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Challenges

 

Sometimes sensitive data is not allowed in production or replicated data stores. Other times, that information may not be needed in a future process step. In either case, removing or covering over the data from source tables and files is the only sure way to keep it from appearing in your output(s).

Removing or masking columns or specific values from database tables usually requires a DBA to manage the process. Removing fields from, or applying omission criteria to, flat files is not a trivial task either. This is especially true with multiple, very large data sources, and complex redaction rules.

Data redaction tools for structured data sources are typically expensive, and unlikely to combine this functionality with field-level protections like encryption, de-identification, pseudonymization at the same time.

Solutions

 

If you manage personally identifiable data in database tables or flat files, you can select which source columns and values will remain or display in your target(s). Populate tables, reports, and hand-off files with data provided on a need-to-know basis.

With either IRI FieldShield or the SortCL program in IRI CoSort, you can selectively omit or mask parts of rows or columns from inputs or outputs based on conditional evaluation logic. That is, either filter out or cover over the field values or component parts (sub-strings or particular bytes) based on your business rules.

If the sensitive data reside in unstructured text files, IRI software can help you find, structure, and place that information in protected, structured targets.

Additional FieldShield functions like encryption, de-identification, and obfuscation are also possible on other fields at the same time. CoSort SortCL users can also redact and mask data during data transformation, migration, and reporting operations.

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