IDQ Asia Pacific Webinars: with Shazia Sadiq
Navigating the Data Quality Landscape
The data (and information) quality domain is supported by several decades of high quality research contributions and commercial innovations.
Research and practice in data and information quality is characterized by methodological as well as topical diversity. The cross-disciplinary nature of data quality problems as well as a strong focus on solutions based on the fitness for use principle has further di-versified the related body of knowledge. Although research pluralism is highly warranted, there is evidence that substantial developments in the past have been isolationist. As data quality increases in importance and complexity, there is a need to motivate exploitation of synergies across diverse research communities.
The above factors warrant a multi-pronged approach to the study of data quality management spanning: organizational aspects, i.e. strategies to establish people, processes, policies, and standards required to manage data quality objectives; architectural aspects, i.e. the technology landscape required to deploy developed processes, standards and policies; and computational aspects which relate to effective and efficient tools and techniques for data quality. Despite a significant body of knowledge on data quality management, the community is lacking a resource that provides a consolidated coverage of data quality over the three different aspects. This gap motivated me to assemble a point of reference that reflects the full scope of data quality research and practice, which has now been published as the “Shazia Sadiq (Ed), Handbook of Data Quality Research and Practice, Springer 2013.”
In this webinar, I will firstly present an analysis of the data quality body of knowledge. I will then present a snapshot of contributions from research and practitioner communities on organisational, architectural and computational aspects. The webinar will provide you with a comprehensive list of resources that you can pursue as relevant for your data quality objectives.
About the Author
Shazia Sadiq is Professor of Information Systems at the School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia. She is co-leader of the Data and Knowledge Engineering (DKE) research group and is involved in teaching and research in databases and information systems. Shazia holds a PhD from The University of Queensland in Information Systems and a Masters degree in Computer Science from the Asian Institute of Technology, Bangkok, Thailand. Her main research interests are innovative solutions for Business Information Systems that span several areas including business process management, governance, risk and compliance in information systems, and data quality management. Shazia has published over 100 peer-reviewed publications including ERA A/A* journals such as VLDBJ, TKDE, and Information Systems, as well as high ranking conferences such as SIGMOD, ICDE, ER, BPM, and CAiSE. She serves on the editorial board, and program committees of over 30 major journals and conferences. She is currently vice-chair of the National Committee on Information and Communication Sciences, The Australian Academy of Science and a director of the IAIDQ Asia Pacific board.
About the Author
Ram Kumar is a senior member of the Chief Analytics Office at Insurance Australia Group (IAG), after having worked as Chief Information Officer, Group Chief Technology Officer and Senior Enterprise Architect at IAG. Previously Ram worked in the Enterprise Architecture Group of New South Wales Police, and also as Manager of International IT Open Standards Group at the Organisation for the Advancement of Structured Information Standards in the USA.
Ram is a member of the board of IAIDQ Asia Pacific.