
Data Class & Rule Library in IRI Workbench
Abstract: HIPAA, GDPR, FERPA, and other data privacy laws require that personally identifiable information (PII) and related data considered sensitive be protected from disclosure or discovery. Read More
Abstract: HIPAA, GDPR, FERPA, and other data privacy laws require that personally identifiable information (PII) and related data considered sensitive be protected from disclosure or discovery. Read More
As I’m finding myself noting more and more frequently this year, AI, and especially generative AI or “GAI”, is the new darling of the tech world, to the point that it has even captured the attention and interest of the general public (albeit not always positively). Read More
MariaDB and MySQL are relational databases that follow the same paradigm when it comes to setting up connections with SortCL-driven Voracity component jobs designed in IRI Workbench. Read More
Editor’s Note: This article updates IRI’s original series on managing metadata assets in Git, and covers project export and import, particularly for use in enterprise data anonymization and test data management scenarios. Read More
Abstract: This article demonstrates the use of the Chrome Remote Desktop (RDP) extension from Google to run IRI Workbench and its SortCL-powered mapping, masking, and munging jobs remotely from a browser. Read More
Over the course of this blog series, we’ve described several data management capabilities, as well as why those capabilities are important and worth caring about. We’ve covered testing, both in terms of test design automation and test data management, data governance and data masking, data migration and modernization, and data quality and improvement. Read More
We started this series of articles by talking about test design automation and the need to introduce automation throughout your testing processes. In this blog, we come full circle to talk, once again, about testing. Read More
When it comes to protecting your data, there are two processes that could be considered absolutely fundamental: finding out which of your data is sensitive and where it can be located, and then actually protecting that data. Read More
In the previous article in this series, we discussed the importance of improving and maintaining the quality of your data. Along the same lines, it is also very important to make sure your data is well-governed. Read More
In conjunction with a newly created wizard used to generate Pseudonym Hash Replacement Rules, based on the same concept discussed in a previous article, a Pseudonym Hash Set File Creation Wizard is now also available in IRI Workbench. Read More
Pseudonymization is a data masking method involving the replacement of one or more original source values in a column in a table, file, or in free-floating text with another, usually consistent “synthetic” value. Read More