Are you struggling to understand the data you need to support your business activities? Are you frustrated over data that don’t answer your questions or provide the wrong answers to your questions? Are you worried that your organization is not adequately supporting its citizens or customers? Are you concerned over civil or criminal liability for the quality and use of your data? If the answer to any of these questions is Yes, they you need to read Data Resource Understanding to help you and everyone in your organization thoroughly understand the data they need to support the business activities.

Most public and private sector organizations have no formal method for thoroughly understanding the data needed to support their business activities. They seldom have a method that begins with the organization’s perception of the business world and continues through a formal Data Resource Development Cycle to produce a high quality, thoroughly understood data resource that fully supports the organization’s current and future business information demand.

Data Resource Data provided the complete detailed data resource model for understanding and managing data as a critical resource of the organization. Data Resource Understanding is the companion book to Data Resource Data. It provides a detailed explanation of how to thoroughly understand an organization’s data resource and to document that understanding with Data Resource Data. Together they provide an organization with the foundation for properly managing their data as a critical resource.

Like Data Resource Simplexity, Data Resource Integration, Data Resource Design, and Data Resource Data, Michael Brackett draws on over half a century of data management experience, in a wide variety of different public and private sector organizations, to understand and document an organization’s data resource. He leverages theories, concepts, principles, and techniques from many different and varied disciplines, such as human dynamics, mathematics, physics, chemistry, philosophy, and biology, and applies them to the process of formally documenting an organization’s data resource.