Want to use Python to run ML experiments or train models on top of BigQuery?

Pachyderm data pipelines integrate seamlessly with BigQuery

ML Engineers that leverage Python are increasingly being tasked with building models on top of BigQuery, but getting BigQuery connected to data pipelines can be a highly complex and time-consuming project.

Pachyderm’s ML Pipelines for BigQuery let you use all your favorite standard python data processing libraries directly on BigQuery data. We provide out-of-the-box integration, data-driven automation, and petabyte scalability, while still ensuring full reproducibility. Our ML Pipelines for BigQuery allow your team to iterate rapidly on BigQuery data, and get your ML models to production more quickly and reliably.

Concept diagram of how Pachyderm enables Python users to access data in BigQuery

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Pachyderm Enables Your Team to Use Python with Your BigQuery Data

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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.