Many Eyes. TableauPublic. Using R for Analyzing Loans, Portfolios and Risk: From Academic Theory to Financial Practice. Data science, machine learning, and analytics have re-defined how we look at the world. The R community plays a vital role in that transformation and the R language continues to be the de-facto choice for statistical computing, data analysis, and many machine learning scenarios. The importance of R was first recognized by the SQL Server team back in 2016 with the launch of SQL ML Services and R Server.
Over the years we have added Python to SQL ML Services in 2017 and Java support through our language extensions in 2019. Earlier this year we also announced the general availability of SQL ML Services into Azure SQL Managed Instance. SparkR, sparklyr, and PySpark are also available as part of SQL Server Big Data Clusters. With that said, much has changed in the world of data science and analytics since 2016. Today we are making the following announcements to clearly state our direction and intent for R within Azure SQL and SQL Server. Looking to the future with the R community. Public Data Sources. Data. DataMarket - Find and Understand Data — DataMarket. Find Data.