精东传媒app

Data has become an important resource for organisations. Many thousands of terabytes of data come into organisations daily through transactional data, sensor networks and social media. IT professionals increasingly working in multidisciplinary teams have the responsibility of communicating this data effectively to the key stakeholders in organisations. Drawing on data visualisation theory, concepts and design and the use if advanced data visualisation tools, big data can be presented into visual form for quick and easy comprehension so that accessible and readily discernible evidence can drive the decision-making process within an organisation.

This course provides students with a sound grounding in data visualisation theory, concepts and design. Students will develop the knowledge and skills to apply best practice principles in the design and implementation of data visualisation applications that utilise big data in ways that inform decision making for organisations. The course requires student to apply fundamental and advanced aspects of data visualisation theory and design principles as well as the methods and techniques for creating user-oriented data visualisation solutions using a data visualisation tool. Students will implement, through a hands-on team project, elements of sound data visualisation design, while developing an appreciation of the ethical considerations and need for strong policy to protect the privacy and security of citizens' data.

On successful completion of this course students should be able to:

1. synthesize academic and professional knowledge of data visualisation theory, concepts and design principles;
2. assess and adapts contemporary and innovative data visualisation approaches to gain insight and value that support effective data-driven decision-making;
3. appraise and present complex and big data in visual from that is readily understandable by specialist and non-specialist audiences using data visualisation methods tools and techniques;
4. interact and collaborate effectively in teams to design and implement data visualisation project;
5. articulate and explain ethical dilemmas with regard to privacy and security concerns that may arise in data visualisation projects.