Principle and Practice: Leveraging the DMBOK to improve modeling outcomes
Laura Sebastian-Coleman, Aetna
The DMBOK2 articulates a set of 13 principles for data management. These recognize data’s unique properties, its value, and the work involved in ensuring its quality. The principles apply to data management generally, but they also inform the work of each data management knowledge area. This presentation will explore the thinking behind the principles and will focus on their application to the data modeling process. The session will be interactive, with participants invited to share their insights about the ways in which a comprehensive vision of data management can support the work of individual practitioners.
Laura Sebastian-Coleman, Data Quality Lead at Aetna, has worked on data quality in large health care analytic data warehouses since 2003. Cigna is a global health service company dedicated to helping people improve their health, well-being and sense of security. Laura has implemented data quality metrics and reporting, launched and facilitated data quality working groups, and contributed to data consumer training programs. She has led efforts to establish data standards and to manage metadata for large analytic data warehouses. DAMA Publications Officer, she also received IAIDQ’s Distinguished Member Award in 2015. She was production editor for the DAMA-DMBOK2and author of Measuring Data Quality for Ongoing Improvement (Morgan Kaufmann, 2013).