Data Masking/Protection
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
IRI Workbench
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
Data Masking/Protection
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
Big Data
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
Data Transformation
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
Data Masking/Protection
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
Data Masking/Protection
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
Data Masking/Protection
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
Data Masking/Protection
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
Data Quality (DQ)
It always bears repeating that being able to serve up high-quality data is really important. This is partly because the consequences of poor data quality can be severe – misleading analytics, stymied processes, greater storage costs (due to duplicated data), and so on – but also because historically many organizations have not treated data quality as the priority it should be. Read More
Data Migration
With the rise of the cloud, data migrations – and specifically, cloud migrations – have become (and, for that matter, are still becoming) increasingly important to many organizations. Read More