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🛠️ Method 1: Manual Creation of a New Utility Set

Steps to Create a New Utility Set Manually​

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  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.
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  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).
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  4. Add Conditions (Optional):

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

Condition Details Table​

Input FieldDescriptionValuesScreenshot
Condition NameInput field to define the name of the condition
TablesRefers to the tables this condition will apply toAll in Utility Set / Particular Table
FieldsColumn of the table
FunctionIs, Is Not (Blank Equal, Greater Than, Less Than, Start With, On the List (manual entry), Linked [table].[field])alt text
ValuesDefines the value of the Field in the databaseInput field to specify the conditions

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

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. alt text

Utility Parameters and Conditions​

Utility ParametersUtility ConditionsDescription
No ChangeN/ALeaves the data unchanged.
Clear ValuesN/AClears the data in the selected fields.
EmailDummy Domain, Keep Domain, All CapsAnonymizes email addresses with additional formatting options.
NameFirst Name, Last Name, All Caps, Full Name, NameHandles name fields with specific conditions for first name, last name, etc.
Consistent IDN/AGenerates a consistent identifier for tracking records.
Fixed ValueInput FieldReplaces the field with a fixed value.
DateSame Year, Random, Adult, ConsistentAnonymizes date fields while retaining some options for consistency.
Phone NumberRandom, Remove Country Code, CONSISTENTHandles phone numbers by formatting them or generating new numbers.
NumberN/ARandomizes or anonymizes numerical data.
Custom ExpressionsN/AAllows custom regular expressions or formats to be applied to the data fields.
Org NameCompany Name, Bank Name, Remove Org Suffix , All CapsAnonymizes Organization Name to either Company Name or Bank Name based on the utility condition selected. Maintains consistency during the anonymisation.
Material NameFixed Mat, Random Mat, All CapsAnonymizes the Material Name different formats based on the selected condition.
IBANN/AAnonymizes the IBAN to an IBAN of the same country while retaining the length and the pattern.
Account NumberN/AAnonymizes the Account Number using format preserving encryption. Retaining the length and numeric pattern.
AddressHouse Number, Street, City, Post CodeAnonymizes the address to either a House Number, Street, City or Post Code based on the condition selected.
IP AddressConsistentAnonymizes the IP Address to a consistent IPv4 format
URLDomain/Sub Domain/URLAnonymizes the selected URL to a consistent format based on the condition selected.
PassportN/AAnonymizes the Passport Number to an anonymized Passport number retaining the original length, character types and delimiters. It will retain the first “N”chars of the passport where “N” will be customizable number.
SSN IDN/AAnonymizes the National Identification Numbers to an anonymized number retaining the original format length, character types and delimiters. It will retain the first “N”chars of the original ID where “N” will be customizable number.
Tax IDN/AAnonymizes the Tax ID to an anonymized Tax ID retaining the original length, character types and delimiters. It will retain the first “N”chars of the Tax ID, where “N” will be customizable number.

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

SalutationExample Name
MRMr. John Smith
MRSMrs. Elizabeth Johnson
MSMs. Angela Baker
MISSMiss Emily Clark
MXMx. Taylor Morgan
DRDr. Alan Grant
PROFProf. Susan Walker
SIRSir James Windsor
MADAMMadam Catherine Blake
DAMEDame Margaret Cole
LORDLord Henry Cavill
LADYLady Charlotte Grey
REVRev. Thomas Hill
FRFr. Michael O'Brien
RABBIRabbi David Cohen
IMAMImam Ahmed Hassan
SHEIKHSheikh Omar Al-Fulan
PRESPres. Laura Bennett
PMPM Richard Matthews
CHCh. Rachel Mendes
GOVGov. William Parker
MAYORMayor Linda Torres
HONHon. Deborah Patel
SENSen. Robert Greene
REPRep. Maria Lopez
AMBAmb. Jonathan Li
SECSec. Amanda Brooks
ABPAbp. Francis Doyle
CARDCard. Leonardo Rossi
BPBp. Gregory Hughes
POPEPope Benedict XVI
CAPTCapt. Sarah Nolan
MAJMaj. Eric Daniels
COLCol. Jacob Steele
GENGen. Laura Whitman
CMDRCmdr. Anthony Reid
LTLt. Chloe Zhang
SGTSgt. Brian O'Connor
CPLCpl. Kevin Blake
CHIEFChief Monica Reyes
OFCOfc. Peter Jacobs
ENGREngr. Daniel Kim
ADVAdv. Neha Reddy
JDGJdg. Michelle Grant
JSTJst. Alan Romero
ESQJohn Edwards, Esq.
ATTYAtty. Gloria Martinez
CLLRCllr. Richard Dawson
PRINPrin. Lily Thompson
DEANDean Marcus Hill
CHAIRChair Olivia Brooks
CEOCEO Benjamin Lee
CFOCFO Anika Shah
COOCOO Henry Morrison
VPVP Sophia White

  1. 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.

  2. 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.

  3. 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.

