Configuration Properties for Masking Techniques
You can define how a specific masking technique works by configuring different properties for a masking technique. The Data Masking transformation masks data based on the masking technique that you select and the specific configuration that you set.
The configuration properties that appear depend on the masking technique and the data type. For example, you cannot blur string data. You cannot select a seed value when you use the Random masking technique.
Repeatable Output
Repeatable output is the consistent set of values that the Data Masking transformation returns.
Repeatable output returns deterministic values. For example, you configure repeatable output for a column of first names. The Data Masking transformation returns the same masked value every time the same name appears in the workflow.
You can configure repeatable masking when you use the Random masking technique, Substitution masking technique, or the special mask formats for string data type. Select Repeatable and enter the seed value to configure repeatable masking.
You cannot configure repeatable output for the Key masking technique.
Seed
The seed value is a starting point to generate masked values.
The Data Masking transformation creates a default seed value that is a random number from 1 through 999. You can enter a different seed value. Apply the same seed value to a column to return the same masked data values in different source data. For example, if you have the same Cust_ID column in four tables, and you want all of them to output the same masked values. You can set all four columns to the same seed value.
Mask Format
When you configure key or random masking for string data type, configure a mask format to limit each character in the output column to an alphabetic, numeric, or alphanumeric character.
If you do not define a mask format, the Data Masking transformation replaces each source character with any character. If the mask format is longer than the input string, the Data Masking transformation ignores the extra characters in the mask format. If the mask format is shorter than the source string, the Data Masking transformation does not mask the characters at the end of the source string.
When you configure a mask format, configure the source filter characters or target filter characters that you want to use the mask format with.
The mask format contains uppercase characters. When you enter a lowercase mask character, the Data Masking transformation converts the character to uppercase.
The following table describes mask format characters:
Character | Description |
|---|
A | Alphabetical characters. For example, ASCII characters a to z and A to Z. |
D | Digits. From 0 through 9. |
N | Alphanumeric characters. For example, ASCII characters a to z, A to Z, and 0-9. |
X | Any character. For example, alphanumeric or symbol. |
+ | No masking. |
R | Remaining characters. R specifies that the remaining characters in the string can be any character type. R must appear as the last character of the mask. |
For example, a department name has the following format:
nnn-<department_name>
You can configure a mask to force the first three characters to be numeric, the department name to be alphabetic, and the dash to remain in the output. Configure the following mask format:
DDD+AAAAAAAAAAAAAAAA
The Data Masking transformation replaces the first three characters with numeric characters. It does not replace the fourth character. The Data Masking transformation replaces the remaining characters with alphabetic characters.
Source Filter Characters
When you configure key or random masking for string data type, configure source filter characters to choose the characters that you want to mask.
When you set a character as a source filter character, the character is masked every time it occurs in the source data. The position of the characters in the source string does not matter, and you can configure any number of characters. If you do not configure source filter characters, the masking replaces all the source characters in the column.
The source filter characters are case-sensitive. The Data Masking transformation does not always return unique data if the number of source string characters is fewer than the number of result string characters.
Target Filter Characters
When you configure key or random masking for string data type, configure target filter characters to limit the characters that appear in a target column.
The Data Masking transformation replaces characters in the target with the target filter characters. For example, enter the following characters to configure each mask to contain all uppercase alphabetic characters: ABCDEFGHIJKLMNOPQRSTUVWXYZ.
To avoid generating the same output for different input values, configure a wide range of substitute characters or mask only a few source characters. The position of each character in the string does not matter.
Range
Define a range for numeric or datetime data. When you define a range for numeric or date values, the Data Masking transformation masks the source data with a value between the minimum and maximum values.
Numeric Range
Set the minimum and maximum values for a numeric column. The maximum value must be less than or equal to the field precision. The default range is from one to the field precision length.
Date Range
Set minimum and maximum values for a datetime value. The minimum and maximum fields contain the default minimum and maximum dates. The default datetime format is MM/DD/YYYY HH24:MI:SS. The maximum datetime must be later than the minimum datetime.
Blurring
Blurring creates an output value within a fixed or percent variance from the source data value. Configure blurring to return a random value that is close to the original value. You can blur numeric and date values.
Select a fixed or percent variance to blur a numeric source value. The low bound value is a variance below the source value. The high bound value is a variance above the source value. The low and high values must be greater than or equal to zero. When the Data Masking transformation returns masked data, the numeric data is within the range that you define.
You can mask a date as a variance of the source date by configuring blurring. Select a unit of the date to apply the variance to. You can select the year, month, day, hour, minute, or second. Enter the low and high bounds to define a variance above and below the unit in the source date. The Data Masking transformation applies the variance and returns a date that is within the variance.
For example, to restrict the masked date to a date within two years of the source date, select year as the unit. Enter two as the low and high bound. If a source date is February 2, 2006, the Data Masking transformation returns a date between February 2, 2004, and February 2, 2008.