Compare IRI Data Protector Suite vs. Informatica Test Data Management in 2026

IRI Data Protector Suite

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Description

Renowned startpoint security software products in the IRI Data Protector suite and IRI Voracity data management platform will: classify, find, and mask personally identifiable information (PII) and other "data at risk" in almost every enterprise data source and sillo today, on-premise or in the cloud. Each IRI data masking tool in the suite -- FieldShield, DarkShield or CellShield EE -- can help you comply (and prove compliance) with the CCPA, CIPSEA, FERPA, HIPAA/HITECH, PCI DSS, and SOC2 in the US, and international data privacy laws like the GDPR, KVKK, LGPD, LOPD, PDPA, PIPEDA and POPI. Co-located and compatible IRI tooling in Voracity, including IRI RowGen, can also synthesize test data from scratch, and produce referentially correct (and optionally masked) database subsets. IRI and its authorized partners around the world can help you implement fit-for-purpose compliance and breach mitigation solutions using these technologies if you need help.

Description

We assist you in uncovering, generating, and customizing test data while also enabling you to visualize coverage and ensure data security, allowing you to concentrate on development tasks. Automate the generation of masked, tailored, and synthetic data to fulfill your development and testing requirements seamlessly. Quickly pinpoint sensitive data locations by implementing uniform masking across various databases. Enhance testers’ productivity by storing, expanding, sharing, and reusing test datasets effectively. Deliver smaller datasets to lessen infrastructure demands and enhance overall performance. Employ our extensive range of masking methods to ensure consistent data protection across all applications. Provide support for packaged applications to maintain solution integrity and accelerate deployment processes. Collaborate with risk, compliance, and audit teams to synchronize with data governance strategies. Boost test efficiency by utilizing dependable, trusted production data sets while simultaneously reducing server and storage demands with appropriately sized datasets for each team. This holistic approach not only streamlines the testing process but also fortifies the data management practices of your organization.