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Data Governance & Observability · Consulting (client unnamed)
DataSentinel
Real-time data trust scoring and SLO-backed observability for modern enterprise data stacks.
2025
−60%
Data Incidents in Prod
100%
Pipeline Monitoring
SLO-backed
Alerting Model
Real-time
Trust Model
The Problem
Enterprise data teams lack a unified trust signal for their data assets. Pipelines fail silently, bad data reaches dashboards and ML models, and engineers spend hours in post-mortems instead of building. The 'credit score' for data doesn't exist.
The Approach
- 01Defined a real-time data trust scoring framework based on freshness, completeness, and schema consistency
- 02Implemented SLO-backed alerting that triggers before bad data reaches downstream consumers
- 03Built a data lineage layer to trace anomalies to their source
- 04Designed the admin UX for data team leads to configure thresholds and monitor pipeline health
- 05Created incident runbooks integrated with the alerting layer
Impact
- ✓60% reduction in data incidents reaching production
- ✓Full observability coverage across monitored pipelines
- ✓Mean time to detect data anomalies reduced from hours to minutes
- ✓Data team confidence in reporting increased measurably