Data observability helps Shippeo’s Customer Experience team respond quickly to issues like missing GPS data or unusual spikes in transport orders. Real-time alerts empower them to act fast, communicate with customers, and keep service levels high.

Yes, it’s designed to fit right in. Sifflet connects to your existing data stack via APIs and supports integrations with tools like Slack, Jira, and Microsoft Teams. It also enables 'Quality-as-Code' for teams using infrastructure-as-code, making it a seamless addition to your DataOps best practices.

Sifflet stands out as a metadata control plane that connects technical reliability with business context. Unlike point solutions, it offers AI-native automation, full data lineage tracking, and cross-functional accessibility, making it ideal for organizations that need to scale trust in their data across teams.

A modern data stack typically includes tools for ingestion, warehousing, transformation and business intelligence. For example, you might use Fivetran for ingestion, Snowflake for warehousing, dbt for transformation and Looker for analytics. Investing in the right observability tools across this stack is key to maintaining data reliability and enabling real-time metrics that support smart, data-driven decisions.

For smaller teams, simplicity and clarity are key. Implementing lightweight data observability dashboards and using tools that support real-time alerts and Slack notifications can help them stay agile without feeling overwhelmed. Also, defining clear roles and giving access to self-service tools boosts autonomy and satisfaction.

Traditional monitoring tools focus on infrastructure and application performance, while data observability digs into the health and trustworthiness of your data itself. At Sifflet, we combine metadata monitoring, data profiling, and log analysis to provide deep insights into pipeline health, data freshness checks, and anomaly detection. It's about ensuring your data is accurate, timely, and reliable across the entire stack.

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.

Data observability helps align technical metrics with strategic business goals. By monitoring real-time metrics and enabling root cause analysis, teams can quickly detect and resolve data issues, reducing downtime and improving decision-making. It’s not just about the data, it’s about the impact that data has on your business.