2.4.5.1 Types of Data Quality Checks
The following are the types of Data Quality Checks and their definitions:
Data Quality Check | Definition |
---|---|
Blank Value Check | Identifies if the base column is empty considering the blank space. |
Column Reference/Specific Value Check | Compares the base column data with another column of the base table or compare with any attribute of compatible data type from a referenced dimension of a base entity. |
Data Length Check | Checks for the length of the base column data by using a minimum and maximum value, and identifies if it falls outside the specified range. |
Duplicate Check | Is used when a combination of the column is unique and identifies all duplicate data of a base table in terms of the columns selected for the duplicate check. |
List of Value Check | It can be used to verify values where a dimension/master table is not present. This check identifies if the base column data does not match with a value or specified code in a list of values. |
NULL Value Check | Identifies if NULL is specified in the base column. |
Referential Integrity Check | Identifies all the base column data that has not been referenced by the selected column of the referenced table. Here, the user specifies the reference table and columns. |
Range Check | Identifies if the base column data falls outside a
specified range of a Minimum and Maximum value.
Value Needs to be between 0 and 100. |
Uniqueness Check for Numeric Identifiers in Dimension | Check to identify duplicates in Numeric Identifier
Attribute for a Dimension Entity.
Check to identify changes in Numeric Identifier Attribute for a Dimension Entity for the same Business Key member. Note: Threshold option is currently not supported for custom check. |
Special Character Check | Identify business term contains only the allowed set of
special characters.
Currently, DFCS has preconfigured
rules for the following Business Terms:
|
Note:
The check category for custom DQ check referencing to dimensions will be shown as Custom Check in the Data Quality Result reports.