Case Study: Top Healthcare Provider achieves scalable, actionable medical insights and 90% reduction in processing and storage with Pachyderm

Top Healthcare Provider Derives Actionable Medical Insights from Terabytes of Clinical Data Using Pachyderm’s Scalable, Data-Driven Machine Learning Pipelines

Top Healthcare Provider, one of the nation’s largest managed healthcare organizations, faced the challenge of extracting actionable insights from tens of millions of member records and 50+ terabytes of clinical data. Their existing Apache Airflow pipelines couldn’t scale or provide reproducible, immutable data lineage for production ML—so the team adopted Pachyderm’s machine learning data foundation to handle automation, versioning and large-scale pipeline orchestration.

Pachyderm enabled the team to partition member data into per-member objects, run parallel pipelines, and process only changed data incrementally. As a result, weekly runs dropped from processing a full 2 TB table to handling about 7.5 GB (roughly a 90% savings on incremental runs), while improving reproducibility, provenance tracking and overall scalability—delivering faster, cheaper, and more reliable ML insights for care providers.