Identified Company Suffixes​

SuffixMeaning / RegionExample Organization Name
Pvt LtdPrivate Limited Company (India)InnoTech Solutions Pvt Ltd
LtdLimited Company (UK, India, etc.)BlueWave Technologies Ltd
LLPLimited Liability PartnershipNexus Consulting LLP
OPCOne Person Company (India)SmartRetail OPC Pvt Ltd
IncIncorporated (USA, Canada)Acme Systems Inc
CorpCorporation (USA)NextGen Data Corp
LLCLimited Liability Company (USA)Quantum Softworks LLC
CoCompany (General)TrustCo Insurance Co
PLCPublic Limited Company (UK, India, etc.)GlobalFin PLC
GmbHGesellschaft mit beschränkter Haftung (Germany, Austria)AutoWerk GmbH
AGAktiengesellschaft (Germany, Switzerland)Siemens AG
SASociété Anonyme (France, Spain, Switzerland)BNP Paribas SA
NVNaamloze Vennootschap (Netherlands, Belgium)Shell NV
OyOsakeyhtiö – Ltd (Finland)Nokia Oy
ABAktiebolag – Ltd (Sweden)Ericsson AB
KKKabushiki Kaisha (Japan)Toyota KK
SARLSociété à Responsabilité Limitée (France, Luxembourg)Ubisoft SARL
Pte LtdPrivate Limited (Singapore)Grab Holdings Pte Ltd
Sdn BhdSendirian Berhad (Malaysia – Private Ltd)Petronas Sdn Bhd
JSCJoint Stock Company (Russia, CIS countries)Rosneft JSC
ASAksjeselskap – Ltd (Norway, Estonia)Telenor AS
PTPerseroan Terbatas – Ltd (Indonesia)Tokopedia PT
UnlimitedUnlimited Company (Ireland, UK – rare)Harris Unlimited
PLLCProfessional Limited Liability Company (USA)LegalEase PLLC
LPLimited PartnershipSummit Partners LP
PCProfessional Corporation (USA)Miller & Co. PC
SESocietas Europaea – Public Company (EU-wide)Airbus SE
IGInterest Group or Informal Group (less formal usage)TechFounders IG

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.

7. Address Conditions​

  • House_Number:
    The address will be anonymized to a random house number.

  • Street:
    The address will be anonymized to a random postcode.

  • City:
    The address will be anonymized to a random city.

  • Post Code:
    The address will be anonymized to a random postcode. The anonymized postcode will retain the length and the format of the original postcode.
    Examples:

    • 12345 → anonymized to a 5-digit numeric postcode
    • 12345-6789 → anonymized to a ZIP + 4-digit format
    • A12 B345 → anonymized to a 7-character alphanumeric format

8. URL Conditions​

  • Subdomain:
    Only the subdomain part of the URL will be anonymized and replaced. The type will NOT be retained while doing the replacement.
    Example: a numeric value can be replaced with an alphabet and vice versa.

  • Domain:
    Only the domain part of the URL will be anonymized. The type will NOT be retained while doing the replacement.
    Example: a numeric value can be replaced with an alphabet and vice versa.

  • URL:
    Both the domain and subdomain parts of the URL will be anonymized and replaced.

Supported Date Formats

Hyphen (-) Formats​

FormatExample
yyyy-MM-dd2025-07-09
dd-MM-yyyy09-07-2025
MM-dd-yyyy07-09-2025
yy-MM-dd25-07-09
dd-MM-yy09-07-25
MM-dd-yy07-09-25

Comma (,) Formats​

FormatExample
yyyy,MM,dd2025,07,09
dd,MM,yyyy09,07,2025
MM,dd,yyyy07,09,2025
yy,MM,dd25,07,09
dd,MM,yy09,07,25
MM,dd,yy07,09,25

Dot (.) Formats​

FormatExample
yyyy.MM.dd2025.07.09
dd.MM.yyyy09.07.2025
MM.dd.yyyy07.09.2025
yy.MM.dd25.07.09
dd.MM.yy09.07.25
MM.dd.yy07.09.25

Slash (/) Formats​

FormatExample
yyyy/MM/dd2025/07/09
dd/MM/yyyy09/07/2025
MM/dd/yyyy07/09/2025
yy/MM/dd25/07/09
dd/MM/yy09/07/25
MM/dd/yy07/09/25

Space ( ) Formats​

FormatExample
yyyy MM dd2025 07 09
dd MM yyyy09 07 2025
MM dd yyyy07 09 2025
yy MM dd25 07 09
dd MM yy09 07 25
MM dd yy07 09 25

No Separator Formats​

FormatExample
yyyyMMdd20250709
ddMMyyyy09072025
MMddyyyy07092025
yyMMdd250709
ddMMyy090725
MMddyy070925

Special Case Formats​

FormatExample
MMM dd, yyyyJul 09, 2025
MMM d, yyyyJul 9, 2025
MMM dd, yyJul 09, 25
MMM d, yyJul 9, 25
  1. 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.

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Utility Parameter Table​

ColumnUtility ParameterUtility Parameter ConditionDescription
EmailCUSTOM_EXPRESSIONnormal-stringThe email column will be anonymized with the anonymized value of the name column concatenated (symbol `

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 TypeExample DataLogging Policy
PersonalName, Email, Phone NumberThe original fields are not logged in the audit logs.
ConfidentialAddress, Account Number, Financial DetailsThe original fields are not logged in the audit logs.
Not RelevantNon-sensitive data without privacy implicationsLog 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.

Final Steps:​

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