week 3 Complete Asst 1 (Analytics software) and Unit 3Data and information

Assessment 1: Participation (Analytics software) 5% due

Assessment 1 : Analytics software familiarisation (SAS VA)
Week 4 Participation feedback, Complete Unit 4Data exploration

Receive feedback on participation at the end of Week 4

Assessment 1 : Participation and engagement
Week 5 Submit Assessment 2, Complete Unit 5Predictive modelling with regression
Assessment 2 : Quantitative Methods Online Course: Regression Section
Week 6 Complete Unit 6Predictive modeling with classification and regression trees (CART)
Week 7 Complete Unit 7Automated machine learning
Week 8 Complete Unit 8Business analytics methodology
Week 9 Submit Assessment 3, Complete Unit 9Design and agile thinking
Assessment 3 : Predictive Modelling - Written report and oral presentation
Week 10 Complete Unit 10Ethical aspects of business analytics
Week 11 -
Week 12 Complete and submit Assessment 4
Assessment 4 : Business analytics capability development - Written report
Week 1 Complete Unit 1Business analytics: Introduction

Assessment 1: Participation Assessment Begins (10%)

Week 2 Complete Unit 2The business analytics development function

Review Units 1 to 7 before Intensive Weekend 1

Week 3 Complete Assessment 1 (Analytics software) Unit 3Data and information

Assessment 1: Participation (Analytics software) 5% due

Assessment 2 : Quant Methods Online Course: Regression Section
Week 4 Participation feedback, Complete Unit 4Data exploration

Receive feedback on participation at the end of Week 4

Week 5 Assessment 2, Unit 5, Intensive Weekend 1Building predictive models with linear regression

Weekend 1

End of week 5

21-22 March, 2020 9am-5pm

Week 6 Complete Unit 6Predictive modeling with classification and decision trees (CART)
Week 7 Complete Unit 7Automated machine learning

Assessment 1 - Statistics for managers (Online tutorial and quiz 20%) due Tuesday 2 April 2019 by 3pm Sydney time

Assessment 1 : Analytics software familiarisation (SAS VA)
Week 8 Complete Unit 8Business analytics methodology
Week 9 Submit Assessment 3, Complete Unit 9Design and agile thinking

Review all Units before Intensive Weekend 2

Intensive Weekend 2: Saturday 18 and Sunday 19 April 2019 - 9am to 5pm

Assessment 3 : Predictive modelling - Written report and oral presentation
Week 10 Complete Unit 10Ethical aspects of business analytics
Week 11 Work on final assessment task-
Week 12 Complete and submit Assessment 4-

8. Policies and Support

Information about UNSW Business School protocols, University policies, student responsibilities and education quality and support.

Program Learning Outcomes

The Business School places knowledge and capabilities at the core of its curriculum via seven Program Learning Outcomes (PLOs). These PLOs are systematically embedded and developed across the duration of all coursework programs in the Business School.

PLOs embody the knowledge, skills and capabilities that are taught, practised and assessed within each Business School program. They articulate what you should know and be able to do upon successful completion of your degree.

Upon graduation, you should have a high level of specialised business knowledge and capacity for responsible business thinking, underpinned by ethical professional practice. You should be able to harness, manage and communicate business information effectively and work collaboratively with others. You should be an experienced problem-solver and critical thinker, with a global perspective, cultural competence and the potential for innovative leadership.

All UNSW programs and courses are designed to assess the attainment of program and/or course level learning outcomes, as required by the UNSW Assessment Design Procedure. It is important that you become familiar with the Business School PLOs, as they constitute the framework which informs and shapes the components and assessments of the courses within your program of study.

PLO 1: Business knowledge

Students will make informed and effective selection and application of knowledge in a discipline or profession, in the contexts of local and global business.

PLO 2: Problem solving

Students will define and address business problems, and propose effective evidence-based solutions, through the application of rigorous analysis and critical thinking.

PLO 3: Business communication

Students will harness, manage and communicate business information effectively using multiple forms of communication across different channels.

PLO 4: Teamwork

Students will interact and collaborate effectively with others to achieve a common business purpose or fulfil a common business project, and reflect critically on the process and the outcomes.

PLO 5: Responsible business practice

Students will develop and be committed to responsible business thinking and approaches, which are underpinned by ethical professional practice and sustainability considerations.

PLO 6: Global and cultural competence

Students will be aware of business systems in the wider world and actively committed to recognise and respect the cultural norms, beliefs and values of others, and will apply this knowledge to interact, communicate and work effectively in diverse environments.

PLO 7: Leadership development

Students will develop the capacity to take initiative, encourage forward thinking and bring about innovation, while effectively influencing others to achieve desired results.

These PLOs relate to undergraduate and postgraduate coursework programs.  Separate PLOs for honours and postgraduate research programs are included under 'Related Documents'.

Business School course outlines provide detailed information for students on how the course learning outcomes, learning activities, and assessment/s contribute to the development of Program Learning Outcomes.

