This primarily refers to the fact that notebooks can be shared to the whole org, to groups, to users, and can be limited to read/write/execute. You could argue that MLflow is also a form of collaboration, where multiple users can share an experiment to create the best model and share results. I suppose it also refers to the idea that it's a unified data platform, where the data engineering (thus data) happens in the same place as the analysis, so access to data is no problem.
