Sifflet is built with data governance in mind. Our platform offers robust data lineage tracking, audit logging, and anomaly detection features that help enforce data contracts and monitor for compliance issues like GDPR violations. By providing full transparency into your data pipelines, Sifflet helps you maintain trust and accountability across your data ecosystem.

Data lineage tracking is key to understanding how data flows through your systems. It helps teams visualize the origin and transformation of datasets, making root cause analysis and impact assessments much faster. For teams focused on data observability and pipeline health, this feature is a must-have.

Sifflet stands out as a metadata control plane that connects technical reliability with business context. Unlike point solutions, it offers AI-native automation, full data lineage tracking, and cross-functional accessibility, making it ideal for organizations that need to scale trust in their data across teams.

Great question! When you integrate dbt with Sifflet, you unlock a whole new level of data observability. Sifflet enhances visibility into your dbt models by pulling in metadata, surfacing test results, and mapping them into a unified lineage view. This makes it easier to monitor data pipelines, catch issues early, and ensure data reliability across your organization.

Shippeo uses Sifflet’s data observability platform to monitor every stage of their data pipelines. By implementing raw data monitoring, intermediate layer checks, and front-facing metric validation, they catch issues early and maintain trust in their real-time supply chain visibility tools.

Declared assets appear in your Data Catalog just like built-in assets, with full metadata and business context. This improves data quality monitoring by making it easier to track data lineage, perform data freshness checks, and ensure SLA compliance across your entire pipeline.

Sentinel and Sage, two of Sifflet’s AI agents, continuously monitor data lineage, usage patterns, and operational metrics to detect issues early. By bundling related alerts, identifying root causes, and suggesting fixes, they reduce downtime and improve overall data reliability. This kind of automated data quality monitoring helps teams stay ahead of incidents and maintain SLA compliance.

Absolutely! Sifflet Insights connects to your broader observability platform, giving you visibility into data pipeline health right from your BI dashboards. It helps track incidents, monitor data freshness, and detect anomalies before they impact your business decisions.