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Developing new visualizations and analytics using R: Why Microsoft Dynamics users should get familiar

by Mark Anderson
Contributing Writer,

On the Power BI desktop, the letter "R" appears as one of the standard Visualization buttons. And though it may seem like some obscure, easily passed over feature, it's actually the most powerful choice on the Visualizations menu.

R Project logo

R is a statistics, analytics, and numerical processing and visualization language that Microsoft has been aggressively promoting in Power BI, SQL Server, Azure, and by extension the larger ecosystem of technology relevant to Microsoft Dynamics ERP and CRM systems.

R started as a data scientist's language, all but unknown to the business software world, says David Eldersveld, a senior solution consultant at BlueGranite in Michigan who also writes about data analysis and visualization. But these days business power-users and enterprise solutions providers are losing out if they ignore this language.

"It's not a domain-specific language," Eldersveld says. "A lot of people say it's just about advanced analytics. Or it's just about machine learning. Or what-have-you. But that just scratches the surface of what you can do with R...You've seen across the board an ecosystem develop around data cleansing, data wrangling, data visualization. It's something that over the past year or two has become more applicable to a traditional business intelligence audience in addition to a data science audience."

In other words, Dynamics users who invest in the larger ecosystem of Microsoft programs - Power BI in particular - might want to know more about the new world of data analysis and visualization that R enables.

Visualize more powerfully

The fact that ...

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About Mark Anderson

Mark Anderson is a science and technology journalist, author and copywriter. Based in western Massachusetts, he's written for many top publications and about everything from IT to genomics to energy. He recently launched a business copywriting service and is the author of two nonfiction books about science, history and literature.

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