|DCAM Curricula & Instructors|
DCAM Curricula & Instructors
DCAM - "The Practitioner’s Guide to Data Management"
Data management is about implementing change in the way financial institutions operate. And change management is not an effortless process. It can be disruptive and generate resistance from critical stakeholders. It is unlikely that new data management programs will be effective by simply “reading the book.” DCAM training defines the stories behind the capability. We examine what works, what doesn’t and why. DCAM training is interactive and presented in the context of operational reality.
DCAM defines the core criteria needed for the development and implementation of a practical data management initiative. The training curricula covers over 100 data management capabilities organized into the seven core components defined below. Each component is supported by a series of requirement statements including specific objectives, implementation advice and sample artifacts needed for verification of achievement. The formal program is supported by examples and vignettes designed to provide guidance for real world implementation.
1.0 Data Management Strategy & Business Case: defines the vision and the purpose of the data management program. Why is data management important?
DCAM Training Instructors
DCAM training is delivered by John Bottega, who holds the distinction of being one of our industry’s first CDO’s and has served as the head of data management in both the public and private sectors; and Mark McQueen, an expert in building sustainable business processes for data management grounded in his experience in both business process optimization and data management; and Colin Gibson , a technology and data management executive who has driven data architecture and data management initiatives in several major financial services companies. We use this unique combination of practical expertise and foundational industry perspective to examine the principles of data management, the mechanisms for managing change and the challenges of effective data governance.