The ModelOps Movement: Streamlining Model Governance, Workflow Analytics, and Explainability - insideBIGDATA

The value additive gains from enterprise use cases of cognitive computing and machine learning are as manifold as they are lucrative. Organizations can employ these technologies to optimize management of distributed retail or branch locations, supply relevant recommendations for tempting cross-selling and up-selling possibilities, and process workflows more effectively--and efficiently--at scale to boost customer satisfaction. What many are beginning to realize, however, is these gains are only manifested when firms can solve the core challenges that have been caveats for statistical Artificial Intelligence: model governance, explainability, and workflow analytics. The ModelOps movement either directly or indirectly addresses each of these three potential barriers to cognitive computing success. "As a vendor, if you haven't built this into your product natively, you're in trouble," Wilde reflected about ModelOps.