DOQS Discrete Detail Pattern

The Discrete Detail Pattern attempts to eliminate business exception conditions from a data model by adding successive layers of attributive definition to any compplex fundamental entity. These successive layers each add increasingly discrete detail to the data model.    


  • We often use data models to make broad sweeping statements about the business.
  • This forces us to generalize many attributes into entities into which they don't belong.
  • By breaking out the related entities into increasingly detailed attributive entities, the ambiguities and exceptions inherent in these generalizations can be identified early.
  • The goal is that the model be accurate for all possible cases. No exceptions!
  • Breaking fundamental entities out using increasingly detailed attributive entities promotes better understanding of the data, and expanded opportunities to use the data to support the business.
  • It also prevents us from building business systems at the wrong level of detail.
  • It turns out that by always connecting relationships to the bottom of our discrete detail "stack" we'll prevent most level-of-detail defects.
  • This means challenging any relationship that connects to the stack anywhere except at the bottom entity type.


  • A decomposing "stack" of attributive entity types, the bottom of which appears arbitrary (e.g. not limited by natural or governmental laws).
  • This pattern is taught in the Quality-Based Data Modeling course.

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