Data Versioning

Data versioning is the process of managing and tracking changes to datasets over time. It allows data scientists and engineers to create, maintain, and revert to different versions of data, ensuring consistency and reproducibility in experiments and analyses. Key characteristics include the ability to store metadata, facilitate collaboration among teams, and integrate with version control systems commonly used in software development. Common use cases include tracking changes in training datasets for machine learning models, maintaining historical records for compliance, and enabling rollback to previous data states in case of errors or anomalies.