Test Data
Realistic test data has a number of advantages over real data for anyone creating or changing a database, prototyping ETL operations, or testing applications. First, synthetic data do not expose personally identifiable information (PII) like credit card, social security numbers, birth dates, etc. Read More
IRI Workbench
A test data generator is an important part of the setup process for DevOps and data architects prototyping database and data warehouse operations, testing applications, benchmarking different platforms, and outsourcing work formats. Read More
Data Masking/Protection
According to Trent Henry of the Burton Group,
Data protection needs to take into account both internal and external threats, including those against critical database and application resources. Read More
Data Migration
Data validation is a process that ensures a program operates with clean, correct and useful data. It uses routines known as validation rules that systematically check for correctness and meaningfulness of data that are entered into the system. Read More
Data Masking/Protection
Editors Note: This article refers only to full or partial column/field redaction of strings in structured database or flat files, and thus one of many static (and API-driven dynamic) data masking functions available in IRI FieldShield. Read More
Data Masking/Protection
Editor’s Note: Note that this article refers to older but still supported methods for obfuscating PII elements like dates of birth and ages in IRI FieldShield. Read More
Data Masking/Protection
Data masking is one method to combat the nearly 72,000 documented breaches of personally identifiable information (PII) that occur every day. With data privacy breaches still at unacceptably high levels, how can companies protect PII such as their national ID numbers across their myriad sources of data? Read More
Data Masking/Protection
IRI FieldShield is a proven, best-in-class data-centric security package for classifying, finding, and masking personally identifying information (PII) and other sensitive data in database columns and flat-file fields. Read More