🛠️ Method 1: Manual Creation of a New Utility Set

Steps to Create a New Utility Set Manually

1. Navigate to Utility Sets Page:

   • Click on the Create Button on the Utility Set view. You will be directed to the Create New Set view.

2. New Utility Set Details:

   • Enter the Utility Set Name and set the Creation Method to Manual.
   • Click Next to proceed.
   • 

3. Edit Fields and Utility Parameters:

   • On the next screen, users can enter single or multiple tables they want to anonymize.
   • Click on Add Tables:
     • A side panel will appear to fill in table details.
     • Table ID: Represents the primary key of the table.
     • Fields: Specify the columns to anonymize (multiple columns can be added as comma-separated values).
     • 

4. Add Conditions (Optional):

   • Click Add a Condition to further filter the selected table data.
   • 
   • The following details are required to add a condition:

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Condition Details Table

Input Field	Description	Values	Screenshot
Condition Name	Input field to define the name of the condition
Tables	Refers to the tables this condition will apply to	All in Utility Set / Particular Table
Fields	Column of the table
Function		Is, Is Not (Blank Equal, Greater Than, Less Than, Start With, On the List (manual entry), Linked [table].[field])
Values	Defines the value of the Field in the database	Input field to specify the conditions

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Example:
Condition: Filtering on the table patient where the value of the column branch is equal to Mining.

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Managing Table Details in the Utility Set

• Edit Table Details:
  • Click on the Table Name or Edit Option in the Utility Set Table.
  • View the selected table and its respective columns for anonymization.
  • Users can:
    1. Delete or add a new column for anonymization.
    2. Define the Utility Parameter, Utility Parameter Conditions, and Privacy Relevance.

Utility Parameters and Conditions

Utility Parameters	Utility Conditions	Description
No Change	N/A	Leaves the data unchanged.
Clear Values	N/A	Clears the data in the selected fields.
Email	Dummy Domain, Keep Domain, All Caps	Anonymizes email addresses with additional formatting options.
Name	First Name, Last Name, All Caps, Full Name, Name	Handles name fields with specific conditions for first name, last name, etc.
Consistent ID	N/A	Generates a consistent identifier for tracking records.
Fixed Value	Input Field	Replaces the field with a fixed value.
Date	Same Year, Random, Adult, Consistent	Anonymizes date fields while retaining some options for consistency.
Phone Number	Random, Remove Country Code, CONSISTENT	Handles phone numbers by formatting them or generating new numbers.
Number	N/A	Randomizes or anonymizes numerical data.
Custom Expressions	N/A	Allows custom regular expressions or formats to be applied to the data fields.
Org Name	Company Name, Bank Name, Remove Org Suffix , All Caps	Anonymizes Organization Name to either Company Name or Bank Name based on the utility condition selected. Maintains consistency during the anonymisation.
Material Name	Fixed Mat, Random Mat, All Caps	Anonymizes the Material Name different formats based on the selected condition.
IBAN	N/A	Anonymizes the IBAN to an IBAN of the same country while retaining the length and the pattern.
Account Number	N/A	Anonymizes the Account Number using format preserving encryption. Retaining the length and numeric pattern.

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Condition-Specific Details:

1. Email Conditions:

   • Dummy Domain: Replaces the email domain (e.g., example.com).
   • Keep Domain: Retains the original domain while anonymizing the rest of the email.
   • All Caps: Anonymizes the original email and converts the entire email to uppercase.

2. Name Conditions:

   • First Name: Anonymizes the name using the first_name anonymisation rule.
   • Last Name: Anonymizes the name using the last_name anonymisation rule.
   • All Caps: Anonymizes the name and converts the name to uppercase.
   • Full Name: Anonymizes the name using the full name anonymisation rule.
   • Name: This utility condition is used for the CONSISTENT anonymisation of names across applications. Appsafe, Filesafe, AISafe, Shared Point or AI Powered Run.
   • If the name consists of any salutations like Mr., Mrs., Dr. Etc. then the system doesn’t treat the salutations as part of the Name. Below is a list of salutations which are currently removed while doing an anonymisation.
   • For Example: Emma Smith will be anonymized to Dorothy1 Williams1
   • Mrs Smith will be anonymised to Williams1
   • Ms. Emma will be anonymised to Dorothy1