RELATED DOCUMENTS

 

UNSW Graduate Capabilities

The Business School PLOs also incorporate UNSW graduate capabilities, a set of generic abilities and skills that all students are expected to achieve by graduation. These capabilities articulate the University’s institutional values, as well as future employer expectations.

UNSW Graduate CapabilitiesBusiness School PLOs
Scholars capable of independent and collaborative enquiry, rigorous in their analysis, critique and reflection, and able to innovate by applying their knowledge and skills to the solution of novel as well as routine problems.
  • PLO 1: Business knowledge
  • PLO 2: Problem solving
  • PLO 3: Business communication
  • PLO 4: Teamwork
  • PLO 7: Leadership development

Entrepreneurial leaders capable of initiating and embracing innovation and change, as well as engaging and enabling others to contribute to change
  • PLO 1: Business knowledge
  • PLO 2: Problem solving
  • PLO 3: Business communication
  • PLO 4: Teamwork
  • PLO 6: Global and cultural competence
  • PLO 7: Leadership development

Professionals capable of ethical, self-directed practice and independent lifelong learning
  • PLO 1: Business knowledge
  • PLO 2: Problem solving
  • PLO 3: Business communication
  • PLO 5: Responsible business practice

Global citizens who are culturally adept and capable of respecting diversity and acting in a socially just and responsible way.
  • PLO 1: Business knowledge
  • PLO 2: Problem solving
  • PLO 3: Business communication
  • PLO 4: Teamwork
  • PLO 5: Responsible business practice
  • PLO 6: Global and cultural competence

While our programs are designed to provide coverage of all PLOs and graduate capabilities, they also provide you with a great deal of choice and flexibility.  The Business School strongly advises you to choose a range of courses that assist your development against the seven PLOs and four graduate capabilities, and to keep a record of your achievements as part of your portfolio. You can use a portfolio as evidence in employment applications as well as a reference for work or further study. For support with selecting your courses contact the UNSW Business School Student Centre.




Academic Integrity and Plagiarism

Academic Integrity is honest and responsible scholarship. This form of ethical scholarship is highly valued at UNSW. Terms like Academic Integrity, misconduct, referencing, conventions, plagiarism, academic practices, citations and evidence based learning are all considered basic concepts that successful university students understand. Learning how to communicate original ideas, refer sources, work independently, and report results accurately and honestly are skills that you will be able to carry beyond your studies.

The definition of academic misconduct is broad. It covers practices such as cheating, copying and using another person’s work without appropriate acknowledgement. Incidents of academic misconduct may have serious consequences for students.

Plagiarism

UNSW regards plagiarism as a form of academic misconduct. UNSW has very strict rules regarding plagiarism. Plagiarism at UNSW is using the words or ideas of others and passing them off as your own. All Schools in the Business School have a Student Ethics Officer who will investigate incidents of plagiarism and may result in a student’s name being placed on the Plagiarism and Student Misconduct Registers.

Below are examples of plagiarism including self-plagiarism:

Copying: Using the same or very similar words to the original text or idea without acknowledging the source or using quotation marks. This includes copying materials, ideas or concepts from a book, article, report or other written document, presentation, composition, artwork, design, drawing, circuitry, computer program or software, website, internet, other electronic resource, or another person's assignment, without appropriate acknowledgement of authorship.

Inappropriate Paraphrasing: Changing a few words and phrases while mostly retaining the original structure and/or progression of ideas of the original, and information without acknowledgement. This also applies in presentations where someone paraphrases another’s ideas or words without credit and to piecing together quotes and paraphrases into a new whole, without appropriate referencing.

Collusion: Presenting work as independent work when it has been produced in whole or part in collusion with other people. Collusion includes:

  • Students providing their work to another student before the due date, or for the purpose of them plagiarising at any time
  • Paying another person to perform an academic task and passing it off as your own
  • Stealing or acquiring another person’s academic work and copying it
  • Offering to complete another person’s work or seeking payment for completing academic work

Collusion should not be confused with academic collaboration (i.e., shared contribution towards a group task).

Inappropriate Citation: Citing sources which have not been read, without acknowledging the 'secondary' source from which knowledge of them has been obtained.

Self-Plagiarism: ‘Self-plagiarism’ occurs where an author republishes their own previously written work and presents it as new findings without referencing the earlier work, either in its entirety or partially. Self-plagiarism is also referred to as 'recycling', 'duplication', or 'multiple submissions of research findings' without disclosure. In the student context, self-plagiarism includes re-using parts of, or all of, a body of work that has already been submitted for assessment without proper citation.

To see if you understand plagiarism, do this short quiz: https://student.unsw.edu.au/plagiarism-quiz

Cheating

The University also regards cheating as a form of academic misconduct. Cheating is knowingly submitting the work of others as their own and includes contract cheating (work produced by an external agent or third party that is submitted under the pretences of being a student’s original piece of work). Cheating is not acceptable at UNSW.

