The future of data observability is all about scale and responsibility. With AI adoption growing and regulations tightening, businesses need observability tools that can handle unstructured data, ensure SLA compliance, and support security observability. At Sifflet, we're already helping customers monitor ML models and enforce data contracts, and we're excited about building self-healing pipelines and extending observability to new data types.

Metadata provides context about your data, such as who created it, when it was modified, and how it's classified. In a data observability platform, strong metadata management enhances data discovery, supports compliance monitoring, and ensures consistent, high-quality data across systems.

Absolutely! SQL Table Tracer is designed with a minimal API and modular architecture, making it easy to plug into larger observability platforms. It provides the foundational data needed for building features like data lineage tracking, pipeline health dashboards, and SLA monitoring.

Successful data governance is measured through KPIs that tie directly to business outcomes. This includes metrics like how quickly teams can find data, how often data quality issues are caught before reaching production, and how well teams follow access protocols. Observability tools help track these indicators by providing real-time metrics and alerting on governance-related issues.

Absolutely. Sifflet is designed to be accessible to everyone. With an intuitive UI and our AI Assistant, even non-technical users can set up data quality monitors, track real-time metrics, and contribute to data governance without writing a line of code.

Absolutely! Sifflet offers both SaaS and self-managed deployment models. With the self-managed option, you can run the platform entirely within your own infrastructure, giving you full control and helping meet strict compliance and security requirements.

Many teams are looking for more flexible and cost-efficient observability tools that offer better business user access and faster implementation. Monte Carlo, while a pioneer, has become known for its high costs, limited customization, and lack of business context in alerts. Newer platforms like Sifflet and Metaplane focus on real-time metrics, cross-functional collaboration, and easier setup, making them more appealing for modern data teams.

Yes, definitely! Companies like Saint-Gobain will be sharing how they’ve used Sifflet for data observability, data lineage tracking, and SLA compliance. It’s a great chance to hear how others are solving real data challenges with our platform.