MONITOR

Lean. Mean. Monitoring Machine. 

Finally, dynamic monitoring that can keep up with your stack. AI features optimize your coverage and minimize noise, detecting issues before they arise. 

Sifflet dashboard features overview

Customize to Your Heart’s Content

Sifflet offers both a robust library of out of the box monitors and customization capability. Your teams decide what needs monitoring and how to set it up. 

Bye-Bye, Alert Fatigue

Data engineers don’t need more alerts, they need smarter alerts. Our AI learns adaptively as it goes to optimize coverage and minimize noise.  

Hello, Data Reliability 

Data reliability is reinforced with less manual work for technical teams, faster response times, and overall stronger performance. 

IMPLEMENT

Ready-to-Go Monitors 

Quick set up and implementation means quicker results. 

  • See value instantly with pre-defined templates to check data at field and table levels
  • Help your business users and technical teams meet their quality and reliability objectives thanks to ready-to-go monitors
Sifflet dashboard overview
SUPERVISE

Lifecycle Monitoring

End-to-end coverage that never sleeps. 

  • Detect anomalies continuously thanks to ML models 
  • Give your business users ownership over monitors through LLM monitoring setup 
  • Maintain control and accuracy with optional manual setup and user feedback
Sifflet dashboard features overview
MAINTAIN

Scalability & Optimization

Monitoring that’s easy to maintain and coverage that’s just right.

  • Optimize monitoring coverage and minimize noise levels with AI-powered suggestions and supervision
  • Implement programmatic monitoring set up and maintenance with Data Quality as Code (DQaC)
Sifflet dashboard overview
TEAMS

Reinforced Reliability

Built for Everyone

Sifflet’s monitoring features reinforce data reliability for all users, so business can deliver.

Data Users

Stop working with corrupt data. Sifflet embeds alerts in your dashboards, so you know exactly when there’s an incident or issue. And you can set up data monitors on your own.

Data Engineers

No more scaling monitors manually. Sifflet’s ML will optimize coverage for you, so you can be proactive instead of reactive in reducing downtimes.

Data Leaders

Give your teams the tools they need to reduce monitoring tasks by up to 50% thanks to Sifflet’s monitoring features.

Data Reliability, Reinforced

Sifflet’s monitoring features reinforce data reliability for all users, so business can deliver.

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.

Simoh-Mohamed Labdoui
Head of Data
"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. "

Callum O'Connor
Senior Analytics Engineer, The Adaptavist
"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."

Sophie Gallay
Data & Analytics Director, Etam
" 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"

Ross Gaskell
Software engineering manager, 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."

Mehdi Labassi
CTO, Carrefour Links
"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."

Sami Rahman
Director of Data, Hypebeast

Frequently asked questions

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.
How does Sifflet support data quality monitoring?
Sifflet makes data quality monitoring seamless with its auto-coverage feature. It automatically suggests fields to monitor and applies rules for freshness, uniqueness, and null values. This proactive monitoring helps maintain SLA compliance and keeps your data assets trustworthy and safe to use.
What is metrics observability and why does it matter for business users?
Metrics observability helps business users trust and understand the KPIs they rely on by making it easy to trace how metrics are defined, calculated, and connected to other data assets. With Sifflet’s observability platform, teams can ensure their business metrics are accurate, reliable, and aligned across departments.
How does Sifflet support data lineage tracking and governance?
Sifflet’s unified data catalog and observability features bring context-rich insights into your data workflows. This integration enhances data lineage tracking and supports stronger data governance by giving teams a holistic view of how data flows and transforms across your systems.
What is SQL Table Tracer and how does it help with data lineage tracking?
SQL Table Tracer (STT) is a lightweight library that automatically extracts table-level lineage from SQL queries. It identifies both destination and upstream tables, making it easier to understand data dependencies and build reliable data lineage workflows. This is a key component of any effective data observability strategy.
How does metadata management support data governance?
Strong metadata management allows organizations to capture details about data sources, schemas, and lineage, which is essential for enforcing data governance policies. It also supports compliance monitoring and improves overall data reliability by making data more transparent and trustworthy.
What practical steps can companies take to build a data-driven culture?
To build a data-driven culture, start by investing in data literacy, aligning goals across teams, and adopting observability tools that support proactive monitoring. Platforms with features like metrics collection, telemetry instrumentation, and real-time alerts can help ensure data reliability and build trust in your analytics.
What makes a data observability platform truly end-to-end?
Great question! A true data observability platform doesn’t stop at just detecting issues. It guides you through the full lifecycle: monitoring, alerting, triaging, investigating, and resolving. That means it should handle everything from data quality monitoring and anomaly detection to root cause analysis and impact-aware alerting. The best platforms even help prevent issues before they happen by integrating with your data pipeline monitoring tools and surfacing business context alongside technical metrics.
Still have questions?