Dashboards offer a heads up display of answers to common questions, but are not generally useful when the questions are not pre-defined – the unknowns. For these problems, you often don't have a single piece of data which by itself provides a definitive answer, but several pieces of information together can form a preponderance of evidence that suggests an answer. Immediate Insight’s Immediate Data Exploration Analytics (IDEA) technology suite unlocks actionable insights into machine and human data by combining search, analytics, real time interactive processing, and a data action framework.
The fine grained data action framework incorporates our Data Router and Workflow Automation to enable organizations to create sophisticated policies and enforce business processes. With the Data Router the system can automatically tag, delete, alert, learn, execute custom scripts, develop data feeds, and trigger defined workflow stages. In the workflow automation and tracking process data of interest is defined and forwarded to a defined instance for further processing. For each stage, metadata is added to the source event and workflow events are created and indexed. Workflow tracking allows business processes steps to be visible from the underlying raw event data, enabling customers to create actionable, business level events.
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Immediate Data Exploration Analytics
Immediate Insight is designed to let operators create new queries with a simple click and respond with results in a second or less. Structured and unstructured data is organized in a unique way enabling high performance complex queries, even with datasets of hundreds of millions of records. This simple click and explore model lets human operators see a lot of associated data about an issue very quickly. Proprietary analytics identify and cluster similar messages, enabling users to manage related messages as a whole, even if they are not identical. Users are able to quickly eliminate the irrelevant with a one-click analytic like ‘less like this’, isolating the interesting data. The system tracks entities, their associations, and stores information about what they've done in the past as metadata. This associative and accumulative approach enables the system to learn as it sees new data and enables queries that return much better insight.