Basic Guidelines for Data Integrity in Enterprise Architecture

The original Relational Model of Data for Large Shared Data Banks [acm.org] was a major milestone in the history of information technology that has undergone changes in understanding over the years. Despite the fact There is No Database Magic [kimballgroup.com], A Review of Relational Concepts [wikipedia.org] is useful to avoid widespread Logical-Physical Confusion [dbdebunk.com]. Conceptual, Logical, Physical: It is Simple [zachman-feac.com] as a framework to ensure enterprise data architecture is transformative across multiple representations.

That is not to say the real world always maps well to the simplest structures, after all Starbucks Does Not Use Two-Phase Commit [eaipatterns.com]. Also, aside from logical correctness, the problem of Basic Human Error Rates [panko.com] must be also managed into any data quality metric.