Productionizing Data Science Models and Data Wrangling Scripts

Abstract

The data wrangling scripts and data scoring scripts in the previous chapters work great in a self-service situation or in small shops where one person is responsible for maintaining the Power BI data models. That is because in those situations you can get away with using the personal version of the on-premises data gateway. But, the enterprise version of the on-premises data gateway is required for enterprise solutions, and it does not allow the use of R or Python scripts embedded in Power BI. Fortunately, you can overcome this limitation using a relatively new feature in SQL Server known as SQL Server Machine Learning Services (SSMLS). SSMLS is a feature of SQL Server that enables you to perform advanced data analytics inside the database via R and Python scripts that are wrapped in a special T-SQL stored procedure. Since you are able to fetch data via a stored procedure call using the on-premises data gateway, you can refactor your previously written data wrangling and data scoring scripts in Power BI to an enterprise solution by wrapping the scripts in a stored procedure.