See the Whole Picture with Sifflet and Snowflake
Your Snowflake data powers decisions across your business, but when something breaks, it’s more than pipelines at risk. It’s dashboards, AI models, customer reporting, and trust. Sifflet brings business context into your observability layer so you can fix what matters, faster.
Why chose Sifflet for Snowflake?
Your Snowflake data powers decisions across teams, but when quality issues strike, it’s not just pipelines that break. It’s customer experiences, revenue reporting, AI model accuracy, and more.
That’s where Sifflet stands apart.
Sifflet brings business context into the heart of data observability, so you don’t just know what’s broken, you know what matters. Our platform weaves metadata, pipeline behavior, and usage patterns into a unified map of technical and business logic, helping your team spot, triage, and resolve issues before they become downstream disasters.
Deep Integration with Snowflake
Sifflet enhances the observability of your Snowflake stack by letting you:
Prioritize What Matters Most
Not every broken table is worth a PagerDuty alert. Sifflet identifies which anomalies impact key dashboards, SLAs, or ML models, so your team focuses where it counts.
Map Lineage with Business Logic
See how data flows across your stack, not just pipelines, but people. Sifflet combines metadata and usage patterns to show who’s using what, and why. From column to customer.
Cut Through the Noise
Sifflet delivers context-rich alerts that combine technical symptoms with business impact. Your team gets fewer false alarms, and faster resolution.
Leverage Time Travel for Smarter Detection
Historical snapshots enhance anomaly detection with temporal intelligence.
Snowflake-specific assets
Sifflet supports multiple Snowflake-specific objects, like streams and stages, for exhaustive coverage.
Usage and Snowflake metadata
Get detailed statistics about the usage of your Snowflake assets, in addition to various metadata (like tags, descriptions, and table sizes) retrieved directly from Snowflake.
Field-level lineage
Have a detailed understanding of how data flows through your platform via field-level end-to-end lineage for Snowflake.
Built for Modern Data Teams on Snowflake
- Trusted by Snowflake-Centric Enterprises Across Europe and the U.S.
- Native integration with Snowflake’s metadata and query engine
- Designed for scale, trust, and business alignment
“With Sifflet, we don’t just detect anomalies in Snowflake. We understand their real-world impact, and we act before anyone downstream even notices.”
Head of Data Governance, European Retail Leader
Perfect For…
- Data Leaders deploying Snowflake as the central nervous system of their organization
- Analytics Teams needing reliable, self-serve dashboards and clear ownership
- Governance & Risk Teams looking to enforce data quality, lineage, and auditability
- AI & ML Teams training models on clean, explainable data they can trust
Go Further
Data Observability for your data stack with Snowflake
Discover the Core Capabilities That Ensure Data Quality in Snowflake
Do You need Data Observability?
Every data-driven team dreams of creating "fireworks" with their insights. But without control, the "fire" of the modern data stack can spark chaos.Discover if you're fighting fires or igniting fireworks:
Sifflet’s AI Helps Us Focus on What Moves the Business
What impressed us most about Sifflet’s AI-native approach is how seamlessly it adapts to our data landscape — without needing constant tuning. The system learns patterns across our workflows and flags what matters, not just what’s noisy. It’s made our team faster and more focused, especially as we scale analytics across the business.
"Enabler of Cross Platform Data Storytelling"
"Sifflet has been a game-changer for our organization, providing full visibility of data lineage across multiple repositories and platforms. The ability to connect to various data sources ensures observability regardless of the platform, and the clean, intuitive UI makes setup effortless, even when uploading dbt manifest files via the API. Their documentation is concise and easy to follow, and their team's communication has been outstanding—quickly addressing issues, keeping us informed, and incorporating feedback. "
"Building Harmony Between Data and Business With Sifflet"
"Sifflet serves as our key enabler in fostering a harmonious relationship with business teams. By proactively identifying and addressing potential issues before they escalate, we can shift the focus of our interactions from troubleshooting to driving meaningful value. This approach not only enhances collaboration but also ensures that our efforts are aligned with creating impactful outcomes for the organization."
" Sifflet empowers our teams through Centralized Data Visibility"
"Having the visibility of our DBT transformations combined with full end-to-end data lineage in one central place in Sifflet is so powerful for giving our data teams confidence in our data, helping to diagnose data quality issues and unlocking an effective data mesh for us at BBC Studios"
"Sifflet allows us to find and trust our data"
"Sifflet has transformed our data observability management at Carrefour Links. Thanks to Sifflet's proactive monitoring, we can identify and resolve potential issues before they impact our operations. Additionally, the simplified access to data enables our teams to collaborate more effectively."
"A core component of our data strategy and transformation"
"Using Sifflet has helped us move much more quickly because we no longer experience the pain of constantly going back and fixing issues two, three, or four times."
Frequently asked questions
Yes, Sifflet leverages AI to enhance data observability with features like anomaly detection and predictive insights. This ensures your data systems remain resilient and can support advanced analytics and AI-driven initiatives. Have a look at how Sifflet is leveraging AI for better data observability here
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