MIT9303 Business Analytics
Unit Code
MIT9303
Level
Postgraduate
Campus
Sydney
Prerequisites
MIT8103
Credit Points
10
Subject Description
MIT9303 Business Analytics is designed to equip students with the knowledge and skills of collecting, analysing, and transforming raw data into meaningful insights to support strategic decision-making. The subject introduces current concepts, processes and technologies in business analytics. The students will also be equipped to use selected analytics to interpret solutions to organisations’ related problems, provide relevant advice, uncover opportunities, optimise operations and gain a competitive advantage.
Course Level
Level 2
Subject Type
☒ Specialisation (MIT Data Science)
☒ Elective (MIT)
Study Mode: Face to face on site
Study Load: Full-time
Learning Topics
- Business analytics and ethical data practice
- Data preparation, modelling and visualisation
- Data warehousing and big-data applications
- Descriptive and predictive analytics
- Text, web, social-media and decision analytics
Subject Learning Outcomes
- Demonstrate and apply an understanding of the fundamental concepts, principles, and methodologies of business analytics including ethical and security components.
- Analytically apply data acquisition, integration, cleaning, and transformation skills to ensure data quality and usability for business analysis.
- Critically apply and compare analytical techniques and statistical methods to extract insights from organisational data.
- Create dashboards and reports to effectively communicate insights derived from business analytics that facilitate decision making
- Evaluate and validate opportunities and challenges for implementing ethical and secure business analysis processes within real-world contexts.
Assessment
AIIHE uses a variety of assessment tools to guide and assess each student’s achievement of the subject learning outcomes. In this subject, students undertake portfolio students will demonstrate their skills, knowledge and understanding of business analytics concepts in the use of business analytics, practical test students will be evaluated in their knowledge of business analytics core concepts and application of methods and techniques, and advanced case study report and presentation students create groups to work on solve a case study and present their work. These tasks assess the knowledge, applied skills, critical analysis, communication and collaborative capabilities relevant to the subject.
Summary of Assessment
- Students must attempt all assessment tasks, and achieve an overall mark of at least 50%, to pass this subject.
- Assessment in this subject is consistent with and informed by the AIIHE Assessment Policy and Procedure.
| Assessment Type | Due Date | Weighting |
|---|---|---|
| Assessment 1: Portfolio | Week 2, 4, 5, 8, 9, 10, & 12 | 35% |
| Assessment 2: Practical test | Week 6 | 30% |
| Assessment 3: Advanced Case Study Report and Presentation | Week 11, 13 | 35% |
Learning Resources
AIIHE will update the topic coverage of the subject and the available relevant learning resources at the time of subject delivery. In the interim, AIIHE provides the following indicative list of relevant reference material. AIIHE also subscribes to eLearning Resources through the Canvas portal, and where relevant material is available, AIIHE will seek to source reference material from this system for staff and student access.
Prescribed Reading
- Sharda, R., Delen, D., Turban, E. (2024). Business Intelligence, Analytics, Data Science, and AI, Global Edition. United Kingdom: Pearson Education, Limited
Texts and References
- Shmueli, G., Bruce, P.C., Gedeck, P., Patel, N.R. (2019). Data Mining for Business Analytics: Concepts, Techniques and Applications in Python. United Kingdom: Wiley.
- Brooks, S. (2022). Business intelligence and analytics: Concepts, techniques and applications. Murphy & Moore Publishing: New York, NY
- Herschel, R.T. (2013). Principles and Applications of Business Intelligence Research. United States: Business Science Reference.