IRI RowGen (Test Data)
Easily create DB, Data Vault, and ETL test data. Outsource development, stress-test apps, and benchmark ... all without production data.
Test Data for Everyone
Automatically build and populate massive DB, file, and report targets with structurally and referentially correct test data -- in minutes, not hours.
Cover Every Scenario
Make better programs and more confident decisions with high quality, high volume test data. Stress-test and future-proof your solutions.
Safe Data that Looks Real
Stop using or masking production data. Use your metadata and business rules to make test data that's safer and better than real data.
IRI RowGen Use Cases
High Volume, Referentially Correct
"RowGen generates 20GB tables with referential integrity for query testing. It eliminates production data access concerns and generates the volumes that reflect our growth."
Simultaneous Functional Testing
"RowGen is the only tool that supplies high volumes of test data on multiple operating systems and simultaneously manipulates the test data for application compatibility."
Better than Production Data
"RowGen creates realistic PII and PAN data to support our OLTP app development and testing. It's the only tool that generates test files in the formats and sizes we need."
Versatile Test Data Generation
Use IRI RowGen to:
- Load Accurate, Safe Test DBs
- Prototype DW ETL Ops
- Outsource Development
- Stress-Test Applications
- Benchmark New Platforms
- Comply with Privacy Laws
Build Test Data Directly into:
- RDBMS tables and Excel
- Rec/Line/Var. Sequential Files
- CSV, LDIF, Text, and XML
- MFVL, ISAM and Vision Files
- Mainframe and V/B Files
- Detail and Summary Reports
When to Consider IRI RowGen
- forgoing adequate testing and making inaccurate suppositions and extrapolations
- coding custom 3GL or shell programs for test sets valid in only one scenario
- using confidential production data at the risk of breaches, NDA violations, etc.
- scouring a low-end market of test data tools that lack speed or functional breadth
- relying on costly, hard-to-modify platform tools that subset and mask production data
When production data:
- contains personally identifiable information
- is restricted
- does not yet exist
- does not reflect future scope
What Others Are Reading
As anyone from healthcare.gov can tell you, complex application development requires adequate needs assessments and sufficiently robust test data.
Can you supply your prototypes with good and bad anonymous data quickly? Will it conform to production ranges, distributions, and appearances?
Testing DB queries and DW ETL/ELT jobs requires test data with structural and referential integrity, and support for special constraints, nulls, etc.