Compare IRI FieldShield vs. Informatica Dynamic Data Masking in 2026

IRI FieldShield

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Description

IRI FieldShield® is a powerful and affordable data discovery and de-identification package for masking PII, PHI, PAN and other sensitive data in structured and semi-structured sources. Front-ended in a free Eclipse-based design environment, FieldShield jobs classify, profile, scan, and de-identify data at rest (static masking). Use the FieldShield SDK or proxy-based application to secure data in motion (dynamic data masking). The usual method for masking RDB and other flat files (CSV, Excel, LDIF, COBOL, etc.) is to classify it centrally, search for it globally, and automatically mask it in a consistent way using encryption, pseudonymization, redaction or other functions to preserve realism and referential integrity in production or test environments. Use FieldShield to make test data, nullify breaches, or comply with GDPR. HIPAA. PCI, PDPA, PCI-DSS and other laws. Audit through machine- and human-readable search reports, job logs and re-ID risks scores. Optionally mask data when you map it; FieldShield functions can also run in IRI Voracity ETL and federation, migration, replication, subsetting, and analytic jobs. To mask DB clones run FieldShield in Windocks, Actifio or Commvault. Call it from CI/CD pipelines and apps.

Description

Your IT department can implement advanced data masking techniques to restrict access to sensitive information, utilizing adaptable masking rules that correspond to the authentication levels of users. By incorporating mechanisms for blocking, auditing, and notifying users, IT staff, and external teams who interact with confidential data, the organization can maintain adherence to its security protocols as well as comply with relevant industry and legal privacy standards. Additionally, you can tailor data-masking strategies to meet varying regulatory or business needs, fostering a secure environment for personal and sensitive information. This approach not only safeguards data but also facilitates offshoring, outsourcing, and cloud-based projects. Furthermore, large datasets can be secured by applying dynamic masking to sensitive information within Hadoop environments, enhancing overall data protection. Such measures bolster the integrity of the organization's data security framework.