Data Resource Integration:
Understanding and Resolving a Disparate Data Resource
The data resource in most public and private sector organization has become quite disparate and is not meeting the organization’s business information demand. The data resource needs to be comparate so that it adequately meets both the current and future business information demand. The task of developing a comparate data resource is not easy, but it is far from impossible.
The first step to developing a comparate data resource is to understand why an organization’s data resource goes disparate, and to stop creating any further disparity. Data Resource Simplexity addressed the first step by explaining why the data resource becomes so complex and what can be done to make it simpler. The word simplexity denotes the development of a simple (comparate) data resource from a complex (disparate) data resource. It emphasizes simplicity rather than complexity.
The second step to resolving the existing disparity is to understand all the details of a disparate data resource and set about permanently resolving that disparity to develop a comparate data resource. Data Resource Integration addresses the second step by describing the types of data variability that can be found in a disparate data resource, how to inventory and document disparate data, how to develop an initial common data architecture, how to cross-reference the inventoried disparate data to a common data architecture so they can be understood in a common context, how to designate a preferred data architecture, how to transform existing disparate data to a comparate data resource using that preferred data architecture, and how to integrate an organization’s fragmented data culture into a cohesive data culture that ensures a continued comparate data resource.
Organizations can choose whether to continue with the current transient data integration that only temporarily resolves data disparity, and usually makes the disparate data situation worse, or they can choose to begin an initiative for formal data resource integration that permanently resolves a disparate data resource and a fragmented data culture.
The presentation will be beneficial to anyone in any public or private sector organization that is involved with developing or using the organization’s data resource. It’s applicable to both business professionals and data management professional, and it’s applicable to all levels from executive to technician.
Michael Brackett retired from the State of Washington in June, 1996, where he was the State's Data Resource Coordinator. He was responsible for developing the State’s common data architecture that spans multiple jurisdictions, such as state agencies, local jurisdictions, Indian tribes, public utilities, and Federal agencies, and includes multiple disciplines, such as water resource, growth management, and criminal justice. He is the founder of Data Resource Design and Remodeling and is a Consulting Data Architect specializing in developing integrated data resources.
Mr. Brackett has been in the data management field for nearly 50 years, during which time he developed many innovative concepts and techniques for designing applications and managing data resources. He is the originator of the Common Data Architecture concept, the Data Resource Management Framework, the data naming taxonomy and data naming vocabulary, the Five-Tier Five-Schema concept, the data rule concept, the Business Intelligence Value Chain, the data resource data concept, the architecture-driven data model concept, and many new techniques for understanding and integrating disparate data.
Mr. Brackett has written eight books on the topics of application design, data design, and common data architectures. His books Data Sharing Using a Common Data Architecture and The Data Warehouse Challenge: Taming Data Chaos explain the concept and uses of a common data architecture for developing an integrated data resource. His book on Data Resource Quality: Turning Bad Habits into Good Practices explains how to stop the creation of disparate data. His book on Data Resource Simplexity is about an approach to data resource management that avoids the creation of disparate data. His latest book on Data Resource Integration explains formal data resource integration, compared to transient data integration. He has written numerous articles and is a well-known international author, speaker, and trainer on data resource management topics.
Mr. Brackett has a BS in Forestry (Forest Management) and a MS in Forestry (Botany) from the University of Washington, and a MS in Soils (Geology) from Washington State University. He was a charter member and is an active member of DAMA-PS, the Seattle Chapter of DAMA International established in 1985. He saw the formation of DAMA National in 1986 and DAMA International in 1988. He served as Vice President of Conferences for DAMA International; as the President of DAMA International for 2000 through 2003; and as Past President of DAMA International for 2004 and 2005. He was the founder and first President of the DAMA International Foundation, an organization established for developing a formal data resource management profession, and is currently Past President of the DAMA International Foundation. He was Production Editor of the DAMA-DMBOK released in April, 2009.
Mr. Brackett received DAMA International’s Lifetime Achievement Award in 2006 for his work in data resource management, the second person in the history of DAMA International to receive that award (Mr. Brackett presented the first award to John Zachman in 2003). He taught Data Design and Modeling in the Data Resource Management Certificate Program at the University of Washington, and has been a member of the adjunct faculty at Washington State University and The Evergreen State College. He is listed in Who's Who in the West, Who's Who in Education, and International Who's Who.