Courses - Faculty of Business And Economics
Business Information Analytics
Postgraduate 700 Level Courses
Analysis of Business Problems
Develops a managerial perspective on the use of small and big data in problem identification, analysis and decision-making. Explores big data strategies and develops an understanding of the business and industry context in which analytics professionals operate and how different parts of organisations interact.
Business Analytics Tools
Develops skills in programming and business intelligence applications using the most commonly applied software and freeware. Provides insights into data wrangling and focuses on using tools for problem-solving, including their application in a variety of business settings.
Information Management
Develops skills in the use of contemporary data management tools and the DataOps ecosystem to optimise the efficient storage of data. Emphasises data stewardship, including data governance and related ethical considerations. Explores behavioural, strategic and social issues related to data management software and tools to create agile data organisations.
Data Visualisation for Business
Develops skills in unsupervised machine learning techniques, e.g., cluster analysis, factor analysis, and text mining, which enable unstructured and structured data to be leveraged to provide insights. Uses storytelling and visualisation techniques to translate data patterns in order to inform managerial decision-making.
Prerequisite: BUSINFO 700
Predictive Business Analytics
Provides insights into the most commonly used supervised machine learning techniques, e.g., linear regression, logistic regression, random forest techniques, neural networks. Applies these techniques to model data for predicting relevant events. Addresses caveats of the techniques and how to evaluate model validity and outcomes.
Decision Analytics
Explores how business analytics can be used to improve business processes and decisions. The link between quantitative models and qualitative processes is explicitly explored. Decision biases are considered in the context of decision modelling. Monte Carlo simulation and optimisation are among the decision tools taught.
Customer and Market Insights
Develops customer and market insight capabilities through the use of machine learning applications such as prospect selection, churn modelling, customer segmentation and attribution modelling. Focuses on the use of CRM data and explores the contributions that survey data can make. Explores campaign management and other aspects of implementing the results of analytical projects.
Prerequisite: BUSINFO 704
Digital Machine Learning - Level 9
Synthesises academic marketing research findings with previously taught knowledge about analytics, the digital channel, marketing planning and practice in order to attain marketing strategic goals. Enables students to critically and independently evaluate alternative analytics and machine learning techniques and apply these insights to formulating solutions to challenges involving, for example, web scraping, network analyses, google analytics and machine learning techniques such as text mining and cluster analysis.
Prerequisite: BUSINFO 704
Supply Chain Optimisation
Uses key analytic modelling techniques to analyse and optimise supply chains. Topics include facility location, network design, and general logistics. Key trade-offs are explored, including that difference between efficiency and effectiveness. Uncertainty is modelled and shown to be key in supply chain design.
Prerequisite: BUSINFO 705
Supply Chain Analytics - Level 9
Synthesises learning from business analytics methodologies (e.g., multivariate data analysis, data mining, and network visualisation) taught in prior classes. Requires application of the latest supply chain research findings from the academic literature in developing practical business solutions, involving issues such as supplier selection and multi-sourcing. Develops skills and knowledge to independently and critically address open-ended and ill-defined challenges in Supply Chain Management including complex tactical supply chain management problems, including supplier selection, multi-sourcing.
Prerequisite: BUSINFO 704
Advanced Project Management
Develops advanced project management skills and readiness for the final business analytics industry project, including definition and formulation of KPIs, risk assessment, progress monitoring, process evaluation, and reporting. Students will apply these skills in the formulation of an industry project proposal.
Consultancy Practice
Develops professional skills in communication, case practice, interviewing, networking, and business etiquette. Enhances team and management skills including conflict management and cultural awareness and builds resilience.
Marketing Analytics Industry Project - Level 9
Marketing analytics consultancy project for a client company with written and oral presentation.
Prerequisite: BUSINFO 706, 707, 710
Supply Chain Analytics Industry Project - Level 9
Supply chain analytics consultancy project for a client company with written and oral presentation.
Prerequisite: BUSINFO 708-710
Marketing Analytics Project - Level 9
Individual marketing analytics consultancy project for a client company with written and oral presentation.
Prerequisite: BUSINFO 706, 707, 710
Supply Chain Analytics Project - Level 9
Individual supply chain analytics consultancy project for a client company with written and oral presentation.
Prerequisite: BUSINFO 708-710
Business Analytics for FinTech
Study of the intersection of finance and business analytics. Considers strategies for improving portfolio performance and valuation accuracy from the perspective of a trader or fund manager, and considers how outside investors and regulators can better detect fraud; uses business analytics tools to improve financial projections.
Prerequisite: BUSINFO 704
FinTech and Financial Intermediation - Level 9
Examines emerging FinTech trends in financial intermediation such as digital transformation and responsible Innovation and evaluates strategies and tactics for financial intermediaries in the banking, real estate and insurance sectors. Critically examines current practices in FinTech from the multiple perspectives of a consultant, regulator, incumbent financial institutions and entrepreneur.
Prerequisite: BUSINFO 704
FinTech Analytics Industry Project - Level 9
Team-based FinTech analytics consultancy project for a client company with written and oral presentations.
Prerequisite: BUSINFO 710, 716, 717