Abstract: A range of explanation engines assist data analysts by performing feature selection over increasingly high-volume and high-dimensional data, grouping and highlighting commonalities among data points. While useful in diverse tasks such as user behavior analytics, opera- tional event processing, and root cause analysis, today’s explanation engines are designed as standalone data processing tools that do not interoperate with traditional, SQL-based analytics workflows; this limits the app...