A frequently overlooked aspect of information quality management is that of data model quality. We often build data models quickly, in the midst of a development project, and with the singular goal of database design. Yet the implications of those models are far-reaching and long-lasting. They affect the structure of implemented data, the ability to adapt to change, understanding of and communication about data, definition of information quality rules, and much more. In many ways, high-quality information begins with high-quality data models. The Data Model Scorecard® provides the tools needed to measure and manage data model quality.

The Scorecard is a set of ten categories for validating a data model. We will explore best practices from the perspectives of both the modeler and reviewer, and you will be provided with a template to use on your current projects. Each of the following categories heavily impacts the usefulness and longevity of the model. Our discussion of them will be accompanied by many examples. More...