Software development, web development, etc. are the most common sectors where you get innumerable resources and tools to do the very same thing. In spite of the options that are already available, new tools are constantly added and the only motive behind this is to make the work of a developer highly simplified. Since different developers have different preferences, there is always a possibility that someone would prefer using something while the others would not. Data analytics is one such area where you have innumerable options to choose from and R language is one of them. When you sign up for Business Intelligence and Analytics classroom training, this would be first options you would get. However, before learning the Data Analytics with R Training Institute, understand why the developers and data analysts have a preference for the R language in comparison to the other options.
The R language came in as a replacement of SAS. Being an open source language that could be used for free and highly user-friendly option, R started to prove to be an option that changed the way how researchers carried their tasks of data analysis. The developers who use only the statistical packages can easily move to the R language as it is a great option. Right from the variety of already available algorithms to the huge online support through forums, R is believed to be the most powerful and flexible language option that you can come across.
There are a variety of advantages that you would come across when you use R instead of using some tools. Being a complete language, R can help you write codes in a way that they provide you the exact solution of the problems that you have. A lot of developers and analysts here believe that there are tools as well that can provide the same functionalities. What you should know here is that even if the difference is very minute, it still affects the way analysis is done. When you use a package, it would only be able to perform a set of tasks meant only for it but in case when you use a language, you get the freedom of working around completely newer tasks as well.
If you are aware of the concept of regression, you would know that you will have to create these new forms meant for regression and the R language would allow you to do this completely. In addition to this, it will also facilitate the way you want to do the regression of the same sort in each of the datasets or databases that you have to use for analysis.
R is vector oriented language and due to this it becomes highly popular. The simple meaning of this is that here you would be treating all the objects as a whole. Since the syntaxes are very easy, you can get your task done simply by writing a few words in the code to get desired results and make your analysis simplified.