ITEC632 - Data and Information Visualisation

Year

Credit points

Campus offering

Prerequisites

ITEC622 Data Analysis and Visualisation

Teaching organisation

3 hours per week for twelve weeks or equivalent.

Unit rationale, description and aim

Innovative digital technologies are enabling today’s businesses to respond to the demands of society to create and maintain personalised online customer relationships. This is possible because businesses collect vast amounts of end–user data via their service systems thereby attaining tremendous insights into end–user’s beliefs, needs and aims. However, the analysis and meaningful presentation of large volumes of diverse data, called big data, to support corporate decision–making processes is a challenging task. Current display methods, such as graphs for analyses are not effective when dealing with extremely large volumes of diverse data. Hence, understanding the techniques and methods needed to visualize large volumes of different types of data have become essential for today’s businesses.

Data visualisation is the presentation of data in a pictorial or graphical format for decision makers to easily identify underlining patterns. It enables organisations to present raw data in a contextual and meaningful way to generate the most value by addressing the quality of data through data governance. Information visualisation goes one step further by revealing the narratives behind the data and by allowing the user to interact with the data. Thus, this unit explores ways in which different visual analytical techniques can be employed to create intelligible, useful and navigable data representations. In addition, it emphasises the need to understand and manage the various challenges associated with the interpretation and visualisation of big data.

The primary aim of this unit is to provide students with an understanding of the principles and techniques of data and information visualisation and with essential skills in developing contextual visualisation models of big data to support evidence–based decision–making while upholding subsidiarity which enables participation of the people closest and most affected by the issues and concerns of the community in bottom–up decision–making processes.