Table of Contents

Search

  1. Preface
  2. Introduction to Test Data Management
  3. Test Data Manager
  4. Projects
  5. Policies
  6. Data Discovery
  7. Creating a Data Subset
  8. Performing a Data Masking Operation
  9. Data Masking Techniques and Parameters
  10. Plans and Workflows
  11. Monitor
  12. Reports
  13. ilmcmd
  14. Data Type Reference
  15. Data Type Reference for Hadoop

Advanced Masking Parameters

Advanced Masking Parameters

Configure parameters for each column that you create in an advanced masking rule.
The following table describes the general properties that you can configure for input, output, and variable columns:
Parameter
Description
Column Name
The name of an input, output, or variable column. Enter any name. The name does not have to match the name of a column in the source. When you assign the rule to source data in a project, you map the column names in the rule to column names in the database.
Column Type
The column type. You can configure the following types of columns:
  • Input. Receives the source data.
  • Variable. A temporary column that contains intermediate values. You can apply masking rules to variable column values in order to mask data before returning data to output columns.
  • Output. Returns the output data. You can apply an expression or a masking rule to variable column data and return the data in the output column.
Datatype
The datatype of the column.
Precision
The precision for the column. The maximum number of digits or the maximum number of characters that the column can accommodate. For example, 798.650 has a precision of 6.
Scale
Number of digits to the right of the decimal point in a number.
Mandatory
Indicates if you must assign the column to a column in the source. Applies to input and output columns.
The following table describes the masking properties that you can configure for variable columns and output columns:
Parameter
Description
Expression
An expression to apply to the variable column. You can create the expression in the Expression Builder.
Masking Rule
Applies a masking rule to the input column and writes the results in the variable column. You can enter the following parameters.
  • Condition. Defines whether an input column should be masked or not. If the condition is true, the
    Data Integration Service
    masks the column.
  • Rule. The data masking rule to apply to the input column.
  • Override properties. You can change the data masking rule parameters if the rule owner enabled the rule to be overridden.
  • Input column. The name of the input column to apply the masking rule to. Select an input column from the columns that you added to the rule.
Condition Input
Applies an expression to the Output column only. Select a condition from the list. If you applied conditions on the input column, you can use it for the output column.
Dependent
Applies dependent masking. Dependent masking replaces the value of a column based on the values returned from a dictionary row for another column. You must define substitution masking for another column before configuring a column for dependent masking.
Enter the following parameter:
  • Input column. The name of the input column that you configured for substitution masking.
  • Dictionary column. Choose the dictionary column to replace the dependent column with.