The discipline of data analytics and data science is seeing a huge increase in the use of the computer language R. Without a doubt, if you have the correct skill set, there are countless options in data science for you to investigate. You can work as a
- Data analyst
- Statistician
- Data scientist if you are proficient in the R language.
These are the highest paying job positions available right now. Even for people who are already working in the field of data science and want to advance their careers, a career in R is a wise decision.
We will discuss in detail regarding the programming language “R” :
- According to IEEE Spectrum’s survey, R ranks seventh among the top ten programming languages of 2018.
- It is the most sought and popular programming language that is used mainly in the data science and analytics industry, making career options in R innumerable.
- R is a free, open-source language that can be easily downloaded from the internet and run on several operating systems such as Windows, Linux, Macintosh, etc.
- R has a very vast and big community. You may have seen many seminars and boot camps being organized across the world that facilitate R education.
- R allows running various machine learning algorithms.
- Supporting data wrangling is another advantage of using R.
- The language is constantly evolving and adapting, thus making it relevant and valuable.
The following reasons are why R is a game-changer:
- Companies wishing to innovate benefit from the open-source nature of the R language. All the necessary functions for data science applications, including modeling, forecasting, and visualization, are included in R.
- R’s open-source nature is appealing and advantageous to the organization because it may be used without paying any fees or obtaining any licenses. As a result, it is easier to explore new areas because the code may be modified to suit the needs of the consumers.
- R has a history of being widely used in academics for research because it comes with a variety of analytical tools. R has risen to the top of the priority list for developers in the business sectors as a result of the constant rise in demand for data analysis.
- R is helpful for carrying out sophisticated computations because it aids in complex statistical analysis as well. Important elements like clustering, analytical models, etc. are provided. R makes it easier for data scientists to customize data collection and offer pertinent insights.
- Data manipulation is made simple by R’s built-in libraries and packages. As a result, the data science community favours it.
- Data wrangling makes the data more readable and usable by ensuring that it is compliant with the final system. In R data science tasks, it has developed into a really useful function. Using data wrangling, the data scientists can automate the data flow throughout the system.
- Companies that previously relied on legacy systems for computational and statistical analysis are increasingly switching to R due to the high demand and fierce market competition. R has so far been embraced by more than 2 million professionals worldwide.
Top companies that are using R are as follows :
- Facebook: Facebook uses R to update the social network graph and status.
- Microsoft: Microsoft’s Azure machine learning platform also makes use of R.
- Twitter: Twitter uses R to model statistical data.
- John Deere: For geospatial analysis, John Deere employs R.
- Ford Motor Company: For statistical analysis, Ford Motor Company uses R.
- Mozilla: To visualize the web activity of the Firefox web browser, Mozilla uses R.
- Amazon and Flipkart: For statistical analysis, they employ R.
- Infosys: It used R for machine learning and exploratory data analysis.
- R is used for machine learning in HCL.
- Twitter: R is used to visualize data.
