This article is third in a 4-part series on feeding the Datadog cloud analytic platform with different kinds of data from IRI Voracity operations. It focuses on visualizing Voracity-wrangled in Datadog.
This article is first in a 4-part series on feeding the Datadog cloud analytic platform with different kinds of data from IRI Voracity operations. It focuses on the value of Datadog and Voracity together.
Splunk Phantom is an orchestration, automation, and response technology for running “Playbooks” to respond to various conditions. Phantom connects to Splunk Enterprise using the Phantom App for Splunk, so that actions can be taken on knowledge derived from data indexed in Splunk.
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.
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 data management platform and its included products (IRI CoSort, NextForm, RowGen, FieldShield and DarkShield) are all machine-readable.
This article demonstrates processing a web-based data source in the IRI Voracity data management platform. Static and streaming data defined in URLs — including flat files in formats like CSV or through FTP/S, HTTP/S, HDFS, Kafka, MQTT, and MongoDB — are supported by the default data processing engine in Voracity, CoSort Version 10.