26776 Foundations of Business Analytics
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Credit points: 3 cp
Subject level:
Postgraduate
Result type: Grade and marksThere are course requisites for this subject. See access conditions.
Anti-requisite(s): 260776 Foundation of Business Analytics
Description
Business analytics is concerned with the use of data, quantitative analysis, predictive models and fact-based management to create value for organisations. With the tremendous growth in the amount of data being generated by organisations, government and society, it is crucial that the leaders of tomorrow understand the proper tools to be able to make evidence-based decisions. In Foundations of Business Analytics, students are provided with the foundations of business analytics, as well as an introduction to techniques and methods required to undertake practical problems. Students ultimately gain the necessary knowledge to initiate and conduct small scale business analytics projects and professionally communicate their findings to a diverse set of stakeholders.
Subject learning objectives (SLOs)
| 1. | Explain the background of business analytics |
|---|---|
| 2. | Demonstrate methods to locate, prepare and analyse data in order to be able to make predictions |
| 3. | Communicate the results of a business analytics project |
| 4. | Relate ethical principles to the collection, storage and use of data by business and government |
Contribution to the development of graduate attributes
The subject introduces students to business analytics and provides a framework for data-driven decision making. To do so requires students to critically analyse the facts they are presented with so as to provide a solution to the identified problem(s). In doing so, it is important that students are cognizant of multiple points of view. The learning activities enable students to develop and apply analytical and presentation skills in complex and diverse contexts.
This subject is aligned with the following Graduate Attributes:
- Intellectual rigour and innovative problem solving
- Social responsibility and cultural awareness
More specifically, this subject contributes to the development of the following program learning objectives in the Master of Business Analytics:
- Research, identify and evaluate the assumptions implicit in data and apply analytical techniques to facilitate business decision making (1.1)
- Create innovative business solutions utilising data for a range of business stakeholders (1.2)
- Critically evaluate and apply professional ethical standards, the principles of sustainability, social responsibility, and Indigenous values as business analysts (3.1)
Teaching and learning strategies
The teaching and learning approach comprises a combination of face-to-face and online learning activities. Students will be required to complete pre-work activities before coming to class. Three face-to-face workshops take place, for a hands-on experience where students will have opportunities to work on business analytics problems individually and in groups.
Pre-class activities: Students are expected to read online content (readings and video tutorials), provided via the learning management system, prior to attending classes. They are also required to complete practice quizzes prior to each class in the learning management system, which will help identify possible gaps on the weekly topics and inform the class discussion. A mandatory, online formative assessment completed after the first workshop, will provide students with further feedback to help direct their self-study.
Workshops: Face-to-face workshops are designed to present the theory and practice associated with business analytics. Students will work individually and in groups during the workshops on various business analytics problems.
Feedback: Individual feedback will be provided after the formative online assessment after Workshop 1. General feedback based on performance in the pre-class practice quizzes will be given at the beginning of Workshops 2 and 3. Finally, students will receive formal feedback on assessment task 1 prior to the submission of assessment task 2.
An aim of this subject is to help you develop academic and professional language and communication skills in order to succeed at university and in the workplace. To determine your current academic language proficiency, you are required to complete an online language screening task, OPELA (information available at https://www.uts.edu.au/research-and-teaching/learning-and-teaching/enhancing/language-and-learning/about-opela-students) [or a written diagnostic task]. If you receive a Basic grade for OPELA [or the written diagnostic task], you must attend additional Language Development Tutorials (each week from week [3/4] to week [11/12] in order to pass the subject. These tutorials are designed to support you to develop your language and communication skills. Students who do not complete the OPELA and/or do not attend 80% of the Language Development Tutorials will receive a Fail X grade.
Content (topics)
- Introduction to business analytics
- Data exploration
- Ethical considerations in relation to data
- Predictive modelling
- Communication and presentation
Assessment
Assessment task 1: Business Analytics Context and Ideation (Individual)
| Objective(s): | This addresses subject learning objective(s): 1 and 4 |
|---|---|
| Weight: | 40% |
| Criteria: |
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Assessment task 2: Business Analytics Prediction and Communication (Individual)
| Objective(s): | This addresses subject learning objective(s): 2 and 3 |
|---|---|
| Weight: | 60% |
| Length: | The presentation should go for no more than 6 minutes. |
| Criteria: |
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Minimum requirements
Students must achieve at least 50% of the subject’s total marks.
It is a requirement of this subject that all students complete OPELA [or a written diagnostic task]. Students who received a Basic grade in the OPELA [or the written diagnostic task] are required to attend 80% of the Language Development Tutorials in order to pass the subject. Students who do not complete the OPELA and/or do not attend 80% of the Language Development Tutorials will receive a Fail X grade.
Required texts
There is no required textbook. Resources will be made available through the learning management system as required.
References
- Albright, S. Christian and Winston, Wayne L. (2019). Business analytics: data analysis and decision making, Cengage.
- Camm, Jeffrey, Cochran, James J., Fry, Michael J., Ohlmann, Jeffrey W., Anderson, David R. and Sweeney, Dennis J. (2019). Business Analytics, Cengage.
- Knaflic, C. N. (2020). Storytelling with Data: Let's Practice. Wiley: New Jersey.
- Sahay, Amar (2018). Business Analytics, Volume 1: A Data-Driven Decision Making Approach for Business, Business Expert Press.