Yes, if you're already using Domains, you can add Subdomains incrementally without any disruption. And if you're starting fresh, you can design your ideal hierarchy from day one. Our team is happy to help with architecture workshops to guide your setup for optimal data lineage tracking and observability.

We’ve introduced Augmented Resolution to help teams group related alerts into a single collaborative ticket, streamlining incident response. Plus, with integrations into your ticketing systems, Sifflet ensures that data issues are tracked, communicated, and resolved efficiently. It’s all part of our mission to boost data reliability and support your operational intelligence.

No, Sifflet does not store your data. We designed our platform to discard any data previews immediately after display, and we only retain metadata like table and column names. This approach supports GDPR compliance and strengthens your overall data governance strategy.

Great question! Sifflet acts as a unified observability platform that consolidates metadata from tools like Snowflake and BigQuery into one centralized Data Catalog. By surfacing tags, labels, and schema details, it makes data discovery and governance much easier for all stakeholders.

When choosing a reverse ETL tool, key features to consider include reliable syncing, strong security and privacy controls, and broad integration capabilities. These features help ensure smooth data pipeline monitoring and support data governance across your organization.

A great data observability tool should offer automated data quality checks like data freshness checks and schema change detection, field-level data lineage tracking for root cause analysis, and a powerful metadata search engine. These capabilities streamline incident response and help maintain data governance across your entire stack.

Sifflet provides end-to-end data lineage tracking that connects your tables to dbt models, semantic layers, and BI dashboards. This visibility helps you understand the full impact of any metadata change, ensuring data quality monitoring and reducing the risk of breaking critical business KPIs.

Yes, and that’s one of the things we’re most excited about! Sifflet empowers non-technical users to define custom monitoring rules and participate in data quality efforts without needing to write dbt code. It’s all part of building a culture of shared responsibility around data governance and observability.