   List of Salutations Currently Detected by the System

Salutation	Example Name
MR	Mr. John Smith
MRS	Mrs. Elizabeth Johnson
MS	Ms. Angela Baker
MISS	Miss Emily Clark
MX	Mx. Taylor Morgan
DR	Dr. Alan Grant
PROF	Prof. Susan Walker
SIR	Sir James Windsor
MADAM	Madam Catherine Blake
DAME	Dame Margaret Cole
LORD	Lord Henry Cavill
LADY	Lady Charlotte Grey
REV	Rev. Thomas Hill
FR	Fr. Michael O'Brien
RABBI	Rabbi David Cohen
IMAM	Imam Ahmed Hassan
SHEIKH	Sheikh Omar Al-Fulan
PRES	Pres. Laura Bennett
PM	PM Richard Matthews
CH	Ch. Rachel Mendes
GOV	Gov. William Parker
MAYOR	Mayor Linda Torres
HON	Hon. Deborah Patel
SEN	Sen. Robert Greene
REP	Rep. Maria Lopez
AMB	Amb. Jonathan Li
SEC	Sec. Amanda Brooks
ABP	Abp. Francis Doyle
CARD	Card. Leonardo Rossi
BP	Bp. Gregory Hughes
POPE	Pope Benedict XVI
CAPT	Capt. Sarah Nolan
MAJ	Maj. Eric Daniels
COL	Col. Jacob Steele
GEN	Gen. Laura Whitman
CMDR	Cmdr. Anthony Reid
LT	Lt. Chloe Zhang
SGT	Sgt. Brian O'Connor
CPL	Cpl. Kevin Blake
CHIEF	Chief Monica Reyes
OFC	Ofc. Peter Jacobs
ENGR	Engr. Daniel Kim
ADV	Adv. Neha Reddy
JDG	Jdg. Michelle Grant
JST	Jst. Alan Romero
ESQ	John Edwards, Esq.
ATTY	Atty. Gloria Martinez
CLLR	Cllr. Richard Dawson
PRIN	Prin. Lily Thompson
DEAN	Dean Marcus Hill
CHAIR	Chair Olivia Brooks
CEO	CEO Benjamin Lee
CFO	CFO Anika Shah
COO	COO Henry Morrison
VP	VP Sophia White

3. Date Conditions:

   • Same Year: Keeps the year consistent across all records.
   • Random: Randomizes the entire date.The random date will not be a future date.
   • Adult: Ensures the date reflects an adult age between 18 to 80 years.
   • Consistent: Keeps the date consistent across records. The consistent date will never be a future date.

4. Phone Conditions:

   • Random: Randomizes the entire phone number.
   • Remove Country Code: Removes the first 4 digits from the original phone number and generates a consistent anonymized value for the remaining number.

5. Org Name Conditions

   • The default condition (if user doesn’t select any value) for an Org Name will be always Company Name.
   • Bank Name: Replaces the Organization Name with an anonymized Bank Name. Also maintains consistency during the anonymisation process.
   • Company Name: Replaces the Organization Name with an anonymized Company Name. Also maintaining consistency during the anonymisation process will, however, retain any suffix of the company name at the end.
   • Remove Org Prefix: Anonymizes the Organization Name to a Company Name and removes the Suffix. The list of identified suffixes by the application is listed below. Users will not be allowed to select a Bank Name and a Remove Org Prefix combination.
   • All Caps: Anonymizes the Org Name to Company Name and capitalizes it.

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Identified Company Suffixes

Suffix	Meaning / Region	Example Organization Name
Pvt Ltd	Private Limited Company (India)	InnoTech Solutions Pvt Ltd
Ltd	Limited Company (UK, India, etc.)	BlueWave Technologies Ltd
LLP	Limited Liability Partnership	Nexus Consulting LLP
OPC	One Person Company (India)	SmartRetail OPC Pvt Ltd
Inc	Incorporated (USA, Canada)	Acme Systems Inc
Corp	Corporation (USA)	NextGen Data Corp
LLC	Limited Liability Company (USA)	Quantum Softworks LLC
Co	Company (General)	TrustCo Insurance Co
PLC	Public Limited Company (UK, India, etc.)	GlobalFin PLC
GmbH	Gesellschaft mit beschränkter Haftung (Germany, Austria)	AutoWerk GmbH
AG	Aktiengesellschaft (Germany, Switzerland)	Siemens AG
SA	Société Anonyme (France, Spain, Switzerland)	BNP Paribas SA
NV	Naamloze Vennootschap (Netherlands, Belgium)	Shell NV
Oy	Osakeyhtiö – Ltd (Finland)	Nokia Oy
AB	Aktiebolag – Ltd (Sweden)	Ericsson AB
KK	Kabushiki Kaisha (Japan)	Toyota KK
SARL	Société à Responsabilité Limitée (France, Luxembourg)	Ubisoft SARL
Pte Ltd	Private Limited (Singapore)	Grab Holdings Pte Ltd
Sdn Bhd	Sendirian Berhad (Malaysia – Private Ltd)	Petronas Sdn Bhd
JSC	Joint Stock Company (Russia, CIS countries)	Rosneft JSC
AS	Aksjeselskap – Ltd (Norway, Estonia)	Telenor AS
PT	Perseroan Terbatas – Ltd (Indonesia)	Tokopedia PT
Unlimited	Unlimited Company (Ireland, UK – rare)	Harris Unlimited
PLLC	Professional Limited Liability Company (USA)	LegalEase PLLC
LP	Limited Partnership	Summit Partners LP
PC	Professional Corporation (USA)	Miller & Co. PC
SE	Societas Europaea – Public Company (EU-wide)	Airbus SE
IG	Interest Group or Informal Group (less formal usage)	TechFounders IG

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6. Material Name Conditions

• The default condition (if user doesn’t select any value) for a Material Name will be always RANDOM_MAT condition.

