Data Quality Dimensions
CompTIA Data+ DA0-001 (V1) PBQ
This exercise includes matching data quality dimensions, like accuracy, completeness, and timeliness, to their corresponding definitions or real-world examples.
Consistency
Relevance
Precision
Uniqueness
Completeness
Validity
Traceability
Accuracy
Timeliness
Integrity
Data that is applicable and useful for a specific purpose or decision-making
Data that is uniform across databases or datasets without contradictions
The extent to which records are distinct with no duplicates
The ability to track the origins, updates, or sources of the data
The adherence of data to rules, formats, or constraints like a specific data type or pattern
The level of detail or granularity in the data
Data that has all required values and is not missing crucial information
Data that maintains proper relationships or linkages between records or datasets
Data that is available when it is needed and is up-to-date
The degree to which data reflects the real-world object or event it represents