Adaptive Analytics Workflow
The Adaptive Analytics Workflow is the core mechanism for discovering, investigating, and tracking hidden behavioral signals from your production AI log data.
Discover: New signals are displayed as Insights and Dashboards within a Project.
Repeat: Future analysis and Insights are impacted by all tracked signals.

Discover
Signals from production log data can be discovered through:
Dashboards: Graphical and tabular displays of product state, monitored columns, tracked Segments, and generated Metrics for independent analysis.
Insights: Human readable explanations of patterns found in signals generated from unsupervised analysis of enriched logs. Insights are clustered subsets of log data representing temporal shifts, segments of interesting behavior, or outliers from expected behavior.
Investigate
Signals can be triaged and refined through:
Explorer: Graphical and statistical comparison of subsets of log data corresponding to filters from Insights. Population and Temporal Comparison allows for rapid triage and refinement of filters for Segment creation.
Logs: The raw ingested data and all generated Metrics associated with a filter from an Insights. This is the direct evidence from production data that led to the Insight.
Track
Once specific behaviors have been identified, understood, and refined they can be codified by creating:
Next Steps
Ready to start using DBNL? Head straight to our Quickstart to get set up on the platform and start testing your AI products right away for free.
Want to understand more about the platform? Check out the Architecture, Deployment options, and other aspects of the Platform.
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