Machine Learning for Model Infrastructure - A Complete Guide

What is the best strategy for selecting a versioning approach?

The choice of versioning strategy depends on several key factors, including the size of your datasets, the frequency of data changes, the need for reproducibility, collaboration among team members, and storage limitations. For small files, Git is often suitable; for larger datasets, DVC or Delta Lake may be more appropriate, while stream-based versioning can be used in real-time scenarios, and a full audit trail is necessary for compliance.

Hash-based versioning utilizes cryptographic hash functions (such as MD5 or SHA256) to generate unique identifiers for data versions. When data changes, the resulting hash value will differ, creating a new version. This approach offers advantages like automatic change detection, deduplication, and data integrity checks; however, it doesn't retain semantic information about the nature of those changes.