Connecting to PostgreSQL-compatible databases for data movement and manipulation in IRI Workbench-supported products like Voracity, CoSort, FieldShield, NextForm and RowGen follows the same paradigm as other relational databases.
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Usually static data masking is performed on production data at rest so it is stored safely, or when replicated to non-production environments for testing or development purposes.
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Production or test data targets, as well as the operational log data, created by SortCL-compatible data manipulation or generation jobs in the IRI Voracity platform and its included products like — IRI CoSort, NextForm, RowGen, FieldShield and DarkShield — are all machine-readable.
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IRI Workbench provides a number of features for working across multiple tables in a database. It includes wizards to: profile databases; classify columns; subset, mask and migrate data; generate test data; etc.
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This article demonstrates processing a web-based data source in the IRI Voracity data management platform. Static and streaming data defined in URLs — including FTP/S, HTTP/S, HDFS, Kafka, MQTT, and MongoDB — are supported by the default data processing engine in Voracity, CoSort Version 10.
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Connecting to and working with data in an Snowflake AWS database from IRI Workbench (WB) is no different than with an on-premise SQL-compatible source. You browse Snowflake tables and exchange metadata in Workbench via JDBC.
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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.
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The Schema Pattern Search in IRI Workbench (WB) can be used to retrieve data in an entire schema matching specific patterns. The search process compares the patterns to all the data in every column of the selected data types in every table in every schema selected.
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The IRI Workbench GUI, built on Eclipse™, provides several ways to create data-driven jobs … jobs which are ultimately expressed in self-documenting plain-text scripts and metadata files.
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This article, along with counterpart articles for Cloudera and HortonWorks, describes the simple 5-step process to connect the IRI Voracity big data management platform to any MapR distribution through the VGrid Gateway.
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This article, along with counterpart articles for HortonWorks (Ambari) and MapR, describes the simple 3-step process to connect the IRI Voracity big data management platform to a Cloudera distribution through the VGrid Gateway.
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