Building Data-driven Web Applications Using R and Shiny

Shiny is a web application framework for the R statistical computing language. It allows interactive applications to be written entirely in R. While it’s possible to write a general purpose web application using R and Shiny, it’s not the sweet spot of the framework. There are better general purpose web application frameworks—such as ASP.NET MVC. […]
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Better Performance for R Functions with Vectorization

One of the best things about R is that so many talented people have contributed a multitude of  valuable packages. In fact there are so many, that for most tasks you don’t have to do any programming at all. However, there are always going to be problems that require custom treatment and that will demand […]
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Setting Memory Limits for R in SQL Server 2016

In previous blogs, we’ve looked at the potential for integrating the statistical language R into soon-to-be-released SQL Server 2016. Developers and analysts are excited about the new possibilities – the response of administrators is considerably more restrained. Administrators are a conservative lot – it’s part of their job description. When learning of a new feature […]
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Version control for data scientists using Git and RStudio

Look at the working directory of the average data science project and you’ll see things like this: cust-churn.csv cust-churn.R cust-churn-old.csv cust-churn-progess-meeting.R cust-churn-working.R cust-churn-working2.R cust-churn-20160217.R test.R test-bk.R Every time a change needs to be made, files are copied to preserve the working code. As changes will often be made to multiple files, it’s common to […]
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SQL Server 2016: R Integration Redux

SQL Server 2016 has now reached Release Candidate 3 (RC3). One of the new features that continues to foster interest in the analytics and data mining community is the integration of SQL Server with the open-source statistics toolset R. If you fall into this category, I’m inclined to suggest you remain patient and wait for […]
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