Prof. Joseph is the Professor of Information Systems and Services at the School of Computer Science. He has been an active researcher in the information systems field, with a focus on research questions at the intersection between information systems and computer science, namely on semantic information processing, crowdsourcing, decision support, and service computing. In particular, he has contributed extensively to understanding the creation, sharing and utilization of information and knowledge in organizations and the links to decision making. He is a recipient of the IBM Faculty Research award for IT services-related research. His research has been funded by the Australian Research Council, Carnegie Bosch Institute, and IBM Research Labs, among others. He is a Charter Member of the Association for Information Systems, a Senior Member of the Association for Computing Machinery (ACM) and a Member of the IEEE.
This online project-based learning course will provide a fast-paced introduction to the key topics related to Data Analytics and Business Intelligence (BI). The primary objective of the course is to equip the students with both the conceptual knowledge and practical skills to infer, visualize, and present useful and actionable information and knowledge from large volumes of structured data. Some of the important topics covered in the lectures will include online analytical processing (OLAP), data warehousing, data visualization and dashboarding, and actionable knowledge inferencing. It will also provide an overview of the emerging developments in the areas of analytics and BI. The lectures will be complemented by a group-based project which will provide the students with hands-on experience using a widely used BI tool. The project will require the students to analyze, visualize, and make realistic inferences from a large real-world dataset to address a specific set of questions and scenarios that will be provided. Students will also prepare a project research report and present it.