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 I build custom observability dashboards using Sifflet data?
Absolutely! With Sifflet's Data Sharing, you can connect your favorite BI tools like Looker, Tableau, or Power BI to our shared tables. This lets you build tailored dashboards and reports using real-time metrics from your observability data, helping you track KPIs, monitor SLA compliance, and visualize trends across teams or domains.
How does Sifflet help with data freshness monitoring?
At Sifflet, we offer a powerful Freshness Monitor that tracks when your data arrives and alerts you if it's missing or delayed. Whether you're working with batch or streaming pipelines, our observability platform makes it easy to stay on top of data freshness and ensure your analytics stay accurate and timely.
Why is Sifflet focusing on AI agents for observability now?
With data stacks growing rapidly and teams staying the same size or shrinking, proactive monitoring is more important than ever. These AI agents bring memory, reasoning, and automation into the observability platform, helping teams scale their efforts with confidence and clarity.
How did implementing a data observability platform impact Hypebeast’s operations?
After adopting Sifflet’s observability platform, Hypebeast saw a 204% improvement in data quality, a 178% increase in data product delivery, and a 75% boost in ad hoc request speed. These gains translated into faster, more reliable insights and better collaboration across departments.
How do modern storage platforms like Snowflake and S3 support observability tools?
Modern platforms like Snowflake and Amazon S3 expose rich metadata and access patterns that observability tools can monitor. For example, Sifflet integrates with Snowflake to track schema changes, data freshness, and query patterns, while S3 integration enables us to monitor ingestion latency and file structure changes. These capabilities are key for real-time metrics and data quality monitoring.
What is data lineage and why does it matter for modern data teams?
Data lineage is the process of mapping the journey of data from its origin to its final destination, including all the transformations it undergoes. It's essential for data pipeline monitoring and root cause analysis because it helps teams quickly identify where data issues originate, saving time and reducing stress under pressure.
What role does reverse ETL play in operational analytics?
Reverse ETL bridges the gap between data teams and business users by moving data from the warehouse into tools like CRMs and marketing platforms. This enables operational analytics, where business teams can act on real-time data. To ensure this process runs smoothly, data observability dashboards can monitor for pipeline errors and enforce data validation rules.
Can historical data access really boost data consumer confidence?
Absolutely! When data consumers can see historical performance through data observability dashboards, it builds transparency and trust. They’re more likely to rely on your data if they know it’s been consistently accurate and well-maintained over time.