Learn our proactive approach to implementing end-to-end data observability.
Adopting CI isn't enough—it’s how you implement it that matters. Learn practical strategies and tools for both beginners and advanced CI setups.
Learn best practices to safeguard data quality and unlock your data team’s velocity.
Our product expert will guide you through our demo to show you how to automate testing for every part of your workflow.
Prevent data quality issues with automated CI testing, ML-powered data monitoring, cross-databased data reconciliation, and unified column-level lineage.
At Datafold, we believe in catching data issues before they reach your stakeholders. Our shift-left approach starts data quality testing early in your pipelines, identifying and resolving problems before they become costly mistakes. Whether through automated CI testing or upstream checks on OLTP databases, Datafold helps your team stay ahead of bad data.
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Eliminate vendor overhead with Datafold's all-in-one platform for data quality testing, monitoring, observability, column-level lineage, and reconciliation. From upstream databases to production, Datafold automates testing at every step, ensuring full confidence in your data pipelines.
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Datafold is engineered to handle complex data ecosystems with ease, scaling effortlessly as your data grows. With built-in security and governance features, including precise access controls and audit trails, ensure your data remains protected and compliant, no matter the size or complexity of your pipelines.
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Accelerate your data migrations by more than 6 months using Datafold's AI-powered SQL conversion and cross-database data diffing capabilities.
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Prevent data quality incidents before they hit production with automated CI/CD testing.
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Automatically detect anomalies and resolve data quality incidents with speed.
"Datafold helps you find the hidden changes you didn't know you made to your data, helping you if they're unintended or understanding what's causing them."
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"Datafold allows real visibility into data changes before the changes are live, reducing mistakes and enabling our analysts and stakeholders to feel confident in their changes."
"You can see right off the bat whether your data quality is what you were expecting, and reviewers can see it, too. Now we’re at the rate where we’re automating code reviews, or close to it, on 100 pull requests per month. And this is just the start."
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