lakeFS Acquires DVC, Uniting Data Version Control Pioneers to Accelerate AI-Ready Data
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Overview of lakeFS
Metadata Search
Transform how you discover and audit data with versioned metadata search that brings reproducibility to collaborative and ML-driven environments.
Discover Data Fast, Audit with Confidence
Quickly locate relevant data using flexible filters like annotations, object size, and timestamps. Audit metadata tags to detect sensitive data (like PII) and ensure proper labeling for internal policies and compliance requirements.
Debug and Trace Data Lineage
Filter and inspect data using metadata like workflow ID or publish time to trace lineage, debug pipeline issues, and understand how data was created – all within a specific lakeFS version.
Search Both System and User-Defined Metadata
Query both automatically captured properties (object path, size, last modified time) and custom annotations, labels, or tags.
Built for Your Existing Stack
Search using any Iceberg compatible query engine such as DuckDB, PyIceberg, Spark, Trino, and others.
With lakeFS, we have streamlined data science and MLOps workflows, adapted data access controls for different data teams, accelerated productivity and reduced time-to-insights for ML engineering projects.
Leonard Aukea Head of Machine Learning Engineering & Operations 
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