Take Charge. Trace Anything.
Map out the relationships between your data assets, find what’s broken upstream and prevent downstream impacts with advanced lineage.
Master Mapping
Map your asset dependencies from end-to-end. Modern UI makes it easy to look at lineage at both the table and column level.
Find Root Causes Fast
When data breaks, you need to know why and where. Sifflet’s lineage capabilities help you get to the root cause fast.
Take Care of Business
Assess the impact of data quality issues and prevent downstream trouble before it happens.
Precision Mapping
See how data moves through your system from its origin to final destination and all the stops in between.
- Map your data dependencies on day one with OOTB lineage enabled by integrations & SQL history parsing
- Benefit from last mile dependencies mapping with declarative lineage
- Work with column level granularity
Full Context At Your Fingertips
Everything you need to get to resolution, faster.
- Asset Health Status
- Documentation
Effortless Navigation & Exports
Investigate, collaborate and share your lineage.
- Navigate lineage effortlessly by folding and unfolding your map
- Screengrab lineage
- Export your lineage as a CSV
Reduce Downtime
Built for Everyone
Sifflet's lineage capabilities help reduce data downtime and break down silos between teams.
Go Further
A Guide to Assessing your Need for 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:
Troubleshoot Faster with Data Observability
Ever feel like data issues are the silent productivity killer in your team?
Building trust in your data and solving problems fast shouldn’t feel like guesswork. Enter unified data observability: the game-changer for confidence, efficiency, and smooth operations.
End-To-End Data Observability With Declarative Assets and Lineage
Find out how to leverage Sifflet's declarative framework to give teams a more comprehensive data documentation and governance while simplifying the troubleshooting experience
Improve Data Quality Rapidly
Sifflet’s lineage features help you break silos between teams and get to the bottom of root causes, so the whole company benefits from better data quality.
"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. "
"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."
"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 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."
"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
Data-quality-as-code (DQaC) allows you to programmatically define and enforce data quality rules using code. This ensures consistency, scalability, and better integration with CI/CD pipelines. Read more here to find out how to leverage it within Sifflet
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
AI enhances data observability with advanced anomaly detection, predictive analytics, and automated root cause analysis. This helps teams identify and resolve issues faster while reducing manual effort. Have a look at how Sifflet is leveraging AI for better data observability here
Data observability ensures data governance policies are adhered to by tracking data usage, quality, and lineage. It provides the transparency needed for accountability and compliance. Read more here.
Yes! While smaller organizations may have fewer data pipelines, ensuring data quality and reliability is equally important for making accurate decisions and scaling effectively. What really matters is the data stack maturity and volume of data. Take our test here to find out if you really need data observability.
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