Information Analytics Tools Techniques And Technologies

AY2015/2016 Semester 1

Learning Objective Large amounts of data are generated by individuals and organisations through various platforms including social media, sensors, and mobile devices. Types of data are mostly unstructured data and examples include videos, tweets, photographs, e-mail messages, and Web logs, to name a few. Such data presents opportunities and challenges in terms of extracting and analysing for decision making, a field known as information analytics. This course provides an introduction to information analytics and its application in various industries, including those in media and communication. It examines the various techniques that have been employed in capturing, storing and analysing large amounts of data, as well as software tools available for these tasks. Related technologies essential to information analytics are also discussed including databases, search engines, social media, and ubiquitous computing. Content Overview of information analytics: Concepts and applications to various industries. Techniques for making sense of data: pre-processing, information extraction, categorization, clustering, association rule mining. Making sense of information through visualisation. Essential technologies for information analytics: databases and data warehousing, information retrieval systems, social computing, mobile and ubiquitous computing.