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Home > Blogs > Why R will Remain Indispensable to Big Data Professionals?
Made especially for statistical analysis and graphical computations, R is a software environment that is indispensable to the world of data science today. Created by Robert Gentleman and Ross Ithaca from New Zealand, R is used widely in numerous fields with supporting operating systems such as macOS, Windows, and Linux.
The importance of R lies in its uniqueness when compared to other languages. It makes R significant in the field of data science and statistical analytics.
Multiple functions/calculations possible through a single vector
Being a vector language, R has the capability of handling many functions at once. This is what makes it stand out from other languages. It is possible to pile on additional functions to a single vector without having to put it in a loop; making R far more efficient compared to other languages.
Ability to run a code without a compiler
Unlike other programming languages like C or Java, with R it is possible to run your code sans compilers. Usually, a compiler has to interpret instructional steps from the code to run it. Whereas with R being an interpreted language, it is possible to interpret the code into a complete program, making the code development a simple task.
There are plenty of online courses, training programs, professional courses and part-time courses that focus on programming languages and R. As it is indispensable to Big Data, R is an extremely relevant and useful programming language to learn today.
Data science support
Whether they are graphs, charts, statistical functions or data interface, R helps with all of these data science functions. It is also supremely efficient when it comes to statistical analysis.
Why is R important to data science professionals?
- Owing to its versatility in the area of statistics, R is indispensable to data science applications. Whether it is a close analysis of data or distributed computing, R is widely efficient.
- Data scientists frequently use R as a data analysis software, for methods such as predictive modeling, visualization and statistical analysis.
- Since a large section of new research concerning statistical analytics is done through R, it not only provides easy implementation of new techniques, but also serves as an ideal environment for statistical analysis.
- Since R is a technology that is open source, it can be easily integrated with other applications.
- R is equipped with highly efficient tools that deliver supremely effective data visualization. From custom designed graphics to graphs and bar charts, the quality and efficiency of R is unparalleled when it comes to visualization.
- R is sophisticatedly user-friendly, lending it a devoted user base. Its online support is not only consistent, but prompt and effective too.
- One of the major reasons for the popularity of R is that it has no license restrictions. It can be run from any place at any time.
- With spectacular graphical capabilities and a fully developed environment for statistical analysis, R as a programming language is versatile, effective, and most of all, extensive.
If you are enthusiastic about creating a ripple in the world of big data analytics, you should consider pursuing big data courses or big data certification programs, which include R programming. Big data training and big data tutorials are also beneficial in giving you an edge in the job market. So why not join a course on Big Data and R through Manipal ProLearn to stay ahead of the curve?
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