“Have you stopped speeding?” You could probably object to a leading question like this in court, but what happens when an important question with only a yes or no answer is solicited on a mandatory form, and the response becomes part of an actionable database record?
In this final article of the series covering the Production Analytic Platform paradigm, we look at data virtualization—a key requirement in today’s multi-source, data-overloaded world.
This is the first of a four-part series of blog articles examining the inherent tradeoffs between data processing and information storage and presentation within traditional ETL paradigms — from the ODS to the data lake.
Considering data processing as a central component of data management and on a par with databases offers new insights on how to improve overall efficiency and return on investment in traditional data warehouses.
Detecting additions and updates to database tables for data replication, ETL, PII masking, and other incremental data movement and manipulation activities can be automated in IRI Voracity workflows designed and run in IRI Workbench (WB).
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.