If you need to revise or clarify any terms associated with academic integrity you should explore the 'Working with Academic Integrity' self-paced lessons available at: https://student.unsw.edu.au/aim.

For UNSW policies, penalties, and information to help you avoid plagiarism see: https://student.unsw.edu.au/plagiarism as well as the guidelines in the online ELISE tutorials for all new UNSW students: http://subjectguides.library.unsw.edu.au/elise. For information on student conduct see: https://student.unsw.edu.au/conduct.

For information on how to acknowledge your sources and reference correctly, see: https://student.unsw.edu.au/referencing. If you are unsure what referencing style to use in this course, you should ask the lecturer in charge.


Student Responsibilities and Conduct

Students are expected to be familiar with and adhere to university policies in relation to class attendance and general conduct and behaviour, including maintaining a safe, respectful environment; and to understand their obligations in relation to workload, assessment and keeping informed.

Information and policies on these topics can be found on the 'Managing your Program' website.

Workload

It is expected that you will spend at least ten to twelve hours per week studying for a course except for Summer Term courses which have a minimum weekly workload of twenty to twenty four hours. This time should be made up of reading, research, working on exercises and problems, online activities and attending classes. In periods where you need to complete assignments or prepare for examinations, the workload may be greater. Over-commitment has been a cause of failure for many students. You should take the required workload into account when planning how to balance study with employment and other activities.

We strongly encourage you to connect with your Moodle course websites in the first week of semester. Local and international research indicates that students who engage early and often with their course website are more likely to pass their course.

View more information on expected workload

Attendance

Your regular and punctual attendance at lectures and seminars or in online learning activities is expected in this course. The Business School reserves the right to refuse final assessment to those students who attend less than 80% of scheduled classes where attendance and participation is required as part of the learning process (e.g., tutorials, flipped classroom sessions, seminars, labs, etc.).

View more information on attendance

General Conduct and Behaviour

You are expected to conduct yourself with consideration and respect for the needs of your fellow students and teaching staff. Conduct which unduly disrupts or interferes with a class, such as ringing or talking on mobile phones, is not acceptable and students may be asked to leave the class.

View more information on student conduct

Health and Safety

UNSW Policy requires each person to work safely and responsibly, in order to avoid personal injury and to protect the safety of others.

View more information on Health and Safety

Keeping Informed

You should take note of all announcements made in lectures, tutorials or on the course web site. From time to time, the University will send important announcements to your university e-mail address without providing you with a paper copy. You will be deemed to have received this information. It is also your responsibility to keep the University informed of all changes to your contact details.



Student Support and Resources

The University and the Business School provide a wide range of support services and resources for students, including:

Business School EQS Consultation Program
The Consultation Program offers academic writing, literacy and numeracy consultations, study skills, exam preparation for Business students. Services include workshops, online resources, individual and group consultations.
Level 1, Room 1035, Quadrangle Building.
BUS.EQS.Consultations@unsw.edu.au
02 9385 4508

Business School Student Centre
The Business School Student Centre provides advice and direction on all aspects of admission, enrolment and graduation.
Level 1, Room 1028 in the Quadrangle Building
02 9385 3189

UNSW Learning Centre
The UNSW Learning Centre provides academic skills support services, including workshops and resources, for all UNSW students. See their website for details.
Lower Ground Floor, North Wing Chancellery Building.
learningcentre@unsw.edu.au
02 9385 2060

Educational Support Service
Educational Support Advisors work with all students to promote the development of skills needed to succeed at university, whilst also providing personal support throughout the process. Check their website to request an appointment or to register in the Academic Success Program.
John Goodsell Building, Ground Floor.
advisors@unsw.edu.au
02 9385 4734

Library services and facilities for students
The UNSW Library offers a range of collections, services and facilities both on-campus and online.
Main Library, F21.
02 9385 2650

Moodle eLearning Support
Moodle is the University’s learning management system. You should ensure that you log into Moodle regularly.
externalteltsupport@unsw.edu.au
02 9385 3331

UNSW IT
UNSW IT provides support and services for students such as password access, email services, wireless services and technical support.
UNSW Library Annexe (Ground floor).
itservicecentre@unsw.edu.au
02 9385 1333

Disability Support Services
UNSW Disability Support Services provides assistance to students who are trying to manage the demands of university as well as a health condition, learning disability or who have personal circumstances that are having an impact on their studies. Disability Advisers can arrange to put in place services and educational adjustments to make things more manageable so that students are able to complete their course requirements. To receive educational adjustments for disability support, students must first register with Disability Services.
Ground Floor, John Goodsell Building.
disabilities@unsw.edu.au
02 9385 4734

UNSW Counselling and Psychological Services
Provides support and services if you need help with your personal life, getting your academic life back on track or just want to know how to stay safe, including free, confidential counselling.
Level 2, East Wing, Quadrangle Building.
counselling@unsw.edu.au
02 9385 5418


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MBAX9135