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Show Your Stack Who’s Boss
Unified data observability that packs a three-in-one punch. From data discovery to integrated monitoring and troubleshooting capabilities, you’ll be the one in charge.
Seamlessly connect with all your favorite data tools to centralize insights and unlock the full potential of your data ecosystem.

Join the ranks of happy customers who’ve made Sifflet a G2 leader, trusted for its innovation and impact
Stay ahead of issues with real-time alerts that keep you informed and in control of your data health
Organize, discover, and leverage your data assets effortlessly with a smart, searchable catalog built for modern teams.
Harness the power of AI-driven suggestions to improve efficiency, accuracy, and decision-making across your workflows.

Empower your team with tailored access, enabling secure collaboration that drives smarter decisions.
Frequently asked questions
How can data observability support a Data as a Product (DaaP) strategy?
Data observability plays a crucial role in a DaaP strategy by ensuring that data is accurate, fresh, and trustworthy. With tools like Sifflet, businesses can monitor data pipelines in real time, detect anomalies, and perform root cause analysis to maintain high data quality. This helps build reliable data products that users can trust.
Can Sifflet Insights help with data pipeline monitoring?
Absolutely! Sifflet Insights connects to your broader observability platform, giving you visibility into data pipeline health right from your BI dashboards. It helps track incidents, monitor data freshness, and detect anomalies before they impact your business decisions.
Where can I find Sifflet at Big Data LDN 2024?
You can find the Sifflet team at Booth Y640 during Big Data LDN on September 18-19. Stop by to learn more about our data observability platform and how we’re helping organizations like the BBC and Penguin Random House improve their data reliability.
Why is combining dbt Core with a data observability platform like Sifflet a smart move?
Combining dbt Core with a data observability platform like Sifflet helps data teams go beyond transformation and into full-stack monitoring. It enables better root cause analysis, reduces time to resolution, and ensures your data products are trustworthy and resilient.
How does data observability improve the value of a data catalog?
Data observability enhances a data catalog by adding continuous monitoring, data lineage tracking, and real-time alerts. This means organizations can not only find their data but also trust its accuracy, freshness, and consistency. By integrating observability tools, a catalog becomes part of a dynamic system that supports SLA compliance and proactive data governance.
What kind of monitoring should I set up after migrating to the cloud?
After migration, continuous data quality monitoring is a must. Set up real-time alerts for data freshness checks, schema changes, and ingestion latency. These observability tools help you catch issues early and keep your data pipelines running smoothly.
Why does great design matter in data observability platforms?
Great design is essential in data observability platforms because it helps users navigate complex workflows with ease and confidence. At Sifflet, we believe that combining intuitive UX with a visually consistent UI empowers Data Engineers and Analysts to monitor data quality, detect anomalies, and ensure SLA compliance more efficiently.
Why is full-stack visibility important in data pipelines?
Full-stack visibility is key to understanding how data moves across your systems. With a data observability tool, you get data lineage tracking and metadata insights, which help you pinpoint bottlenecks, track dependencies, and ensure your data is accurate from source to destination.
Data Observability is Now
Make Data Observability Everyone’s Business Now







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