Data Scientist, Enterprise Architecture Department at the University of Auckland, New Zealand
Mozhgan Memari: Mozhgan (pictured), is a data scientist at the Enterprise Architecture Department at the University of Auckland designing a data quality framework to improve the quality of data stored in the university data warehouse and to resolve some inconsistencies in data. She has more than 6 years’ experience working with different data domains and applying data quality features over data in different companies. Furthermore, she received a PhD degree in semantics in databases from University of Auckland. In her research, Mozhgan has addressed a long-standing gap between the industry standard for data management, SQL, and its implementations in real database systems.
Bruce Cassidy: Bruce is a database professional, and has been working with data systems for almost thirty years. The last ten years has been spent working with various facets of business intelligence, including strategy, architecture, design and implementation. His career includes the implementation of New Zealand’s first SMP Oracle database server running on Windows NT and more recently an award-winning green-fields BI strategy and design.
This paper introduces a data quality (DQ) framework and develops a methodology for assessment and management of the DQ in the University data warehouse (DW). The framework includes a technical design that defines the required metrics, techniques and tools to measure, store and report DQ values in the DW. It is the first that integrates […]