Event CoverageLive
96%
events carry required identifiers
✓user_id coveragestable
✓device_id mappingstable
⚠session.sourcemissing
4% flagged for identifier review
Data Teams
Keep product signals clean,typed and ready for analysis.
Validate event capture, inspect schema quality, monitor pipeline health and prepare behavioural data for AI-powered analysis.
Schema HealthLive
7properties need review
⚠checkout.product_idunmapped
⚠session.referrermissing
✓user.plan_typeclean
✓event.sourceclean
Mostly unmapped checkout fields
core identifiers mapped
events checked this hour
typed properties approved
Data Quality
How data teams keep product analysis trustworthy.
Validate live event capture
Confirm that events are firing with the right identifiers, properties and timestamps before dashboards are built on top.
Inspect property quality
Surface unmapped, missing or noisy custom properties and route fixes to the right engineering owner.
Monitor pipeline health
Track event volume trends, schema drift alerts and capture gaps so problems surface before they reach analysts.
Prepare AI-ready data
Type, clean and approve the fields that power ACAI analysis so every answer is grounded in trusted behavioural data.
Schema healthLive eventsProperty qualityAI-ready data
Team Workflow
Turn schema gaps into clean, trusted data loops.
Audit the schema
Pull the full event list, check identifier coverage and flag any properties that are missing, duplicated or incorrectly typed.
Route the gaps
Assign missing or broken fields to engineering owners, track fix status and verify capture in the live stream.
Ship clean data
Mark approved fields as AI-ready, export the trusted dataset and confirm that downstream analysis is grounded in verified events.
Recommended Plays
Use Advaita when the team needs evidence before the next product call.
- Review raw event shape before teams build dashboards.
- Spot missing identifiers and noisy custom properties.
- Prepare trusted datasets for analysis agents and exports.