Define clear success KPIs that support ROI, such as improvements in SLA compliance, reduction in ingestion latency, or increased data reliability. Using data observability dashboards and pipeline health metrics can help you monitor progress and communicate value to stakeholders. It's also important to set expectations early and maintain strong internal communication.

Our Head of Product, Martin Zerbib, will walk you through how Sifflet enables data lineage tracking, real-time metrics, and data profiling at scale. You’ll get a sneak peek at our roadmap and see how we’re making data more accessible and reliable for teams of all sizes.

We’re focused on solving the next generation of challenges, like hybrid environments, end-to-end data lineage tracking, and scaling data trust. Whether it's batch data observability or real-time pipeline monitoring, our mission is to help organizations build resilient, transparent, and future-proof data stacks.

Absolutely! Sifflet’s data lineage tracking gives you a clear view of how data flows and transforms across your systems. This level of transparency is crucial for root cause analysis and ensuring data governance standards are met.

Machine learning is at the heart of our data quality monitoring efforts. We've developed models that can detect anomalies, data drift, and schema changes across pipelines. This allows teams to proactively address issues before they impact downstream processes or SLA compliance.

jobvalley enhanced data visibility by implementing Sifflet’s observability platform, which included a powerful data catalog. This centralized hub made it easier for teams to discover and access the data they needed, fostering better collaboration and transparency across departments.

Sifflet enables comprehensive data pipeline monitoring through features like monitoring-as-code and seamless integration with data lineage tracking and governance tools. This gives Carrefour full visibility into their pipeline health and helps ensure SLA compliance.

When a data catalog integrates seamlessly with your databases, cloud storage, and data lakes, it enhances your ability to monitor data pipelines in real time. This connectivity supports better ingestion latency tracking and helps maintain a reliable observability platform.