Data Masking/Protection
The identity fabrication rule is a deterministic but non-reversible data masking rule that can help you create realistic test PII for a whole record from just one original value. Read More
Data Masking/Protection
Healthcare providers, medical researchers, and other “business associates” collect and process sensitive data on patients, which HIPAA law classifies as protected health information (PHI). Because PHI is stored and shared in databases, clinical notes, imaging studies, treatment forms, and EDI (claim) formats – both on-premise and in the cloud – safeguarding it by finding and de-identifying it can be a complex, time-consuming challenge. Read More
Data Masking/Protection
The purpose of IRI data masking tools is to discover and obfuscate Personally Identifiable Information (PII) in various data sources. Depending on the type of data source, we recommend different products in the IRI Data Protector Suite, typically IRI FieldShield or IRI DarkShield. Read More
Data Masking/Protection
The IRI DarkShield data masking tool includes fit-for-purpose wizards in its IRI Workbench GUI to search (classify) and mask (remediate) sensitive ”dark data” (as defined by Gartner) in many semi, unstructured, and structured file, NoSQL, and relational database (RDB) sources. Read More
Data Masking/Protection
Abstract: This article describes how IRI DarkShield users can access files in SharePoint Online for searching and masking PII. It documents the setup steps you will take to use Microsoft Entra ID (formerly Azure Active Directory) for authorization, and configure DarkShield jobs in the IRI Workbench graphical IDE, built on Eclipse. Read More
Data Transformation
This article demonstrates the Voracity user’s ability to join values in a flat-file file to those in an RDB (Relational Database) table to provide meaningful information. Read More
Data Masking/Protection
The IRI DarkShield data masking tool includes fit-for-purpose wizards in its IRI Workbench GUI to search (classify) and mask (remediate) sensitive ”dark data” (as defined by Gartner) in many semi, unstructured, and structured file, NoSQL, and relational database (RDB) sources. Read More
Big Data
Corporations and government agencies store a lot of useful information in non-transactional semi-structured and unstructured data sources. Finding that data – in documents, logs, and images – is important not only for data masking, but also for textual ETL. Read More
Data Masking/Protection
The IRI DarkShield data masking product now includes fit-for-purpose wizards in the IRI Workbench IDE to search (classify) and mask (remediate) sensitive ”dark data” (as defined by Gartner) in many semi, unstructured, and structured file, NoSQL, and relational database (RDB) sources. Read More
Big Data
As you may already know, IRI DarkShield produces search annotations and masking results with every operation. These log files can contain a large volume of data, including:
metadata about the file/database source(s) what data was found as a match which matcher matched the data how the data was masked (if it was) where matches occurred within each file or database. Read More