Accurate and effective analysis of data is a crucial skill in today's data-rich business environment. Visual Data Analytics (VDA) is an indispensable scientific tool for analysing all sorts of business-related data and, in particular, complex high-dimensional data. Applications include the visualisation of financial statements, capital market data, marketing data, supply chain data and many others. VDA has the ability to encode vast amounts of information into a small space that can be then intuitively interpreted for decision-making. This unit draws upon statistics, computer science, behavioural psychology and information design for visualising numerical and text data. It presents statistical and data analysis methods that are necessary for description, exploration, inference and diagnosis using data reduction, visual mining, smoothing, clustering and validation techniques. Upon completion of the unit, students should be proficient in producing high integrity visuals that enable fast and precise business decision-making. Students will also learn about the limitations of visual perception and how to design powerful visuals that can tap into our natural cognitive predisposition in favouring visual types of information.
13 interactive lectures x 2 hours each, plus 13 workshops driven by student work x 1 hour each, plus 10 week x 1 hour tutorials on software training (e.g. for Tableau, Gephi, Google Charts, Google Big Query)
Weekly assignments (20%), group projects (40%), final exam (40%)
The unit assumes knowledge of statistics and confidence in working with data.
QBUS5001 or QBUS5002