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Frequently asked questions
What new dbt metadata can I now see in Sifflet?
You’ll now find key dbt metadata like the last execution timestamp and status directly within the dataset catalog and asset pages. This makes real-time metrics and pipeline health monitoring more accessible and actionable across your observability platform.
How does Sifflet support data governance at scale?
Sifflet supports scalable data governance by letting you tag declared assets, assign owners, and classify sensitive data like PII. This ensures compliance with regulations and improves collaboration across teams using a centralized observability platform.
Can I use the Fivetran integration to monitor data pipeline health?
Absolutely! By surfacing connector statuses and metadata directly in the lineage graph and catalog, Sifflet helps you stay on top of pipeline health and detect issues early. It's a powerful step forward in proactive data pipeline monitoring.
Is Forge able to automatically fix data issues in my pipelines?
Forge doesn’t take action on its own, but it does provide smart, contextual guidance based on past fixes. It helps teams resolve issues faster while keeping you in full control of the resolution process, which is key for maintaining SLA compliance and data quality monitoring.
Why is data quality monitoring so important for data-driven decision-making, especially in uncertain times?
Great question! Data quality monitoring helps ensure that the data you're relying on is accurate, timely and complete. In high-stress or uncertain situations, poor data can lead to poor decisions. By implementing scalable data quality monitoring, including anomaly detection and data freshness checks, you can avoid the 'garbage in, garbage out' problem and make confident, informed decisions.
Why is combining data catalogs with data observability tools the future of data management?
Combining data catalogs with data observability tools creates a holistic approach to managing data assets. While catalogs help users discover and understand data, observability tools ensure that data is accurate, timely, and reliable. This integration supports better decision-making, improves data reliability, and strengthens overall data governance.
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 do real-time alerts support SLA compliance?
Real-time alerts are crucial for staying on top of potential issues before they escalate. By setting up threshold-based alerts and receiving notifications through channels like Slack or email, teams can act quickly to resolve problems. This proactive approach helps maintain SLA compliance and keeps your data operations running smoothly.