Take Charge. Trace %%Anything.%%

Map out the relationships between your data assets, find what’s broken upstream and prevent downstream impacts with advanced lineage. 

Sifflet dashboard features overview

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. 

OVERSEE

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
Sifflet dashboard features overview
UNDERSTAND

Full Context At Your Fingertips

Everything you need to get to resolution, faster.

  • Asset Health Status
  • Documentation
Sifflet dashboard features overview
EXPLORE

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
Sifflet dashboard features overview

Reinforced %%Reliability%%

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

Data Engineers

With Sifflet’s lineage, get up to 50% of the time you spend on mundane reliability tasks back and gain insight into your data across the entire lifecycle.

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Data Leaders

Reduce data downtime and help the whole company benefit from better data quality by ensuring your teams can get to the bottom of root causes, faster.

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Data Users

Understand where your data comes from to make informed decisions and break down silos between teams.

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%%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.

Speak with our experts

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
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Frequently asked questions

Can Sifflet support SLA compliance and data governance goals?
Absolutely! Sifflet supports SLA compliance through proactive data quality monitoring and real-time metrics. Its deep metadata integrations and lineage tracking also help organizations enforce data governance policies and maintain trust across the entire data ecosystem.
How does Sifflet make it easier to manage data volume at scale?
Sifflet simplifies data volume monitoring with plug-and-play integrations, AI-powered baselining, and unified observability dashboards. It automatically detects anomalies, connects them to business impact, and provides real-time alerts. Whether you're using Snowflake, BigQuery, or Kafka, Sifflet helps you stay ahead of data reliability issues with proactive monitoring and alerting.
How did Sifflet help Meero reduce the time spent on troubleshooting data issues?
Sifflet significantly cut down Meero's troubleshooting time by enabling faster root cause analysis. With real-time alerts and automated anomaly detection, the data team was able to identify and resolve issues in minutes instead of hours, saving up to 50% of their time.
How does data quality monitoring help improve data reliability?
Data quality monitoring is essential for maintaining trust in your data. A strong observability platform should offer features like anomaly detection, data profiling, and data validation rules. These tools help identify issues early, so you can fix them before they impact downstream analytics. It’s all about making sure your data is accurate, timely, and reliable.
How does Sifflet support root cause analysis when a deviation is detected?
Sifflet combines distribution deviation monitoring with field-level data lineage tracking. This means when an anomaly is detected, you can quickly trace it back to the source and resolve it efficiently. It’s a huge time-saver for teams managing complex data pipeline monitoring.
What are some key features to look for in an observability platform for data?
A strong observability platform should offer data lineage tracking, real-time metrics, anomaly detection, and data freshness checks. It should also integrate with your existing tools like Airflow or Snowflake, and support alerting through Slack or webhook integrations. These capabilities help teams monitor data pipelines effectively and respond quickly to issues.
How can organizations improve data governance with modern observability tools?
Modern observability tools offer powerful features like data lineage tracking, audit logging, and schema registry integration. These capabilities help organizations improve data governance by providing transparency, enforcing data contracts, and ensuring compliance with evolving regulations like GDPR.
What makes Sifflet a more inclusive data observability platform compared to Monte Carlo?
Sifflet is designed for both technical and non-technical users, offering no-code monitors, natural-language setup, and cross-persona alerts. This means analysts, data scientists, and executives can all engage with data quality monitoring without needing engineering support, making it a truly inclusive observability platform.