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description=Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.;

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home dvc skip to content webinar replay end to end lineage with amazon sagemaker ai mlflow dvc watch now data version control close data version control open data version control for ai ml data infrastructure for local workflows git extension doc blog course community close community open community meet the community testimonials contribute learn events github discord get started data version control manage data the way code is managed using a git like model we bring software engineering best practices to data ai ml and data science teams data version control for ai ml and data infrastructure get started with lakefs book a demo free and open source lakefs enterprise data version control git extension for small data science projects get started with dvc dvc for vs code free and open source get vs code extension for enterprise ai and data engineering teams highly scalable data version control infrastructure designed for complex ai operations and big data environments with petabyte scale multimodal object stores and data lakes learn more about lakefs for individual datascientists the easy to use data version control git extension for small data science projects apply data version control to your data science workflows with minimal overhead learn more about dvc sep 22 virtual meetup community solution end to end lineage with amazon sagemaker ai and mlflow save your spot learn from aws experts sandeep raveesh paolo di francesco manuwai korber we re on github 15892 what s new empowering thousands of users and customers from startups to fortune 500 companies subscribe for updates we won t spam you keep updated on blog posts with our rss feed data version control for ai ml and data infrastructure for local workflows git extension about lakefs help support get started community documentation contact us community blog twitter github discord legal privacy policy privacy settings do not share or sell my personal information end to end lineage with dvc and amazon sagemaker ai mlflow apps aws solutions architects demonstrate how to build an end to end mlops workflow combining dvc for data versioning amazon sagemaker ai for scalable training and sagemaker ai mlflow apps for experiment tracking and lineage the post presents two deployable patterns dataset level lineage foundational and record level lineage healthcare compliance with individual record traceability enabling full reproducibility and audit capabilities for regulated industries jeny de figueiredo september 22 2026 17 minutes read