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 part 3 of a 4-part series on Production Analytics. Processing on Par with Information [Part 1] Data Processing Drives Efficiency [Part 2] Unifying the Worlds of Information and Processing [Part 4]
The inclusion of full function data processing in the Production Analytic Platform simplifies the task of gathering data from external sources such as the Internet of Things and clickstream data that requires both intensive exploratory modeling as well as high-speed application and maintenance of those models on real-time and streaming data.
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.
Editors Note, Q2’19: In addition to the method described below, there is now also available to IRI FieldShield (data masking product) or IRI Voracity (data management platform) users a Data Class Database Masking wizard, which can be used if you have pre-classified your data.
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).