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Going through the four previous posts, we hope that you now have a better view of what R, a powerful language for statistical computing and graphic, has to offer in our world of information. That is
– significant reduction of working time year after year for both statisticians and scientists,
– versatile capabilities to address all types of data: text, images, videos, sounds, and
– agility to adapt to any business and context: finance, political sciences, natural sciences,
All reducing drastically the risk of error which can lead to dramatic consequences.
In addition to the above let us see how R brings a source of innovation through its functioning and its community. It is difficult to disassociate these two. The wide community around R is the reason why its functionalities are under constant development. Many R packages and functionalities find their genesis in an idea or a need born in users’ minds, who then work on the development of these packages, often on a voluntary basis. Subsequently, other members of the R community contribute to the build by testing, commenting, improving or completing the packages, through add-ins, applications and functionalities.
It is through this participative and Open Source (OS) functioning that R is expanding every day with more and more powerful, varied and adaptive tools. R is like a Swiss army knife into which each user can incorporate new tools or functions in accordance with their needs and desires.
The impact of the R community on its software development is not limited to the technological development of the tool. The network of R users continues to grow thanks to the many conferences organized around the world, and this has the merit of targeting all socio-demographic and professional profiles. The number of R users is also increasing. These users return to their community and promote R through multiple and varied training, given in various formats and platforms, often voluntarily by R enthusiasts.
The multiplication of followers and users of R undoubtedly causes increased expectations concerning its functionality. We can expect that from these needs will flourish new R-tools, and still more specific innovations. The aRt of innovation!
This blog has been co-authored by Paul Majerus and Kamel Abid.
Paul Majerus is a Data analyst – Statistician at Sogeti Luxembourg.
