1.1.1 Types of Data Quality Checks

The following are the types of Data Quality checks and their definitions:

Table 1-1 Data Quality Checks

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.
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.
Generic Check	Check to identify duplicates in Textual Identifier Attribute for a Dimension Entity: Purpose: Ensure that there are no duplicate entries for textual identifiers (e.g., names, codes) in the dimension entity. Check Process: Extract the textual identifier (e.g., "Customer Name" or "Product Code"). Perform a duplicate search to identify if the same textual identifier appears more than once. Flag duplicate entries for correction.
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.
Special Character Check	Identify business term contains only the allowed set of special characters. Currently, AFCS has preconfigured rules for the following Business Terms: Legal Entity Code Legal Entity Description Legal Entity Name Data Source Code Data Source Description

The controls are specific to reports.

Note:

The check category for custom DQ check referencing to dimensions will be shown as Custom Check in the Data Quality Result reports.