Functions

Functions are used to anonymize data using a rule. Gigantics offers default functions that can be modified while editing the rule. The function options vary depending on the type of data contained in the table cell.

This is the list of available functions:

• Mask
• Shuffle
• List
• Delete
• Blank

Mask

Masks the data into another value by transforming or replacing current data value. The options are:

Text transform (string/char)

Transforms the text value into the selected format.

	Value		New value
None	foo bar	->	foo bar
Uppercase	foo bar	->	FOO BAR
lowercase	FOO Bar	->	foo bar
Title case	foo bar	->	Foo Bar
Snake case	foo bar	->	foo_bar
Kebab case	foo bar	->	foo-bar

Replace (any)

Replaces the selected value with a different one

Alphabetical chars / Digits / Symbols

Replaces each alphabetic character with a different character. This replacement can be partial or conditional:

• With: Select the character with which all alphabetic characters will be replaced:

Value	With		New value
foo bar	x	->	xxx xxx
testing char	x	->	xxxxxxx xxxx
1234	0	->	0000
1234753-H	0	->	0000000-H
123.65	,	->	123,65
$99	£	->	£99

• Field length: Additionally, it allows you to change the length of the new value. It can have 3 configurations:
  • Initial: Keep the length of the current value.
  • Random: Each field of the new value will have a different length than the original value.
  • Fixed: All values will have the same length.

Type	Value	With	Length		New value
Initial	foo bar	Y	-	->	YYY YYY
Initial	123456	0	-	->	000000
Initial	859.939.292	,	-	->	859,939,292
Random	testing char	Y	-	->	YY YYYYYYY
Random	345	1	-	->	1111
Fixed	new gigantics	Y	2	->	YY YY
Fixed	4321	9	2	->	99

• Condition: Adds a condition that allows to keep parts of the string or to replace a substring.
  • Keep: Select this option to keep the first or last X characters.
  • Replace: Select this option to replace the first or last X characters.

Value	With	Condition	# Chars		New value
foo bar	z	Keep first	2	->	foz zzz
foo bar	z	Keep last	4	->	zoo bar
testing char	z	Replace first	1	->	zesting char
new gigantics	z	Replace last	3	->	new giganzzz

Word

Replace full word to other new

Value	With		New value
John	Test	->	Test
Sarah	Test	->	Test
Sarah Cruz	Test	->	Test Test

Regex

Replace chars/numbers/symbols using regex

Value	Regex	Replace with		New value
test@email.com	.+?(?=@)	xxxx	->	xxxx@email.com
(+34) 603402022	(?:00\|\+)\?[0-9]{2}	0	->	(+00) 603402022

Field

Replace all field data to new value

Value	With		New value
test multiple field	undefined	->	undefined
769C Honey Creek St.	Unamed Road	->	Unnamed Road
data:image/png;base64	img	->	img

Shuffle

This function collects the column values and mixes them randomly.

Example:

Input:

• Shuffle column: city
• Table:

Input:

#	email	street	city	state
1	debra.burks@yahoo.com	9273 Thorne Ave.	Orchard Park	NY
2	kasha.todd@yahoo.com	910 Vine Street	Forney	TX
3	tameka.fisher@aol.com	769C Honey Creek St.	Redondo Beach	CA

Output:

#	email	street	city	state
1	debra.burks@yahoo.com	9273 Thorne Ave.	Forney	NY
2	kasha.todd@yahoo.com	910 Vine Street	Redondo Beach	TX
3	tameka.fisher@aol.com	769C Honey Creek St.	Orchard Park	CA

Suffle group

This is a variant of shuffle where the selected fields are grouped together so that the selected fields are mixed in the same way and not each field independently.

Example:

Input:

• Shuffle group: city and state columns
• Table:

#	email	street	city	state
1	debra.burks@yahoo.com	9273 Thorne Ave.	Orchard Park	NY
2	kasha.todd@yahoo.com	910 Vine Street	Forney	TX
3	tameka.fisher@aol.com	769C Honey Creek St.	Redondo Beach	CA
4	daryl.spence@aol.com	988 Pearl Lane	Uniondale	NY

Output:

#	email	street	city	state
1	debra.burks@yahoo.com	9273 Thorne Ave.	Redondo Beach	CA
2	kasha.todd@yahoo.com	910 Vine Street	Uniondale	NY
3	tameka.fisher@aol.com	769C Honey Creek St.	Forney	TX
4	daryl.spence@aol.com	988 Pearl Lane	Orchard Park	NY

List

Select a random value from a list. The lists available here are created from the Datasets area of the project configuration items. If the number of records is greater than the number of records in the dataset, the values will be repeated.

Example:

Input:

• Column: fruit
• Dataset: [Banana, Apple, Pear]
• Table:

#	fruit	price
1	Pineapple	$0.60
2	Strawberry	$0.40
3	Coconut	$2.95

Output:

#	fruit	price
1	Pear	$0.60
2	Banana	$0.40
3	Apple	$2.95

Delete

This function will NULL the selected column. This function can’t be used on columns which are specified as NOT NULL.

Example:

Input:

• Delete column: price
• Table:

#	fruit	price
1	Pineapple	$0.60
2	Strawberry	$0.40
3	Coconut	$2.95

Output:

#	fruit	price
1	Pear	NULL
2	Banana	NULL
3	Apple	NULL

Blank

Remove the value of the field.

Example:

Input:

• Delete column: price
• Table:

#	fruit	price
1	Pineapple	$0.60
2	Strawberry	$0.40
3	Coconut	$2.95

Output:

#	fruit	price
1	Pear
2	Banana
3	Apple