Safe Test Data


Next Steps
Overview Data Masking Data Quality Test Data Forensics RBAC Stewardship COBIT EMM MDM DGaaS


Part of the governance role in protecting data at risk is assessing and avoiding the use of unsafe production data for testing. Realistic, but not real, test data is a necessity for:

  • application stress- and range-testing
  • outsourced program development
  • simulating databases and their applications
  • hardware and software benchmarking
  • sharing custom file and report formats

Very often, however, those who need test data simply replicate the production database, or use snippets of real production files. Both are inherently risky because they can expose sensitive, private data. They may not even be possible if the production data is unavailable or does not yet exist.

Meanwhile, generating useful test data that is safe can be difficult for many reasons, including:

  • it may be hard to mask real data for test uses
  • integrity constraints cannot easily be preserved
  • available fake data is in the wrong layout
  • the data needs to be filtered and transformed
  • complex test data generators are hard to write
  • most commercial tools are slow or hard to use


You can now recommend and use a tool that easily generates safe, referentially correct test data in production database and file formats without needing production data. Specifically, the IRI data generation package, RowGen, synthesizes realistic test data in the same table, report and production file formats you need to load, or send outside the firewall.

Any number, size, type, and position of fields, records, or files can be specified in a single job script and I/O pass. Various selection and ranging criteria -- as well as data transformations -- can be applied to prototype and stress applications.

With IRI RowGen -- or the IRI Voracity data management platform that includes RowGen, FieldShield, et al -- you can synthesize artificial, but realistic PIIin database and file targets, assuring DevOps and risk management officials that the test data is both valuable and safe. RowGen's logging and audit functions are also available to help you verify compliance with data privacy rules.

Common Metadata

The SortCL program in the IRI CoSort package or IRI Voracity platform defines and manipulates production data with the same metadata that RowGen uses for specifying test data.

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