According to the research, computer programming languages are the best choice for our latest generation career. It helps the students to provide them best job opportunities in 2023 with the highest salary amount.
Most programming languages, such as C, C++, C#, Clojure, Crystal, D, Dart, etc., are just used for general purposes. You can use them to create various types of applications.
However, other task-specific programming languages like python, Java, Javascript, Typescript, etc., are used for exhaustive tasks. These programming languages have become well-known because they do that task more efficiently.
The R programming language is included in one of the latest specialized cutting-edge tools. It is an open-source programming language. If you compare R, SAS and SPSS, and other programming languages, R language is considered the most popular. The user range of the R programming language is 250000 to over 2 million.
Many R Programming applications are used by millions of researchers, analysts, and brands such as Facebook, Google, Bing, Accenture, Wipro, etc. The applications of R are not only used by these sectors but also by e-commerce, banking, government, etc.
To learn more about the R programming language’s real-life analogies, let’s dive in depth.
What Is R Programming Language?
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R is a programming language that is used for statistical computing, data analysis, and graphics. It was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, in the mid-1990s. R provides a wide variety of statistical and graphical techniques, including linear and nonlinear modeling, time-series analysis, classical statistical tests, clustering, and others.
One of the main advantages of R is its large community of users, who contribute packages (libraries) that provide additional functionality to the language. R is open-source software, which means that the source code is available to anyone, and users are free to modify and redistribute it. This has contributed to the growth of a vibrant ecosystem of R packages and resources.
The r language is widely used in academia, industry, and government for data analysis, statistical modeling, and visualization. It is particularly popular in fields such as data science, biostatistics, finance, and social sciences.
Why learn R Programming?
Learning R programming can be beneficial for several reasons:
- Data Analysis: R is widely used for data analysis, making it a valuable skill for anyone working with data in fields such as business, finance, healthcare, social sciences, and more.
- Statistical Computing: If you’re interested in statistics or statistical computing, R provides a powerful platform with extensive libraries and functions for conducting various statistical analyses.
- Data Visualization: R offers robust tools for creating visualizations and graphical representations of data, which is essential for understanding data patterns, trends, and relationships.
- Research and Academia: Many researchers and academics use R for their data analysis and statistical computing needs. Learning R can help you excel in academic research or pursue a career in academia.
- Data Science and Machine Learning: R is widely used in the field of data science and machine learning. It offers numerous packages and tools for implementing machine learning algorithms, making it a valuable skill for data scientists and machine learning engineers.
- Open Source Community: R has a vibrant and supportive open-source community. Learning R allows you to connect with other users, share knowledge, and contribute to open-source projects.
Career Opportunities: Proficiency in R programming can open up various career opportunities in industries such as finance, healthcare, consulting, research, government, and technology.
Applications of r programming Language
Let’s begin from the opening and examine the uses of the Applications of R for research purposes:
1. Applications Of R in research and academics
R is a statistical research tool. Statisticians and students use it to perform various statistical calculations and analyses. Statistical techniques such as linear and non-linear modeling, time-series analysis, classical statistical testing, clustering, classification, and others are implemented by R and its libraries.
It is used for deep learning and machine learning research. R is one of the best commonly used languages for machine learning, with libraries facilitating supervised and unsupervised learning.
Other research involving large data sets, such as detecting genetic anomalies and patterns and different drug compositions all use the applications of R to sift through a large collection of relevant data and draw meaningful conclusions from it.
Applications Of R cases in academics and research
- