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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2018/08/r-python-in-sql-server.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>Did you know that you can run R and Python code within a SQL Server instance? Not only does this give you a powerful server to process your data science calculations, but it makes things faster by eliminating the need to move data between client and server. Best of all, you can access this power via your favourite interface on your local machine, like the <a rel="nofollow" href="https://www.rstudio.com/products/rstudio/" target="_blank">RStudio IDE</a> for R or the <a rel="nofollow" href="https://code.visualstudio.com/docs/languages/python" target="_blank">VS Code Python extensions</a>. </p>
<p><iframe allowfullscreen="" src="https://www.youtube.com/embed/D5erljpJDjE" width="450" height="283"></iframe></p>
<p>To make this work, all you need is the necessary functions to launch computations in SQL Server, provided in the revoscaler package for R, and the revoscalepy library for Python. The <a rel="nofollow" href="https://www.youtube.com/watch?v=D5erljpJDjE&feature=youtu.be" target="_blank">video above</a> demonstrates how to <a rel="nofollow" href="https://docs.microsoft.com/en-us/machine-learning-server/install/python-libraries-interpreter?WT.mc_id=Revolutions-blog-davidsmi" target="_blank">set things up for Python</a>, and R users should check out the tutorials <a rel="nofollow" href="https://docs.microsoft.com/en-us/sql/advanced-analytics/tutorials/sqldev-in-database-r-for-sql-developers?view=sql-server-2017&WT.mc_id=Revolutions-blog-davidsmi" target="_blank">Learn in-database analytics using R in SQL Server</a>.</p>
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