A Big Deal for Big Data? Microsoft, R and You R visualization of how the World Cup national teams are drawn from League players from around the world

A Big Deal for Big Data? Microsoft, R and You

Microsoft announced at the end of last month that it was acquiring Revolution Analytics, a commercial provider of software and services for the open source R programming language. R is focused on statistical computing and predictive analytics, which will be key to enabling Microsoft to offer customers the kinds of tools they need to make sense of big data.

Microsoft announced at the end of last month that it was acquiring Revolution Analytics, a commercial provider of software and services for the open source R programming language. R is focused on statistical computing and predictive analytics, which will be key to enabling Microsoft to offer customers the kinds of tools they need to make sense of data--big and otherwise.

“As their volumes of data continually grow, organizations of all kinds around the world--financial, manufacturing, health care, retail, research--need powerful analytical models to make data-driven decisions,” wrote Microsoft’s Joseph Sirosh, corporate vice president, Machine Learning, in a blog post. “This requires high performance computation that is ‘close’ to the data, and scales with the business’ needs over time. At the same time, companies need to reduce the data science and analytics skills gap inside their organizations, so more employees can use and benefit from R. This acquisition is part of our effort to address these customer needs.”

Indeed, when it comes to data analytics, what companies need to do and what they are capable of is often very different. How can R help Microsoft close the gap? For that matter, just what is R?

According to a whitepaper from Revolution Analytics, R is a programming language created in New Zealand in the early 1990s by the University of Aukland’s Ross Ihaka and Robert Gentleman. R, an open source descendent of the S language developed by Bell Labs, was written by statisticians for statisticians. This makes it well-suited for the increasingly complex analytics challenges companies today are facing.

Hadley Wickham of Rice University has contributed to many R packages. In the Revolution Analytics whitepaper, Wickham is quoted as saying that R is designed to help users do the kinds of things that you do most often when performing data analysis. For example, he noted in the paper, “R has data frames built into the core language. It’s such a natural structure, and it makes working with data much easier. But very few other languages have data frames built in.”

R is also known for its speed and effectiveness in generating charts and graphics from data. This is especially important as more and more people at organizations—not just data scientists and number crunchers—need to be able to make practical use of data. Data visualization helps stakeholders interpret data according to their department’s or project’s or customer’s (or whomever’s) specific needs.

“R is especially useful for generating charts and graphics, quickly and easily. The ability to create visual plots of complex data is more than just a handy trick; it’s an incredibly important step in the analysis of data because it enables you to literally 'see' the patterns and anomalies hidden within the data,” states the whitepaper.

In his blog, Sirosh says that the acquisition of Revolution Analytics will help Microsoft customers use advanced analytics on premises, in hybrid cloud platforms and on Microsoft Azure.

Microsoft has also promised its support for the “open source evolution of R and, particularly, the community of people that drives that evolution.”

Microsoft—and its customers—have a lot to gain from nurturing the active R community, which extends the capabilities of R with packages that enable specialized statistical techniques and other features.

In a post published the day the acquisition was announced, Revolution Analytics Chief Community Officer David Smith concedes that some may consider Microsoft a “strange bedfellow” for an open source company, but he goes on to note the strides Microsoft has made in embracing open source, including specific use of the R language.

“Microsoft is a big user of R,” Smith wrote. “Microsoft used R to develop the match-making capabilities of the Xbox online gaming service. It’s the tool of choice for data scientists at Microsoft, who apply machine learning to data from Bing, Azure, Office, and the Sales, Marketing and Finance departments. Microsoft support R extensively within the Azure ML framework, including the ability to experiment and operationalize workflows consisting of R scripts in MLStudio.”

Microsoft has not provided details on when the deal will close.

Have you used R? Visualizing a scale from one to 10, how big a deal is this acquisition when it comes to your big data needs? (With one being “little to none” and 10 being “it’s a game changer.”) Please let us know your thoughts in the comments section below.

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