During a routine data-profiling exercise on a new data warehouse, an analyst runs a foreign-key validation between the SalesFacts fact table and the ProductDim dimension table. The profiler report shows that 97.8% of the 1.2 million SalesFacts.ProductID values are found in ProductDim.ProductID, leaving 26,769 rows that reference a non-existent product. Which data-quality dimension is this report primarily quantifying?
The report is measuring consistency. A key aspect of consistency is referential integrity, which ensures that values meant to link records across different tables are valid. In this case, the profiler is calculating what percentage of foreign-key values (SalesFacts.ProductID) have a matching primary-key value in the related dimension table (ProductDim.ProductID). Completeness would focus on whether mandatory fields are populated, uniqueness would evaluate duplicate records, and timeliness would consider how current the data is. None of those other dimensions rely on cross-table validation.
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CompTIA Data+ DA0-002 (V2)
Data Governance
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