What are the applications of R Programming in the Real World?

Introduction:

Both data science and big data have proved themselves to be very useful and even necessary in many different fields and industries today. With the help of big data and data science, we get to keep up with the trends and capitalize on every opportunity. R is such a tool that is used to make sense of big data and also gain use from it. With that, R has proved itself to be quite useful in research by processing large amounts of data and that too in lesser time. In this article, we aim to explore the various R applications in the real world.

Different R Applications in the real world:

Below are some of the uses of R in the real world. We are going to talk about how R is being used in different sectors and helping them boost their sectors even more.

R in Research and Academics:

As we all know that R is a statistical research tool and still used by statisticians and students to perform a variety of statistical computations and analysis. Our readers should know that statistical techniques like linear and non-linear modeling, time-series analysis, classification, classical statistic tests, clustering, and many others are all implemented by R and its libraries. Similarly, R Programming language is used for machine learning research and deep learning as well. Furthermore, R is considered to be one of the most commonly used languages for machine learning with libraries that facilitate monitored and unmonitored learning.

R in IT Sector:

IT companies not only tend to use R for their own business intelligence but offer all such services to other small, medium, and large scale businesses as well. These companies are known to have used it for their machine learning products too. Similarly, they use R to build statistical computing tools and data handling products and also create other data manipulation services. Some of the big IT companies that use R frequently are mentioned below.

• Accenture.
• IBM.
• Infosys.
• Paytm.
• Tata consultancy services.
• Wipro.

R in Finance:

When we talk about the finance sector, there is a widespread use of R and data science in this sector. R provides an advanced statistical suite for all the financial tasks and computations. Different types of tasks are easily done through R and its libraries on daily basis. This includes moving averages, auto-regression, time-series analysis, stock market modeling, financial data mining, downside risk assessment, and much more. Similarly, R is also used to support the many business decision-making processes. R’s data visualizations powers have the ability to represent the findings of data analysis in different graphical formats. This includes candlestick charts, density plots, and drawdown plots of very high quality.

R in E-Commerce:

It is surprising that analytics is quite useful for risk assessment and for devising marketing strategy in the field of finance and retail. But what is more surprising is that E-commerce goes beyond that in terms of usage of data science. The E-commerce companies tend to use R for improving the user’s experience on their site and also for marketing and finance purposes. R is used to improve the cross-product selling. To explain further, whenever a customer is buying a product, the site also suggests additional products that complement their original purchase.

R in Social Media:

The social media companies like Facebook are using R for behavior analysis and sentiment analysis. Based on the user’s history and the mood and tone of their recent posts and viewed content as well, they can alter and improve the suggestions to the users. Similarly, the advertisements which are shown to the users are also adjusted according to the user sentiment and history. Another use of R is to analyze traffic, user sessions, and content

R in Banking:

Different banking firms are using R for credit risk modeling and other forms of risk analytics. Banks also use R along with other proprietary software like SAS. With that, it is used frequently by banks to detect any type of fraud, mortgage haircut modeling, stat modeling etc. With that, it is used for volatility modeling, loan stress test simulation, client assessment, and much more. Apart from statistics, bankers tend to use R for business intelligence and data visualization. Among all the uses of R, another one is in the calculation of customer segmentation, customer quality, and customer retention.

R in Healthcare:

R has also proven to be quite helpful in healthcare department. With the help of R, you can easily crunch data and process all type of information thereby providing an essential backdrop for further analysis and data processing. There are many fields in the healthcare industry that are using R heavily. These are genetics, drug discovery, bioinformatics, epidemiology, and more. Lastly, R is very useful for pre-clinical trials for all the new drugs and medical techniques.

R in Manufacturing:

A variety of manufacturing companies are using R to complement their marketing and business strategies. They are using R to analyze customer feedback and help streamline and improve their products. Similarly, they also use data to support their marketing strategies and predict demand and market trends to adjust their manufacturing practices. Thus the use of R and data analytics in manufacturing has helped this sector a lot in boosting their business.

Conclusion:

As you can see, the use of R and data analytics in the real world has brought so much ease in a variety of industries. So, read this article today and understand what R is and how its applications are being used in the real world. And don’t forget to stay safe, stay home, and never stop learning.