Search, Shop and Adopt %%Your Data%%

Everyone’s more productive when they can discover, browse, preview and adopt the data they need with confidence, all from one spot.

Sifflet dashboard features overview

Intelligent by Design

At last, a data catalog that’s smart. Powered by algorithms that make it easy to find what you’re looking for in seconds and LLM-assisted documentation and classification recommendations that can even detect PII.

Nothing But the Truth 

From a business glossary to centralized metadata, give everyone a single source of truth. And you’ll never question data accuracy, freshness or reliability thanks to built-in monitoring. 

Easy to Connect and Use

The moment you open your data catalog, it’s ready for whatever you need. Whether you’re on the product team and want to understand how churn rate is computed or a business analyst in search of the right data source, intuitive UI means everyone can collaborate.

BROWSE

Single Source of Truth 

A one-stop shop for data knowledge at your company. 

  • E2E with OOTB cataloguing and declarative
  • Maintain data documentation and classification thanks to GenAI assisted asset descriptions that can detect PII
  • Create a business glossary so everyone’s on the same page
  • Preview your data in one click
Sifflet dashboard overview
SHOP

Smart Data Assets Search

Find and adopt the data you need for your work, in record time.

  • Simplify discovery with smart data sorting algorithms
  • Segment data access for business domains
  • Use the Sifflet Insights browser extension while you work
Sifflet dashboard overview
TRUST

Built-In Monitoring

When monitoring is built in, you’ll never question data freshness, accuracy, or reliability.

  • Enable data mesh and data self-serve thanks to built-in monitoring and data asset health status
  • Enhance and assess monitoring coverage with filtering options
Sifflet dashboard overview

Reinforced %%Reliability%%

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

Data Users

Find the data you need when you need it, understand what data powers your dashboards, and make strategic recommendations and plans with confidence.

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Data Engineers

Sifflet’s catalog is embedded in a data observability platform, not the other way around. That means you are better equipped to ensure reliability and quality than with a standalone catalog.

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Data Leaders

Improve your team’s productivity by giving them back up to 40% of the time they spend looking for the right data and vetting quality and empower business owners with clean documentation.

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Drive Data Adoption Now

Sifflet makes sure your teams never question the accuracy, freshness, or quality of assets in your catalog.

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
Still have a question in mind ?
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Frequently asked questions

Can non-technical users benefit from Sifflet’s data observability platform?
Absolutely. Sifflet is designed to be accessible to everyone. With an intuitive UI and our AI Assistant, even non-technical users can set up data quality monitors, track real-time metrics, and contribute to data governance without writing a line of code.
What are some of the latest technologies integrated into Sifflet's observability tools?
We've been exploring and integrating a variety of cutting-edge technologies, including dynamic thresholding for anomaly detection, data profiling tools, and telemetry instrumentation. These tools help enhance our pipeline health dashboard and improve transparency in data pipelines.
What exactly is data observability, and how is it different from traditional data monitoring?
Great question! Data observability goes beyond traditional data monitoring by not only detecting when something breaks in your data pipelines, but also understanding why it matters. While monitoring might tell you a pipeline failed, data observability connects that failure to business impact—like whether your CFO’s dashboard is now showing outdated numbers. It's about trust, context, and actionability.
How can data observability support a Data as a Product (DaaP) strategy?
Data observability plays a crucial role in a DaaP strategy by ensuring that data is accurate, fresh, and trustworthy. With tools like Sifflet, businesses can monitor data pipelines in real time, detect anomalies, and perform root cause analysis to maintain high data quality. This helps build reliable data products that users can trust.
How does data observability support data governance and compliance?
If you're in a regulated industry or handling sensitive data, observability tools can help you stay compliant. They offer features like audit logging, data freshness checks, and schema validation, which support strong data governance and help ensure SLA compliance.
What is “data-quality-as-code”?

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

What tools can help me monitor data consistency between old and new environments?
You can use data profiling and anomaly detection tools to compare datasets before and after migration. These features are often built into modern data observability platforms and help you validate that nothing critical was lost or changed during the move.
What features should we look for in scalable data observability tools?
When evaluating observability tools, scalability is key. Look for features like real-time metrics, automated anomaly detection, incident response automation, and support for both batch data observability and streaming data monitoring. These capabilities help teams stay efficient as data volumes grow.