Innovative Routines International (IRI), Inc., a leading developer of big data transformation and data-centric protection software, announced major new versions of its products for securing personally-identifying information in databases and files, and rapidly generating safe, intelligent test data for entire databases, files and reports.  The respective FieldShield and RowGen v3 upgrades include major functional enhancements, and full support in the IRI Workbench graphical IDE, Built on Eclipse.

FieldShield v3 can automatically apply security measures to database columns containing common personally identifiable information (PII) in multiple tables. According to IRI technical director Rob Howard, FieldShield’s new data protection rule engine and function library “allow users to specify, save, and re-use protections that apply only to column names matched through regular expressions. Protecting multiple columns at once saves job design time and preserves referential integrity during data protection.”

The new FieldShield release delivers protections in 10 functional categories, and includes these new methods:
• FIPS-compliant OpenSSL and 3DES encryption
• AES-128 (in addition to AES-256 with or without format preservation)
• Random selection or data generation
• 256-bit hashing
• Custom data masks
• Record reformatting

RowGen v3 automates the creation of structurally and referentially correct database test data in a new job wizard in the IRI Workbench GUI. The wizard consolidates the tasks of:
• Parsing – table descriptions and integrity constraints are translated to test data generation definitions that reflect the source structures, column data types, and dependent sets
• Generation – pre-sorted flat files containing the test data are created for loads, and the definitions remain for modification and re-use
• Population – target tables are rapidly bulk loaded in the order necessary to maintain the same table relationships that exist in production

RowGen v3 also features new test data customization and value range distribution features which, according to Howard, “provide complete realism for every column without personally identifying anyone.” For more information, visit and