Data masking, a key feature in icaria TDM, serves as a cross-functional capability for identifying and protecting sensitive data within its data management processes. It must be so, as the platform's main strategy is to find and deliver data created within the application environments themselves, with the primary source of test data being the production environment.
icaria TDM has a comprehensive process for dissociating sensitive data, in both operating modes it offers: anonymization and pseudonymization. However, it is not enough to just dissociate the sensitive data. It is necessary to audit the dissociation processes and provide information to the user.
Data masking session
In icaria TDM, the concept of a process session is relevant. The session collects information about the execution for two purposes:
Operational efficiency. TDM processes are complex due to reasons of volume and/or information structure. The data architect needs execution information to fine-tune the processes.
Audit and control. TDM processes that operate with real data, responsible for the protection of sensitive information, must provide sufficient information to know which data are processed, in which environments they are delivered, or which users request them.
Information from the sensitive data masking session.
The sensitive data dissociation session collects information on:
Data processing procedures executed in the session.
The status of application of dissociation algorithms for sensitive information by data type, and by table and field.
Traceability domains for those attributes that must maintain consistency.
The original and final status of database resources that dissociation needs to manage, such as activating primary and foreign keys when dissociating affected attributes.
Messages, warnings, and errors from the process.
Process statistics, such as processing times or records.
Data delivery audit
icaria TDM delivers data suitable for testing in any application environment. The delivery history allows for an understanding of the statistics of movements for each instance. Information is provided on:
The affected data metamodel.
The date and time of each movement.
The source and destination environments.
The type of TDM process that executed the movement.
