iAURA Data Observability by Persistent
Trusted data for the Databricks lakehouse
Persistent’s iAURA Data Observability brings intelligence and automation to how enterprises monitor data. It monitors the health, reliability and timeliness of their data across the Databricks Data Intelligence Platform.
Designed to complement the open, scalable and AI-ready architecture of Databricks, iAURA unifies three critical pillars of data assurance into a single intelligent framework:
- Data quality: Automatically generates and applies data quality rules, validating integrity, consistency and correctness against incoming datasets to ensure they meet defined data quality expectations.
- Data reconciliation: Continuously reconciles records between source and target systems, ensuring no data is lost, duplicated or transformed incorrectly during ingestion, transformation or consumption.
- Data freshness: Monitors ingestion timeliness and volume, verifying that data pipelines operate at the expected frequency and scale, and proactively alerts teams to delays or anomalies.
Together, these capabilities create a comprehensive observability layer that keeps enterprise data accurate, complete and current, powering trusted analytics, regulatory compliance and AI-driven decision-making.
- Trusted decisions: Reliable, reconciled data builds confidence
- Efficiency gains: Automation cuts effort and cost
- Faster outcomes: Fresh, timely data accelerates decisions
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