Among the many database-centric features in IRI Workbench is the ability to create, modify, and execute SQL statements manually or graphically. These “SQL scrap-booking” features are available through the free Data Tools Platform (DTP) plug-in for Eclipse, which also supports IRI job wizards for database:profiling, searching, classification, E-R diagramming, and integrity checking integration, including ETL, pivoting, slowly changing dimensions, and change data capture column masking, including format-preserving encryption, redaction, and pseudonymization subsetting, test data generation, and bulk loading migration, replication, and offline reorgs
To use the cross-platform(!)
Sonra recently demonstrated the processing of complex XML data in the IRI Voracity data management platform with the help of Sonra’s Flexter Data Liberator software. Flexter and Voracity are a match made in heaven.
This article focuses on IRI Workbench execution options for scripts based on the SortCL program language, which covers IRI Voracity ETL, CDC, SDC, pivoting and subsetting jobs, as well as its constituent product jobs; i.e.,
For the last 30 or so years, the precursor to most large scale business intelligence (BI) environments has been the Enterprise Data Warehouse (EDW). A data warehouse (DW) is usually a central database (DB) for reporting, planning, and analyzing summarized, subject-matter data integrated from disparate, historical transaction sources.
This is the third in a series of articles for creating an IRI Voracity ETL flow of a month-end job for processing sales transactions.
The traditional or enterprise data warehouse (EDW) has been at the center of data’s transformation to business intelligence (BI) for years. An EDW involves a centralized data repository (traditionally, a relational database) from which data marts and reports are built.
Update Q3’2019: Subsequent to the development of the IRI Voracity Add-On for Splunk described below, there is now also a Splunkbase-registered IRI Voracity App for Splunk available for Seamless Data Preparation, Indexing, and Visualization…
After our first examples of external unstructured data preparation and PII data masking for Splunk generated interest in these capabilities, IRI wanted to develop a direct integration from the Splunk user interface (UI).