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Common for unconditional and conditional column masking:
Column masking is not applied to Member Properties, Unknown and Calculated members, and Predefined time type hierarchy.
Currently, column masking does not support the SQL interface.
Partial masking on numerical dimension field is not supported.
The original column data is preserved while masking because numeric data is masked with a number, and a date is masked with a date. You can specify a fixed pattern or a Regex expression for any string data type.
The masked value is displayed while browsing the semantic model on any BI tool with an MDX connection.
If using Tilde (~) for column masking and want to apply a filter on the masked value from Kyvos UI, then you must change the value of the field value separator as the default value of the kyvos.filter.value.separator property is also Tilde (~). Hence, you must change the default value of this property so that column masking with the Tilde character can function.
To apply column masking to a pre-defined hierarchy, you must select the full name of the hierarchy.
You can also create, delete, update, save, and assign column masking rules by using the Security Rest API's.
For conditional column masking:
Data conditions are only allowed on dimensions (level or attribute). Conditions based on measures are not supported.
Conditional masking on date field is not supported.
Conditional masking on measure field is not supported.
Merging of measure values against fully masked only attribute or single level hierarchy is not supported
Unconditional column masking
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Unconditional In unconditional column masking is used in Spark-based deployments where , the entire column is masked uniformly. In this approach, any user who accesses the masked column will see only obfuscated or masked values rather than the actual data, regardless of their access permissions.
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From the Toolbox, click Semantic Models.
Select the semantic model name from the list and click the Process tab if needed.
Click the Action menu (...) in the work area, then click Data Security.
If the option is not displayed, you must save the semantic model and try again.Click users or groups that this rule will apply to.
Click the plus sign in the Rules column.
Add a rule name and description.
From the Column Level area, click Mask Data and select Conditionally mask data, and then select the field on which you want to apply the column masking.
Click the Conditional Mask Data link and click the field link. The field list is displayed. Select the field that you want to conditionally mask.
Click the value link, and the Conditional Mask with dialog box is displayed. You must enter the required value for conditional column masking. The available choices vary depending on the data you are using.
For any string data type, choose one of the following:
Fixed: Use this option to specify a fixed value for column masking.
Enter a value that you want to apply for column masking. The entered value is displayed in the Preview area.
NOTE: You can specify any character or special characters, such as #, *, @. If you keep the field blank, then while semantic model browsing, the field value is displayed as blank.
Regex: Use this option to specify a Regex expression for column masking.
Enter a Regex expression that you want to specify for the field value, and then provide a value that you want to use for column masking.
You can also select a Regex expression from the Choose from common expressions list.
To verify whether the Regex expression is successfully masked with the value, enter a relevant value in the Test Value field. The result is displayed in the Preview field. If the expression is not masked successfully, you can modify the expression, as needed.
NOTE: In an expression, the Delimiter (/) and the flags (g,m,i,u,s,d) are not supported.
Click Select the field link to select the field on through which you want to apply set a condition for conditional column masking.
Click the plus sign to add additional fields, if required.
Click Add.
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