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Frequently asked questions

What can I expect from Sifflet at Big Data Paris 2024?
We're so excited to welcome you at Booth #D15 on October 15 and 16! You’ll get to experience live demos of our latest data observability features, hear real client stories like Saint-Gobain’s, and explore how Sifflet helps improve data reliability and streamline data pipeline monitoring.
Can Sifflet help me trace how data moves through my pipelines?
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.
What’s the first step when building a modern data team from scratch?
The very first step is to set clear objectives that align with your company’s level of data maturity and business needs. This means involving stakeholders from different departments and deciding whether your focus is on exploratory analysis, business intelligence, or innovation through AI and ML. These goals will guide your choices in data stack, platform, and hiring.
Why is collaboration important in building a successful observability platform?
Collaboration is key to building a robust observability platform. At Sifflet, our teams work cross-functionally to ensure every part of the platform, from data lineage tracking to real-time metrics collection, aligns with business goals. This teamwork helps us deliver a more comprehensive and user-friendly solution.
Why is declarative lineage important for data observability?
Declarative lineage is a game changer because it provides a clear, structured view of how data flows through your systems. This visibility is key for effective data pipeline monitoring, root cause analysis, and data governance. With Sifflet’s approach, you can track upstream and downstream dependencies and ensure your data is reliable and well-managed.
How does Sifflet help with compliance monitoring and audit logging?
Sifflet is ISO 27001 certified and SOC 2 compliant, and we use a separate secret manager to handle credentials securely. This setup ensures a strong audit trail and tight access control, making compliance monitoring and audit logging seamless for your data teams.
Why is data observability important for monetizing data products?
When you're selling data, trust is everything. Data observability ensures your data is accurate, fresh, and traceable, which builds client confidence. Carrefour, for example, used observability to monitor over 800 assets and enforce data quality across 8 countries, making their data products reliable and revenue-generating at scale.
How does Sifflet ensure a user-friendly experience for data teams?
We prioritize user research and apply UX principles like Jacob’s Law to design familiar and intuitive workflows. This helps reduce friction for users working with tools like our Sifflet Insights plugin, which brings real-time metrics and data quality monitoring directly into BI dashboards like Looker and Tableau.
Still have questions?