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Unified column-level lineage for your entire stack

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Column-level lineage that integrates with your data warehouse, data transformation models, and BI tools.

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Powering leading data teams
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Use cases

Your data ecosystem, unlocked

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01

Track your data from source to end application

The Datafold Data Explorer maps out detailed column-level lineage, tracing your data from source to BI dashboards, ML models, and reverse ETL syncs. Understand every step of your data’'s journey for complete transparency.

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02

Stay ahead of data quality issues with proactive impact analysis

Use column-level lineage to predict the effects of data transformation code changes on key business assets before they hit production. Debug faster and prevent downstream data quality issues.

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03

Develop transparency across all of your tools

Integrate with a variety of applications like dbt, Tableau, Hightouch, Looker, and more. Gain full visibility into how your data flows through your entire pipeline, ensuring complete and reliable data in the most important tools of your business.

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04

Access lineage in a way that works for you

Easily access metadata, use column-level lineage at scale, and more within the Datafold Data Explorer. Explore column-level lineage with the visual Data Explorer's DAG, or query it directly with the Datafold REST API.

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Integrations

Visibility for your entire stack

Explore Integrations
Datafold integrates with 50+ popular data tools
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Customers

How our customers are ensuring data quality with speed and confidence

Key metrics
100%+
data accuracy & quality KPI achievement
90%+
faster testing and code review

"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."

Zachary Baustein
Lead Product Analyst
Key metrics
3+
Hours saved during the validation process for each new model
300+
Models rebuilt and validated in Snowflake

"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."

Adam Underwood
Staff Analytics Engineer
Key metrics
200+
HOURS OF TESTING SAVED PER MONTH
20%+
increase in productivity

"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."

John Lee
Director, Product Analytics