International IFIP Conference on Artificial Intelligence Theory and Applications

Keynote:

Dynamic Data Mart  for Enterprise Heterogeneous Big Data and System Integration through utilizing Data Marshalling, Data Meshing Data Mining  and Automated Data Intelligence

 Elizabeth Chang FIEEE

UNSW at Australian Defence Force Academy

Elizabeth.chang@unde.edu.au

Today large enterprises and corporates are facing several major issues while managing their data and information. The divisions and departments typically have had their own information systems, legacy or near retired systems and data repositories, either in their own data centers or on excel sheets.

Frequently due to the lack of a single unified data source at the corporate level, we often see operational database everywhere, resultant data marts everywhere that lead to processes, polices and rules everywhere, and all kinds of dashboards everywhere within the organization or enterprise.

Due to this lack of ICT strategies, and understanding the importance of ICT governance, each division or department often has developed their own Data Management approach to cope with their business operations. This has resulted in out of control of enterprise data management, which potentially leads to greater risks to the organization, as data and information are the life blood of modern business enterprises, leading to a multitude of vulnerabilities to the business and its capability.

In addition, these disparate new and legacy systems lack sustainability because they cannot meet the dynamic business needs and there will no system capability for self-organized business intelligence, and they cannot adapt to the continuous changing needs of the enterprise.

Existing Enterprise Data Warehouses methods are systems which have been constructed by experts in order to answer in an efficient way business oriented queries at various levels of granularity along predefined dimensions. They have fixed designs and implementations, and they are not suitable for today’s dynamic business changing environment. Changes would require Data Warehouse experts to update the Corporate Data Warehouse Design and implementation each time when business process change or the business requires somewhat different information or intelligence. This is often impractical as software vendors tend to move on much more frequently than information systems they build. We have developed a modern Dynamic data Mart as an approach to Integrating Heterogeneous Big Data based on a modern technology.

In this keynote, Prof Chang will present an Advanced Dynamic Data Marts architecture and design principles that is built around 6 main functions, 3M (Data Marshalling, Data Meshing and Data Mining,) and 3R (Reconciliation, Representation and Recommendation), leading to mining the user’s behavior, user decision making processes, create and drop views automatically through usage mining and adaptive data mart dimensions, facts and data associations relationships in a timely manner. This keynote is presented with a real time demonstration of such a dynamic data mart that is built for a large enterprise, such as the Australian Defense Force.

Biography

Professor Elizabeth Chang is a Fellow of the IEEE (USA). Professor Elizabeth Chang is Professor in IT and Logistics and Canberra Fellow at the University of New South Wales at the Australian Defense Force Academy (ADFA). She hold BSc, MSc and PhD in Computer Science and Software Engineering and has been CIO/CTO in a Multinational Logistics and Transport Company in Hong Kong.

Professor Chang leads the research group at UNSW Canberra at ADFA targeting the key issues in Logistics big data management over  heterogeneous logistics, supply and transport networks, predictive analytics, situation awareness, cyber-physical systems, asset sustainment, trust measurement and prediction and  risk assessment and quantification.

She has delivered 41 Keynote/Plenary speeches largely at major IEEE Conferences and  the most recent ones are in the area of Semantics, Ontologies, business intelligence, data quality, and the Internet of Things etc.   She has published 7 authored, 8 edited books, 15 book chapters, 100+ International journal papers and over 300 refereed conference papers with an H-Index of 35 (Google Scholar). Her academic achievements include 22 Competitive Research Grants including 11 Australian Research Council (ARC) Grants worth over $15 million. She has supervised/co-supervised 41 PhD theses to completion, 21 Maters Theses and 16 Post-docs.

She is Chair for IEEE IES Technical Committee on Industrial Informatics (2014-2015). She is Chair of the IFIP International Working Group 2.12/12.4 on Web Semantics.(2012-2015). She is also an Associate Editor for IEEE Transactions on Industrial Electronics (since 2007) and Guest Editor on IEEE Transactions on Industrial Informatics (since 2005), Co-editor in Chief for International Journal on Engineering Intelligent Systems and the International Journal of Computer Systems Science and Engineering. She has been General Chair and Technical Chair for over 20 International and IEEE Conferences.