As you learned the essentials of predictive modeling and explored advanced predictive algorithms available in RevoScaleR package in the previous chapter, now is a good time to learn how to operationalize it. This chapter discusses how you can operationalize R Prediction models in both SQL Server 2016 and SQL Server 2017.
The idea of marrying SQL Server and machine learning is to keep analytics close to the data and eliminate costs, as well as security risks. In addition, using Microsoft R libraries helps to improve the scale and performance of your R solutions.
This chapter outlines the steps for operationalizing your R prediction models into a powerful workflow integrated in SQL Server. First, we'll discuss the concept of integrating an existing R model into SQL Server using the extensibility framework, native scoring (SQL Server 2017), and real...
