Solution by Persona

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.

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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Most catalogs go out of date the moment they’re published.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

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Frequently asked questions

What’s new in Sifflet’s data quality monitoring capabilities?

We’ve rolled out several powerful updates to help you monitor data quality more effectively. One highlight is our new referential integrity monitor, which ensures logical consistency between tables, like verifying that every order has a valid customer ID. We’ve also enhanced our Data Quality as Code framework, making it easier to scale monitor creation with templates and for-loops.

Why is data governance important when treating data as a product?

Data governance ensures that data is collected, managed, and shared responsibly, which is especially important when data is treated as a product. It helps maintain compliance with regulations and supports data quality monitoring. With proper governance in place, businesses can confidently deliver reliable and secure data products.

What is a Single Source of Truth, and why is it so hard to achieve?

A Single Source of Truth (SSOT) is a centralized repository where all organizational data is stored and accessed consistently. While it sounds ideal, achieving it is tough because different tools often measure data in unique ways, leading to multiple interpretations. Ensuring data reliability and consistency across sources is where data observability platforms like Sifflet can make a real difference.

How can I monitor the health of my ingestion pipelines?

To keep your ingestion pipelines healthy, it's best to use observability tools that offer features like pipeline health dashboards, data quality monitoring, and anomaly detection. These tools provide visibility into data flow, alert you to schema drift, and help with root cause analysis when issues arise.

What role does metadata play in a data observability platform?

Metadata provides context about your data, such as who created it, when it was modified, and how it's classified. In a data observability platform, strong metadata management enhances data discovery, supports compliance monitoring, and ensures consistent, high-quality data across systems.

How is data freshness different from latency or timeliness?

Great question! While these terms are often used interchangeably, they each mean something different. Data freshness is about how up-to-date your data is. Latency measures the delay from data generation to availability, and timeliness refers to whether that data arrives within expected time windows. Understanding these differences is key to effective data pipeline monitoring and SLA compliance.

How does Sifflet Insights help improve data quality in my BI dashboards?

Sifflet Insights integrates directly into your BI tools like Looker and Tableau, providing real-time alerts about upstream data quality issues. This ensures you always have accurate and reliable data for your reports, which is essential for maintaining data trust and improving data governance.

How does Sifflet support real-time metrics and proactive monitoring?

Sifflet’s observability platform is designed to provide real-time metrics and proactive monitoring through advanced data quality checks, anomaly detection, and custom health scores. This helps data teams catch issues before they escalate, ensuring your data products stay healthy and consistent.

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