Dependent masking substitutes multiple columns of source data with data from the same dictionary row.
When the Data Masking transformation performs substitution masking for multiple columns, the masked data might contain unrealistic combinations of fields. You can configure dependent masking in order to substitute data for multiple input columns from the same dictionary row. The masked data receives valid combinations such as, "New York, New York" or "Chicago, Illinois."
When you configure dependent masking, you first configure an input column for substitution masking. Configure other input columns to be dependent on that substitution column. For example, you choose the ZIP code column for substitution masking and choose city and state columns to be dependent on the ZIP code column. Dependent masking ensures that the substituted city and state values are valid for the substituted ZIP code value.
You cannot configure a column for dependent masking without first configuring a column for substitution masking.
Configure the following masking rules when you configure a column for dependent masking:
The name of the input column that you configured for substitution masking. The Data Masking transformation retrieves substitute data from a dictionary using the masking rules for that column. The column you configure for substitution masking becomes the key column for retrieving masked data from the dictionary.
The name of the dictionary column that contains the value for the column you are configuring with dependent masking.