What’s in for you?
This rich statistical analysis environment helps data scientists innovate since they can experiment quickly with a variety of hypotheses. These short iterations enable them to quickly learn what works and what doesn’t.
R is regarded as being an easy language to learn and designed for those with a background in statistics.
R is also seen as an expressive language, which makes it easier for your data scientists to concisely represent the models they’re creating — for instance, models exploring pricing elasticity or promotion effectiveness.
And because it is widely used in academia, R continues to be at the forefront of data analytics. As researchers develop innovative algorithms, they’re quickly added to R libraries.