Capture your data science knowledge, learn from successes and failures of the past and reuse existing assets for new projects.
Provide visibility and transparency to stakeholders outside the data science team and encourage cross-team communication and collaboration.
A single source of truth for understanding asset lineage : capturing how models were trained, what data sets were used, what features were created, what model version was promoted to production.