Bhekisipho Twala is a Professor in Artificial Intelligence and Statistical Science and the Director of the newly established Institute for Intelligent Systems
at the University of Johannesburg (UJ) in South Africa. Before then, he was Head of the Electrical and Electronic Engineering Science Department at UJ and Principal Research Scientist at the Council of Science and Industrial Research (CSIR) within the Modelling and Digital Science Unit. His research work involved an expanded swath of data, analytics, and optimization approaches that brings a more complete understanding of digital customer experiences. Prof Twala’s current work involves promoting and conducting research in artificial intelligence within the electrical and electronic engineering science fields and developing novel and innovative solutions to key research problems in these areas. He earned his Bachelor’s degree in Economics and Statistics from the University of Swaziland in 1993; followed by an MSc in Computational Statistics from Southampton University (UK) in 1995; and then a PhD in Machine Learning and Statistical Science from the Open University (UK) in 2005. Prof. Twala was a post-doctoral researcher at Brunel University in the UK, mainly focussing on empirical software engineering research and looking at data quality issues in software engineering. His broad research interests include multivariate statistics, classification methods, knowledge discovery and reasoning with uncertainty, sensor data fusion and inference, and the interface between statistics and computing. He has particular interests in applications in finance, medicine, psychology, software engineering and most recently in robotics and has published over 70 scientific papers. Prof. Twala has a wide ranging work experience to organisations ranging from banks, through universities, to governments. He is currently an associate editor of the Intelligent Data Analysis Journal, Journal of Computers, International Journal of Advanced Information Science and Technology, International Journal of Big Data Intelligence, Journal of Image and Data Fusion, Journal of Information Processing Systems, and a fellow of the Royal Statistical Society. Other professional memberships include the Association of Computing Machinery (ACM); the Chartered Institute of Logistics and Transport (CIT), South Africa and a senior member of the Institute of Electrical and Electronics Engineers (IEEE).
Intelligent Systems: Does data quality really matter?
Abstract - Use of real-world data in various areas and their electronic availability has put importance of data quality to higher level. In general data quality has syntactic and semantic component. The syntactic component is relatively easy to achieve if supported by tools, while semantic component requires more research. In many cases such data come from different sources, which are distributed across enterprise and are at different quality levels. Special attention needs to be paid to data upon which critical decisions are met in/for intelligent systems. In fact, since most intelligent systems are data-driven, data quality becomes a critical factor for success. In the present keynote address we will focus on the effects of various types of poor data quality (present in varying densities) in selected domains and its adverse effect on intelligent systems and classification/prediction performance.