Safe Test Data Generation
Realistic Data in Real Formats
Build Smart Test Data & Manage It Smarter
Do you need an easier way to:
- create test DBs with referential integrity
- simulate and share file and report layouts
- develop and stress-test applications
- benchmark new hardware and software
- conduct data warehouse ETL testing
using your data models and metadata, but not production data?
Table views, index orders, key relationships, and file and report contents, must reflect reality to be useful in testing. Generating realistic values and formats with safe data in ideal ranges -- and populating large targets -- can take a long time with other tools or programs.
With the IRI RowGen product or IRI Voracity platform, you can generate multiple test data targets for test database loads, flat-file structures, and custom report formats from scratch -- all without access to real data. Or if you want to use and anonymize, subset, or otherwise mask real data for production or on-demand or virtualized testing scenarios, you can do that in IRI Voracity or with the IRI FieldSield product, too!
We offer four methods for producing safe, intelligent test data in database, flat-file, semi-structured file, and formatted report targets:
Synthetic test data creation (via random generation / selection)
Data Masking Capabilities
Use any of the static data masking software products available in the IRI Data Protector Suite, or included free in the IRI Voracity platform:
- IRI FieldShield for structured files and databases
- IRI DarkShield for unstructured text, document, and image files
- IRI CellShield for Excel spreadsheets
Data Synthesis Capabilities
RowGen can create structurally and referentially correct test data for every popular RDBMS with defined constraints, plus test data in custom report layouts or popular file/feed formats like these:
- Record, line, or variable sequential
- COBOL index (MF ISAM, Vision)
- CSV, LDIF, JSON, and XML
- Fixed position text and mainframe blocked
- MQTT and Kafka topics
- BIRT (via ODA) and KNIME (analytic & visualization nodes) in Eclipse
RowGen can also randomly select data from set files at the field level. That, along with custom/compound data values, value ranges, and distributions, improve test data realism.
Support for standard and complex data transformations, set files, and conditional selection also contribute to RowGen's value in simulating production table and file formats for a variety of applications.
For database users, RowGen leverages the DDL information for Oracle, DB2 UDB, SQL Server, Sybase, Teradata, and other platforms to create realistic tables with structural and referential integrity. Use RowGen to populate an entire test enterprise data warehouse (EDW) or DataVault.
If you use IRI Voracity, you can use its included RowGen synthesis and FieldShield data masking capabilities to find, classify, subset, and mask data, and integrate that data for static development use in lower environments or virtual use in live testing environments.
Consider our test data management advice as you scope out your requirements and plan your strategy, and see these links for more information on using safe test data for: