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Frequently asked questions

Can I use custom dbt metadata for data governance in Sifflet?
Absolutely! Our new dbt tab surfaces custom metadata defined in your dbt models, which you can leverage for better data governance and data profiling. It’s all about giving you the flexibility to manage your data assets exactly the way you need.
Will Sifflet cover any upcoming trends in data observability?
For sure! Our CEO, Salma Bakouk, will be speaking about the top data trends to watch in 2025, including how GenAI and advanced anomaly detection are shaping the future of observability platforms. You’ll walk away with actionable insights for your data strategy.
How does data profiling support GDPR compliance efforts?
Data profiling helps by automatically identifying and tagging personal data across your systems. This is vital for GDPR, where you need to know exactly what PII you have and where it's stored. Combined with data quality monitoring and metadata discovery, profiling makes it easier to manage consent, enforce data contracts, and ensure data security compliance.
Can Sifflet support real-time metrics and monitoring for AI pipelines?
Absolutely! While Sifflet’s monitors are typically scheduled, you can run them on demand using our API. This means you can integrate real-time data quality checks into your AI pipelines, ensuring your models are making decisions based on the freshest and most accurate data available. It's a powerful way to keep your AI systems responsive and reliable.
Is this integration useful for teams focused on data governance and compliance?
Yes, it really is! With enhanced lineage and metadata tracking from source to destination, the Fivetran integration supports better data governance. It helps ensure transparency, traceability, and SLA compliance across your data ecosystem.
How does Sifflet support data lineage tracking across tools like Snowflake and dbt?
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.
How can I monitor data freshness proactively instead of reacting to problems?
You can use a mix of threshold-based alerts, machine learning for anomaly detection, and visual freshness indicators in your BI tools. Pair these with data lineage tracking and root cause analysis to catch and resolve issues quickly. A modern data observability platform like Sifflet makes it easy to set up proactive monitoring tailored to your business needs.
How does a data catalog improve data reliability and governance?
A well-managed data catalog enhances data reliability by capturing metadata like data lineage, ownership, and quality indicators. It supports data governance by enforcing access controls and documenting compliance requirements, making it easier to meet regulatory standards and ensure trustworthy analytics across the organization.
Still have questions?