MS Machine Language Server for Enterprise-Grade Analytics

R Server is dead! Long live Machine Learning Server! The introduction of Microsoft R Server with SQL Server 2016 was tremendously exciting for data scientists and analysts working with “Big Data”. When SQL Server 2017 was released, many were shocked to see that R Server was gone. They were, however, relieved to discover that R […]
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Querying SQL Server Data from R Using RODBC

In the previous blog, we looked at some of the annoyances encountered when installing RODBC on Linux. Of course, RODBC can also be used in R running on Windows. In either case, running queries using RODBC is straightforward and without surprises. As is always the case, the first thing we need to do is connect. […]
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Creating a Web Service in R

R is a powerful language and environment for statistical computing. It excels at crunching data and performing complex modeling. In application development, its strength is in creating the “back end” components. Shiny Server allows R developers to create web applications using R. It provides R functions to create pretty sophisticated user interfaces and link them […]
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Why You Must Manage Packages in R—and How to Do It

Reproducibility is a critical component of data science. In fact, it’s critical to all research—witness the reproducibility crisis currently engulfing academic research. It equally important in software development. We all expect our applications to work the same way…time after time. Software that operates erratically is undesirable. The unyielding regularly with which computers perform tasks could […]
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SQL Server 2016: Parallel Processing for R Server with MPI Part 2

Part 2: Parallel Processing with Microsoft R Server and MPI In Part 1 we saw how to configure a server with Microsoft R Server to make use of the Rmpi library to achieve parallel processing. In Part 2, we will look at how to launch R Server processes on multiple machines creating a flexible R […]
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