Modern Data Governance Starts with Observability

Data Governance Leader

You’re not just checking compliance boxes. You’re enabling safe, scalable data use across the organization. Sifflet gives governance leaders full visibility, control, and automation, so policies stick, risks shrink, and data stays trusted no matter how fast things move.

Stronger Compliance, Less Manual Work

Automated cataloging, lineage, and audit trails make it easier to meet regulatory requirements without drowning in spreadsheets or manual updates. Sifflet keeps your governance up to date and always inspection-ready.

Fewer Blind Spots Across the Data Stack

With Sifflet, governance teams get full visibility across ingestion, transformation, and consumption, including shadow data and undocumented assets. You can finally govern what’s actually in use, not just what’s documented.

Governance That Scales With the Business

Sifflet integrates directly into your data workflows, so policies and controls scale alongside your teams and infrastructure. Whether you're onboarding new domains or expanding your stack, governance stays aligned and under control.

A Catalog That’s Actually Alive

Most catalogs go out of date the moment they’re published. Sifflet’s catalog is powered by automated metadata ingestion across your full stack: Snowflake, Databricks, dbt, Tableau, and more. You get real-time visibility into schema changes, freshness, usage, and ownership. No more chasing people for updates. No more flying blind.

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Lineage That Goes Beyond Tables

Sifflet provides deep, column-level lineage with full context, not just technical dependencies, but business impact. You can trace an issue from a broken pipeline to a downstream dashboard, and instantly see which KPIs, reports, or teams are affected. This makes policy enforcement, impact analysis, and root-cause resolution fast and reliable.

Governance Built Into the Workflow

Sifflet turns governance from a reactive process into a built-in feature of everyday data ops. You can tag sensitive assets, certify trusted datasets, monitor for violations, and set up alerts, all from inside the platform. No need to bolt governance onto the side. It’s already baked in, and it scales with your data.

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

Data Governance: a Thought Leader Perspective

Data Quality is one of the core pillars of a successful Data Governance Strategy, find out more about it with Dan Power, Thought Leader and MD in Data Governance at State Street Asset Management.

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What is Data Governance? A Reminder

Discover how data governance offers value beyond compliance: what it is, why it matters, and best practices for implementation.

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Frequently asked questions

Can I use the Fivetran integration to monitor data pipeline health?

Absolutely! By surfacing connector statuses and metadata directly in the lineage graph and catalog, Sifflet helps you stay on top of pipeline health and detect issues early. It's a powerful step forward in proactive data pipeline monitoring.

What does 'observability culture' mean at Adaptavist?

For Adaptavist, observability culture means going beyond tools. It's about clear ownership of alerts, integrating data quality monitoring into sprints, and giving stakeholders ways to provide feedback directly in dashboards. They even track observability metrics to continuously improve their own observability practices.

How does Sifflet help with SLA compliance for business metrics?

By combining real-time metrics monitoring with proactive alerts and incident management workflows, Sifflet helps teams stay on top of SLA compliance. Users can track metrics freshness, detect anomalies, and take action before SLA breaches occur.

Why is data lineage tracking essential for modern data teams?

Data lineage tracking is key to understanding how data flows through your systems. It helps teams trace anomalies back to their source, identify downstream dependencies, and improve collaboration across departments. This visibility is crucial for maintaining data pipeline monitoring and SLA compliance.

What kind of visibility does Sifflet provide for Airflow DAGs?

Sifflet offers a clear view of DAG run statuses and their potential impact on the rest of your data pipeline. Combined with data lineage tracking, it gives you full transparency, making root cause analysis and incident response much easier.

How does Sifflet support data lineage tracking and context enrichment?

Sifflet enhances your data catalog with lineage tracking and context by incorporating dbt model descriptions, input-output dataset views, and AI-powered recommendations. This enrichment helps users quickly understand where data comes from and how it's used, making it easier to trust and leverage data confidently.

Can Sifflet detect anomalies in my data pipelines?

Yes, it can! Sifflet uses machine learning for anomaly detection, helping you catch unexpected changes in data volume or quality. You can even label anomalies to improve the model's accuracy over time, reducing alert fatigue and improving incident response automation.

What if I use tools that aren’t natively supported by Sifflet?

No worries at all! With Sifflet’s Universal Connector API, you can integrate data from virtually any source. This flexibility means you can monitor your entire data ecosystem and maintain full visibility into your data pipeline monitoring, no matter what tools you're using.

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