R is a domain-specific programming language which aims to do data analysis. It has some unique features which make it very powerful. The most important arguably being the notation of vectors. These vectors allow us to perform a complex operation on a set of values in a single command. 1. It is a simple and effective programming language which has been well developed. 2. It is data analysis software. 3. It is a well-designed, easy, and effective language which has the concepts of user-defined, looping, conditional, and various I/O facilities. 4. It has a consistent and incorporated set of tools which are used for data analysis. 5. For different types of calculation on arrays, lists and vectors, R contains a suite of operators.

There are several tools available in the market to perform data analysis. Learning new languages is time taken. The data scientist can use two excellent tools, i.e., R and Python. We may not have time to learn them both at the time when we get started to learn data science. Learning statistical modeling and algorithm is more important than to learn a programming language. A programming language is used to compute and communicate our discovery.R communicate with the other languages and possibly calls Python, Java, C++. The big data world is also accessible to R. We can connect R with different databases like Spark or Hadoop. In brief, R is a great tool to investigate and explore the data. The elaborate analysis such as clustering, correlation, and data reduction are done with R.