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Frequently asked questions

How does Sifflet ensure data security within its data observability platform?
At Sifflet, data security is built into the foundation of our data observability platform. We follow three core principles: least privilege, no storage, and single tenancy. This means we only use read-only access, never store your data, and isolate each customer’s environment to prevent cross-tenant access.
What role did data observability play in improving Meero's data reliability?
Data observability was key to Meero's success in maintaining reliable data pipelines. By using Sifflet’s observability platform, they could monitor data freshness, schema changes, and volume anomalies, ensuring their data remained trustworthy and accurate for business decision-making.
What role does data ownership play in data quality monitoring?
Clear data ownership is a game changer for data quality monitoring. When each data product has a defined owner, it’s easier to resolve issues quickly, collaborate across teams, and build a strong data culture that values accountability and trust.
How does data lineage support compliance with data privacy regulations?
Data lineage plays a key role in compliance monitoring by providing transparency into where data comes from, how it's processed, and where it ends up. This is crucial for meeting regulations like GDPR and HIPAA, and for maintaining strong data governance practices across the organization.
What’s coming next for dbt integration in Sifflet?
We’re just getting started! Soon, you’ll be able to monitor dbt run performance and resource utilization, define monitors in your dbt YAML files, and use custom metadata even more dynamically. These updates will further enhance your cloud data observability and make your workflows even more efficient.
How is AI shaping the future of data observability?

AI enhances data observability with advanced anomaly detection, predictive analytics, and automated root cause analysis. This helps teams identify and resolve issues faster while reducing manual effort. Have a look at how Sifflet is leveraging AI for better data observability here

Why is data observability becoming more important in 2024?
Great question! As AI and real-time data products become more widespread, data observability is crucial for ensuring data reliability, privacy, and performance. A strong observability platform helps reduce data chaos by monitoring pipeline health, identifying anomalies, and maintaining SLA compliance across increasingly complex data ecosystems.
How does Sifflet enhance data governance for my organization?
Sifflet supports data governance by allowing you to classify assets with tags and labels, define business terms in a shared glossary, and track data lineage. These features help ensure consistent definitions and safe handling of sensitive data across your stack.
Still have questions?