Data Masking Process

The process to mask operational data comprises two steps:

• Transforming identifiable data based on the data masking configuration.

• Purge the data from the entities.

Run the Database Package

Prerequisites

Create a backup of the source environment.

Run the Database Package

To run the package, perform the following steps:

1. Create a PDB clone of the source environment.

2. Confirm whether the package runs on the newly-cloned environment and not on the source environment.

3. Run the package on the cloned PDB using the following command. You need ohi_<app>_owner privileges to run the package.

   exec ohi_data_masking_pkg.mask_data_parallel(<parameter 1>, <parameter 2>, '<parameter 3>', <parameter 4>, '<parameter 5>');

   Where:

   • The parameter 1 and 2 contain seed values for NUMHASHADD and NUMHASHCON transformation functions.

   • The parameter 3 contains a seed value for the TXTHASH function.

   • The parameter 4 is optional and contains the commit frequency with a default value of 5000.

   • The parameter 5 is optional and contains a Yes (Y) or No (N) values to enable the logging process. The application has the logging process as disabled by default.

   Following are the sample commands to run the masking package:

   exec ohi_data_masking_pkg.mask_data_parallel(999 ,987, 'sometext');

   exec ohi_data_masking_pkg.mask_data_parallel(999 ,987, 'sometext', 10000, N);

4. Create an export of the masked schema.

5. Deploy the application by following the instructions in the Installation Guide to install the application on the server with the masked schema.

Data Transformation Process

Step 1: Mask Data

1. The process starts to transform data based on the configuration from the Data Masking Configuration Integration Point.

2. The process resets the audit columns for the transformed or updated rows, like Created By, Creation Data, Last Updated By and Last Updated Date columns of a table.

Step 2: Purge Data

The application purges the data from the entities listed below.

Entities

List of entities that purge completely for this process:

Table 1. Tables

Used For	Entity Name
Notes	Note
Extracts	Extract
Financial Details	FinancialTransactionDetail RegistrationInvoice FinancialTransactionProcessData FinancialTransactionSet FinancialTransaction FinancialGroupingCombination FinancialTransactionSetActivity FinancialHold BaseFinancialObjectActivity FinancialBulkingGroupActivity Registration RegistrationActivity FinancialSubjectRegistration FinancialTransactionDetailProcessData BaseFinancialObject AccountingDetail GenerateAccountingDetailMessage CreateAccountingDetailRegistration In addition to the above entities Financial technical tables are also part of the purge process
Callouts	CalloutExecution CalloutRuleExecution
Logs	LogApplicationEvent LogDynamicLogicEvent LogPHIEvent
Other Tables	InterfacedMessageDetail Bookmark MacroHistory ImportData SourceReplicationEvent TargetReplicationEvent OAuthAssertionJWTBearerGrantConfiguration OAuthClientConfigurationParameter OAuthGrantConfiguration OAuthParameter LargeClaimChangeLog

Properties

List of the properties set to null as part of this process:

Table 2. Columns

Entity Name	Properties
Activity	correlationId descr extraInfo internalRemarks subjectId
ActivityMessage	value0..value9
ClaimMessage	value0..value9 referenceCode
ClaimLineMessage	value0..value9 referenceCode
CtrClaimMessage	value0..value9 messageText alternativeMessageText providerMessageText
CtrClaimLineMessage	value0..value9 messageText alternativeMessageText providerMessageText
BillMessage	value0..value9
CtrBillMessage	value0..value9
RegimeConsumption	descr
AuthorizationMessage	value0..value9
EligibilityCheckMessage	value0..value9
EligibilityCheck	eligibilityResponse
AdjudicationCaseDetail	descr
Task	extraInfo context correlationId subjectCode
TaskAttribute	valueChar valueClob valueNr
InterfacedMessage	correlationId requestMessage responseMessage
DataFile	File data
Address	houseNumber