Easily build data science workflows on top of your data warehouse!

Pachyderm data pipelines integrate natively with any data warehouse

As organizations migrate to using data warehouses, data science teams are being asked to leverage that data for more and varied use cases. Data scientists are quickly discovering that working with data warehouses is not as easy as it should be.

Fortunately, Pachyderm makes it easy to create flexible data science workflows on top of any data warehouse.

With seamless integration, automation and petabyte scalability Pachyderm will help your teams iterate faster and get data science workflows to production in record time. In addition, Pachyderm’s core capabilities in versioning and lineage will ensure that any data science project retains reproducibility.

Concept diagram of how Pachyderm enables data science with data in data warehouses

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Pachyderm Enables Your Team to Build Data Science Workflows on Top of Data Warehouses

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About Pachyderm

Pachyderm provides industry-leading data versioning, pipelines, and lineage that allow data science teams to automate the machine learning lifecycle and optimize their machine learning operations (MLOps).

With investment from Benchmark, Microsoft M12, and others, Pachyderm, Inc. offers a user deployed Pachyderm Enterprise Edition, a hosted SaaS Pachyderm Hub, and an open-source Pachyderm Community Edition.

Pachyderm helps customers get their ML and AI projects to market faster, lower data processing and storage costs, and supports strict data governance requirements through data-driven automation, petabyte scalability, and end-to-end reproducibility.