Get migrations right the first time with our new guide on data migration best practices.
Learn strategies to mitigate risks, streamline processes, and deliver on-time and on-budget outcomes that earn stakeholder trust.
Every data migration needs a hero!
A data migration shouldnât be your villain origin story. Â Learn from the best (and worst) data migrations.
Get migrations right the first time with our new guide on data migration best practices.
Learn strategies to mitigate risks, streamline processes, and deliver on-time and on-budget outcomes that earn stakeholder trust.
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$20M to Help Data Teams Deliver Reliable Products Faster
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Data reliability made easy
Supercharging every workflow in data engineering
Proactively prevent errors from entering your data pipeline
Go from 0 to 100% test coverage of your ELT and BIÂ Code.- See how a change to the source code anywhere in your pipeline impacts the produced data, downstream columns, metrics and BI dashboards.
- Integrate into CI/CD workflow to prevent data regressions.
Be the first to know about data incidents
- With ML-based smart alerts, be the first to know when thereâs an anomaly with your data pipeline so you can inform relevant stakeholders, stay ahead of the data outages, and identify the root causes.
- Integrate into CI/CD workflow to prevent data regressions.
Find the data you can trust
- Datafold unifies search and documentation for all datasets and BI dashboards across your data platform and helps data users find relevant and trustworthy data faster and instantly assess the quality and profile of any dataset.
- Datafold automatically indexes all data in warehouses and imports descriptions and metadata from ELT tools such as Airflow and dbt, providing a single source of truth for data producers and consumers
Accelerate your move to new data stacks
- Whether youâre migrating to a new database or changing ETL tools, youâll need to know which data to migrate while also proving to your stakeholders that the migration was successful.
- Data Catalog with profiling and lineage help you identify core data vs columns or tables that can be deprecated, while Data Diff showcases exactly which rows or columns are different in the migration.
HANDLEÂ DATAÂ WITHÂ CARE
Integrations with the entire modern data stack
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Our progress would not be possible without the support of our early adopters
"Datafold makes it a lot easier to understand the impact of your change on downstream data. The tool is super easy to use and does a great job highlighting exactly where there are differences in your data in a digestible way".
Zachary Baustein
Lead Data Analyst
âDatafold's column-level lineage gives confidence in the whole system. If my stakeholders ask âwhy is this dashboard out of date?â I can answer in 25 seconds instead of digging through pull requests for hours. As a product owner, I can understand how the rest of the company makes decisions based on the data we produce. It brings data confidence and visibility to the company.â
Maura Church
Director of Data Science
âWhen everything is correct, Datafold clearly saves time on testing; but when something is wrong or thereâs an error, it saves unimaginable amounts of time that would go into finding and fixing bad data.â
Ezgi Ozcan
Product Analyst
"Datafold makes it a lot easier to understand the impact of your change on downstream data. The tool is super easy to use and does a great job highlighting exactly where there are differences in your data in a digestible way".
Dave Wallace
Sr Data Engineer
"Datafold is a game-changerâ there is so much value in actually understanding the effect of your pull request. It gives me the confidence that my code does what I expect it to do."
Josh Devlin
Analytics Engineer
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