Solution by Persona

Business Teams

Data User

Take control of your decisions. Sifflet gives business users unmatched clarity and trust in their data, driving smarter actions with ease.

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Data Freshness and Reliability

Sifflet gives data users visibility into when data was last updated, and alerts when source data changes unexpectedly, so you’ll always know the status of your numbers.

Self-Service Troubleshooting

Vetting data quality has often been tough. Sifflet makes it easier and simpler to trace unusual values thanks to data lineage, and get historical context of data changes and updates.

Analysis Confidence

You’ll be able to analyze numbers with confidence thanks to knowledge of who owns and maintains different data assets and verify data accuracy before sharing insights.

Superior Insights. Check.

Sifflet makes it easier to gain strategic insights about your market, products, and customers. By ensuring the highest levels of data quality, your teams can make the best possible strategic decisions for your company, unlocking new levels of performance that help you compete in the age of AI.

Never Question Your Numbers Again.

Sifflet gives you the ultimate confidence in your data products and dashboards. By ensuring that your data is monitored and triaged night and day, you can always be sure of the freshness, accuracy, and quality of your numbers.

See Value From Day One.

Sifflet connects to hundreds of tools already in your stack and offers out-of-the-box monitors and tooling so you can start seeing value from day one.

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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How Carrefour transformed Data Quality

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Frequently asked questions

How does Sifflet help with root cause analysis and incident resolution?

Sifflet provides advanced root cause analysis through complete data lineage and AI-powered anomaly detection. This means teams can quickly trace issues across pipelines and transformations, assess business impact, and resolve incidents faster with smart, context-aware alerts.

How does Sifflet help with end-to-end data observability?

Sifflet enhances end-to-end data observability by allowing you to declare any asset in your data stack, including custom applications and scripts. This ensures full visibility into your data pipelines and supports comprehensive data lineage tracking and root cause analysis.

Can data quality monitoring alone guarantee data reliability?

Not quite. While data quality monitoring helps ensure individual datasets are accurate and consistent, data reliability goes further by ensuring your entire data system is dependable over time. That includes pipeline orchestration visibility, anomaly detection, and proactive monitoring. Pairing data quality with a robust observability platform gives you a more comprehensive approach to reliability.

How can data observability help reduce data entropy?

Data entropy refers to the chaos and disorder in modern data environments. A strong data observability platform helps reduce this by providing real-time metrics, anomaly detection, and data lineage tracking. This gives teams better visibility across their data pipelines and helps them catch issues early before they impact the business.

Can Sifflet detect unexpected values in categorical fields?

Absolutely. Sifflet’s data quality monitoring automatically flags unforeseen values in categorical fields, which is a common issue for analytics engineers. This helps prevent silent errors in your data pipelines and supports better SLA compliance across your analytics workflows.

What role does data lineage tracking play in AI compliance and governance?

Data lineage tracking is essential for understanding where your AI training data comes from and how it has been transformed. With Sifflet’s field-level lineage and Universal Integration API, you get full transparency across your data pipelines. This is crucial for meeting regulatory requirements like GDPR and the AI Act, and it strengthens your overall data governance strategy.

How is data volume different from data variety?

Great question! Data volume is about how much data you're receiving, while data variety refers to the different types and formats of data sources. For example, a sudden drop in appointment data is a volume issue, while a new file format causing schema mismatches is a variety issue. Observability tools help you monitor both dimensions to maintain healthy pipelines.

Can business users benefit from data observability too, or is it just for engineers?

Absolutely, business users benefit too! Sifflet's UI is built for both technical and non-technical teams. For example, our Chrome extension overlays on BI tools to show real-time metrics and data quality monitoring without needing to write SQL. It helps everyone from analysts to execs make decisions with confidence, knowing the data behind their dashboards is trustworthy.

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