Predictive Analytics Using SQL for Operations Management

Abstract

Operations management uses past data and also models to try and make educated guesses of the future events. It makes decisions better, makes processes more effective and minimizes losses. Regression analysis, time series and machine are some of the most commonly used techniques. Another great point is that SQL from data prep is critical to model accuracy. Thus, all in all, the contemporary problems, such as data quality or integrated analytic model complexity, are the only serious challenges apart from numerous opportunities for improving efficiency, minimizing costs, and gaining a competitive edge with the help of predictive analytics.