Data Resource Design: Reality Beyond Illusion

Are you struggling with the formal design of your organizations data resource? Do you find yourself forced into generic data architectures and universal data models? Do you find yourself warping the business to fit a purchased application? Do you find yourself pushed into developing physical databases without formal logical design? Do you find disparate data throughout the organization? If the answer to any of these questions is Yes, then you need to read Data Resource Design to help guide you through a formal design process that produces a high quality data resource within a single common data architecture.

Most public and private sector organizations do not consistently follow a formal data resource design process that begins with the organizations perception of the business world, proceeds through logical data design, through physical data design, and into implementation. Most organizations charge ahead with physical database implementation, physical package implementation, and other brute-force-physical approaches. The result is a data resource that becomes disparate and does not fully support the organization in its business endeavors.

Data Resource Design describes how to formally design an organizations data resource to meet its current and future business information demand. It builds on Data Resource Simplexity, which described how to stop the burgeoning data disparity, and on Data Resource Integration, which described how to understand and resolve an organizations disparate data resource. It describes the concepts, principles, and techniques for building a high quality data resource based on an organizations perception of the business world in which they operate.

Like Data Resource Simplexity and Data Resource Integration, Michael Brackett draws on five decades of data management experience building and managing data resources, and resolving disparate data in both public and private sector organizations. He leverages theories, concepts, principles, and techniques from a wide variety of disciplines, such as human dynamics, mathematics, physics, chemistry, philosophy, and biology, and applies them to properly designing data as a critical resource of an organization. He shows how to understand the business environment where an organization operates and design a data resource that supports the organization in that business environment.