This article looks at sets from an informational processing perspective; what they are; how they are constructed; and, distinct ways in which data can be drawn from sets within IRI software products using the SortCL data definition and processing program; i.e.,
Update: Q2’16: In addition to the database profiling wizard in the data discovery menu group in IRI Workbench described below, IRI has introduced robust data classification that enables the application of field rules for multi-source data transformation and protection through data class libraries.
Data architects and data scientists, as well as DBAs and governance teams, may need to use or migrate data in legacy file formats and databases. Additionally, the ability to mash-up those sources with newer file and database repositories is important in data integration (ETL) and analytic projects, as well as in data profiling for data loss prevention and privacy law compliance.
This article is fourth in a 4-part series on managing metadata assets in the IRI Workbench IDE through EGit. It focuses on the security of your metadata.
This article is third in a 4-part series on managing metadata assets in the IRI Workbench IDE through EGit. It focuses on its value in tracking metadata lineage.
This article is second in a 4-part series on managing metadata assets in the IRI Workbench IDE through EGit. It focuses on its metadata version control.
This article is first in a 4-part series on managing metadata assets in the IRI Workbench IDE. It focuses on the value of a metadata hub in general, and an Egit implementation in particular.
Data and database migration are key considerations for any system implementation, upgrade, or consolidation. Data migration happens for many reasons, like appliance upgrades or enhancements, server maintenance, or data center relocation.