dvc diff or some dataset management tooling

dvc plays really well with git, but one thing that I still miss in a data version control system that I really value in source version control systems is the tooling to inspect patches. Because data should be a deterministic reproducible output from the source code, almost all important changes are found in the code history. But frequently I also want to inspect what changed in the data.

Concrete scenario: let's say that I have an input csv and a transformation script that outputs a sanitized version of that input file. Then, I make a very small change in the sanitizing strategy, and run the command again. I can see that the output file changed hash, so I know that my code indeed changed behavior. But 99.999% of the outputs data points stayed the same, just a very minor portion of the file changed.

How can I inspect the data points that changed? Or the files in a very large output directory that changed? I can't git diff those files anymore because they're ignored. I believe that this is achievable with dvc.

No files, tests, or entry points are named. Start by reviewing the existing DVC diff and dataset-management entry points, then define how users should inspect changed data points and changed files in large output directories; done should include a clear, tested way to compare those changes.