Data Transformation
Forty years after the first release of IRI CoSort for CP/M, CoSort v10 for Unix, Linux, and Windows platforms was released in the middle of 2018.
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Business Intelligence (BI)
This article covers installation of the KNIME Analytics Platform as a core feature in the IRI Workbench IDE for Voracity, built on Eclipse, as well as the IRI Voracity Data Provider, or Job Source, node for KNIME described in this article.
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Business Intelligence (BI)
In Q3’19, IRI created a new, free app for Splunk Enterprise and Enterprise Security users that seamlessly indexes data from any Voracity platform data wrangling or protection job.
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Business Intelligence (BI)
In predictive analytics, machine learning involves training a computer to evaluate data sets and create prediction models from trends it finds in the data. Machine learning builds off traditional statistics and creates larger and more advanced models faster than a person ever could.
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Big Data
Business Intelligence (BI)
Before you can make use of the data you have and trust its value for, analytic, testing, and other production jobs, you have to know enough about that data.
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Big Data
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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Business Intelligence (BI)
Oracle Data Visualization Desktop, Oracle DV or DVD for short, is business intelligence (BI) software that can organize, aggregate, and visualize data for informational outcomes. What seems to make this BI software unique is its ability to create slideshow presentations from its different visualizations.
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Big Data
An operational data store (or “ODS”) is another paradigm for integrating enterprise data that is relatively simpler than a data warehouse (DW).
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Data Transformation
The Schema Data Class Search wizard in IRI Workbench (WB) can be used to match data in entire schemas to configured data classes. The search process compares the matchers in the data classes with the data to determine the best match, if any.
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