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 Transformation
This is the first in a series of blog posts that will highlight the various data management capabilities provided by IRI Voracity across a range of contexts and use cases. Read More
Data Masking/Protection
Introduction: In the context of IRI software, set files are text files containing realistic or replacement values for data management applications in the IRI Voracity platform ecosystem. Read More
ETL
Data flowing through application development, machine learning, and analytic pipelines must address several needs common to all three, including:
Realism, to reflect production data characteristics and application test requirements; Compliance, with business and data privacy rules, plus DB and analytic models; Availability, or security, of the data (depending on your perspective); and, Auditability, for lineage and accountability. Read More
Data Masking/Protection
IRI DarkShield has always had the ability to search through and mask Personally Identifiable Information (PII) and other sensitive data in unstructured sources like PDF documents and image files. Read More
Data Masking/Protection
This is the third addition to our 4-article DevOps pipeline series. Here are the links to related DevOps articles for Jenkins, GitLab and AWS CodePipeline. Read More
IRI Workbench
This article demonstrates how to synthesize and write data to CSV, JSON, and XML files, plus an Oracle table all at once via the IRI RowGen New Test Data Job wizard in IRI Workbench. Read More
Business Intelligence (BI)
This article is a continuation of the previous article, which introduced IRI support for XLS and XLSX file formats in the SortCL program used for moving and manipulating spreadsheet data in both the IRI Voracity data management (ETL, data quality, etc.) Read More
Test Data
Automating where you can, when you can, is the basis of DevOps automation. Allowing IRI job script executions which mask or synthesize test data to be handled in the CI/CD pipeline supports this pursuit. Read More
Data Masking/Protection
One of the data masking requirements for IRI FieldShield that we see in PHI anonymization use cases involves the blurring of dates at the row level, instead of the column level while providing a configurable option to retain the interval between those dates. Read More