Master Data Management: Cornerstone of Explainable and Optimized ML models

A recent Accenture research on the state of machine learning (ML) in enterprises indicates 84% of C-suite executives believe they must leverage artificial intelligence (AI) to achieve their growth objectives, yet 76% report they struggle with how to scale. The key challenges in scaling ML in enterprises are availability of quality data and ability to explain ML outcomes; here we will discuss how Master Data Management (MDM) can help address these challenges. In 1959, Arthur Samuel defined machine learning as "... gives computers the ability to learn without being explicitly programmed". And how exactly is that achieved? At its core, machine learning is the application of statistical methods to uncover patterns in the training data and make predictions or decisions without being explicitly programmed.