Data Management
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data_quality_dimension:completeness
Completeness
Definitions
- Completeness of data values is the degree to which all required data values are present.
- Completeness of data elements is the degree to which all required data elements in the dataset are present.
- Completeness of data records is the degree to which all required data records in the dataset are present.
Note
Missing values is a term used to indicate that data values are not complete.
Relations
| Completeness | is a characteristic of | data values |
| Completeness | is a characteristic of | data elements |
| Completeness | is a characteristic of | data records |
| Completeness | is a characteristic of | data files |
| Completeness | is a characteristic of | metadata |
Examples
Incomplete data value
| Name | |
|---|---|
| Johnson |
E-mail is missing value for Johnson.
Incomplete data element
| Surname | City |
|---|---|
| Williams | Paris |
First name is missing as data element.
Incomplete data records
| Surname | City |
|---|---|
| Hank Williams | Paris |
Steve Kerr is missing in this file.
Incomplete data files
A reference file for all cities in UK is missing.
Incomplete metadata
| Data element | Data type | Definition |
|---|---|---|
| Name | Character |
Definition of data element 'Name' is missing.
Reference(s)
DAMA NL (2020). Dimensions of Data Quality (DDQ). Research paper. https://www.dama-nl.org/wp-content/uploads/2020/09/DDQ-Dimensions-of-Data-Quality-Research-Paper-version-1.2-d.d.-3-Sept-2020.pdf
data_quality_dimension/completeness.txt · Last modified: 2024/03/08 13:33 (external edit)