Data lineage tracking shows how data flows through your systems and how different assets depend on each other. This is incredibly helpful for root cause analysis because it lets you trace issues back to their source quickly. With Sifflet’s lineage capabilities, you can understand both upstream and downstream impacts of a data incident, making it easier to resolve problems and prevent future ones.

While a data catalog helps you find and understand your data, data observability ensures that the data you find is actually reliable. Observability tools like Sifflet monitor the health of your data pipelines in real time, using features like data freshness checks, anomaly detection, and data quality monitoring. Together, they give you both visibility and trust in your data.

Reverse ETL automates the syncing of data from your warehouse to business apps, helping reduce the number of manual data requests across teams. This improves data reliability by ensuring consistent, up-to-date information is available where it’s needed most, while also supporting SLA compliance and data automation efforts.

Great question! Data observability plays a key role in GDPR compliance by giving teams real-time visibility into where personal data lives, how it's being used, and whether it's being processed according to user consent. With an observability platform in place, you can track data lineage, monitor data quality, and quickly respond to deletion or access requests in a compliant way.

The ability to define joins directly in the monitor setup interface means you can now monitor relationships across datasets without writing custom SQL. This is crucial for data quality monitoring because many issues arise from inconsistencies between related tables. Now, you can catch those problems early and ensure better data reliability across your pipelines.

Data lineage is essential for GDPR because it helps you trace personal data from source to destination. This means you can see where PII is stored, how it flows through your data pipelines, and which reports or applications use it. With this visibility, you can manage deletion requests, audit data usage, and ensure data governance policies are enforced consistently.

No worries at all! With Sifflet’s Universal Connector API, you can integrate data from virtually any source. This flexibility means you can monitor your entire data ecosystem and maintain full visibility into your data pipeline monitoring, no matter what tools you're using.

Absolutely! While dbt is fantastic for defining tests, Sifflet takes it further with advanced data drift detection and anomaly detection. Our platform uses intelligent monitoring templates that adapt to your data’s behavior, so you can spot unexpected changes like missing rows or unusual values without setting manual thresholds.