![]() Most technical professionals find themselves having to support and interact with a range of technologies from both open source and commercial vendors. Part of the appeal of SQL is its availability in so many different products. ![]() SQLServer 2016 is available as a preview, but is still subject to changes before its official release. Simple-talk is filled with excellent articles that focus specifically on SQLServer. Once the details of the release are finalized, you can expect more upcoming articles that uniquely address R as implemented within SQLServer. But since the final version of SQLServer is not yet available at this time, and Simple-Talk has already covered SQL Server Access from R, this article will demonstrate open source R in RStudio using SQL with other relational databases. There is a great deal of excitement regarding Microsoft’s acquisition of Revolution Analytics that subsequently lead to R being integrated into SQLServer 2016. As you might expect, R supports the use of SQL to retrieve data from centrally located relational databases. However, several packages in R allow you to go beyond this realm and create and query ad-hoc datasets on the fly in the midst of processing and analyzing data, regardless of the data’s original source or final destination. In this article, we will look at several different approaches that involve manipulating data with SQL using various R packages. ![]() The R platform and programming language supports a vast array of data science techniq. With decades of history and over 7,000 packages available on CRAN it can be overwhelming to determine where to start. The R-Basics and Visualizing Data with R articles provide initial direction, but don’t go into much detail about how to manipulate datasets within R.įortunately, database professionals can be productive quickly in this realm by leveraging their well-honed SQL skills.
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