Documentation
Discoveries

Discoveries

Discoveries are data findings revealed by Agents when they find something noteworthy in your data. They analyze data to generate opportunities, anomalies, and recommendations that require your attention.

What are Discoveries?

Discoveries are the output of Altertable's monitoring system:

  • Generated by agents: agents continuously analyze your data
  • Require human review: team members approve or reject findings
  • Include context: each discovery links to its source and reference
  • Provide recommendations: agents explain what they found and suggest actions

Goals of Discoveries

  • Detect anomalies: identify and alert on data points that deviate from historical patterns
  • Reduce noise: only notify when something meaningful happens
  • Enable collaboration: team members review and discuss findings
  • Accelerate response: get actionable findings without manual analysis

Discovery Lifecycle

Every discovery moves through a review workflow:

StatusDescription
Needs reviewAwaiting review from a team member
AcceptedApproved and marked as actionable
RejectedDismissed as not relevant or false positive

Discovery Types

Discoveries can contain different types of data:

TypeDescription
Trend changeRevenue dropped 15% week-over-week
AnomalyUser signups spiked unexpectedly
Schema changeNew tables detected in database
Segment shiftPower user cohort shrinking
New modelsNew semantic models available
Events detectedWeb analytics events ready for analysis

Reviewing Discoveries

When reviewing a discovery:

  1. Read the description and recommendation
  2. Check the visualization if available
  3. Review the source data for context
  4. Approve to mark as actionable or Reject to dismiss

The platform evolves with your input, automatically optimizing the discovery process based on your reviews.

Discovery Sources

Discoveries originate from various references:

  • Insights: monitor individual insights for changes
  • Dashboards: track entire dashboards for anomalies
  • Connections: watch database connections for schema changes
  • Segments: observe user segments for behavioral shifts
  • Semantic models: detect new data models and tables
  • Events: monitor event tracking for new activity

Learn More

  • Agents: autonomous data collaborators that help you automate the work
  • Dashboards: combine insights and attach agents
  • Insights: charts and analyses that agents monitor
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