• RANDOM_MAT: Replaces the Material Name with a MATERIAL_SEQUENCE_NO. Also, this condition will maintain consistency across the data. Example: “Inflammable Liquid” → MATERIAL_1

• FIXED_MAT: Replaces the Material Name with an anonymized material name. This condition also maintains consistency across the data. Example: “Inflammable Liquid” → RUBBER_1

• All Caps: Anonymizes the Material Name using the selected method and capitalizes it.

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Supported Date Formats

Hyphen (-) Formats

Format	Example
yyyy-MM-dd	2025-07-09
dd-MM-yyyy	09-07-2025
MM-dd-yyyy	07-09-2025
yy-MM-dd	25-07-09
dd-MM-yy	09-07-25
MM-dd-yy	07-09-25

Comma (,) Formats

Format	Example
yyyy,MM,dd	2025,07,09
dd,MM,yyyy	09,07,2025
MM,dd,yyyy	07,09,2025
yy,MM,dd	25,07,09
dd,MM,yy	09,07,25
MM,dd,yy	07,09,25

Dot (.) Formats

Format	Example
yyyy.MM.dd	2025.07.09
dd.MM.yyyy	09.07.2025
MM.dd.yyyy	07.09.2025
yy.MM.dd	25.07.09
dd.MM.yy	09.07.25
MM.dd.yy	07.09.25

Slash (/) Formats

Format	Example
yyyy/MM/dd	2025/07/09
dd/MM/yyyy	09/07/2025
MM/dd/yyyy	07/09/2025
yy/MM/dd	25/07/09
dd/MM/yy	09/07/25
MM/dd/yy	07/09/25

Space ( ) Formats

Format	Example
yyyy MM dd	2025 07 09
dd MM yyyy	09 07 2025
MM dd yyyy	07 09 2025
yy MM dd	25 07 09
dd MM yy	09 07 25
MM dd yy	07 09 25

No Separator Formats

Format	Example
yyyyMMdd	20250709
ddMMyyyy	09072025
MMddyyyy	07092025
yyMMdd	250709
ddMMyy	090725
MMddyy	070925

Special Case Formats

Format	Example
MMM dd, yyyy	Jul 09, 2025
MMM d, yyyy	Jul 9, 2025
MMM dd, yy	Jul 09, 25
MMM d, yy	Jul 9, 25

5. Custom Expressions:

   • Definition: While creating a utility parameter, you can define the Utility Parameter as Custom_Expression.

   • SQL Expression: Custom expressions are SQL update queries that are executed once all the anonymizations are done.

   • Steps for Custom Expression:

     1. Select the Utility Parameter as Custom_Expression and enter the expression in the parameter text box.
     2. Ensure that the expression follows correct SQL syntax.

   • Guidelines for SQL Expression:

     1. Enclose table column names in hash characters (#).
     2. Enclose strings in single quotes ('').

   • Example of Custom Expressions:

     • Example SQL expression:
       UPDATE #table# SET #column# = 'new_value' WHERE #column# = 'old_value'

   • Restrictions:

     • The application doesn't allow you to customize a column with Custom_Expression using another column that also has a utility parameter selected as Custom_Expression.

Utility Parameter Table

Column	Utility Parameter	Utility Parameter Condition	Description
Email	CUSTOM_EXPRESSION	normal-string	The email column will be anonymized with the anonymized value of the name column concatenated (symbol `

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Privacy Parameter Classification

The Privacy Parameter is used to protect sensitive customer information, determining the logging behavior during job runs. It is classified into three categories: Personal, Confidential, and Non-Relevant.

Privacy Types and Logging Policies:

Privacy Type	Example Data	Logging Policy
Personal	Name, Email, Phone Number	The original fields are not logged in the audit logs.
Confidential	Address, Account Number, Financial Details	The original fields are not logged in the audit logs.
Not Relevant	Non-sensitive data without privacy implications	Log original values in the audit logs.

Privacy Classification:

• Personal: Data that can directly identify an individual, such as name, address, phone number, or email.
• Confidential: Data that is not directly identifying but is sensitive and private, such as account numbers, financial details, or proprietary business information.
• Not Relevant: Data that does not have privacy implications and does not directly or indirectly identify individuals or contain sensitive business information.

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Final Steps:

1. After entering the Utility Parameter, Utility Parameter Condition, and Privacy Parameter, click Save to finalize the settings.