Scaling DS/ML for Operational Use Requires a Formalized Life-Cycle Management Methodology
Many organizations have made significant investments in their data science / machine learning (DS/ML) programs. They staffed up, invested in tools, developed pilots and proofs of concept, completed tests—and likely made some mistakes along the way. But they gained experience,…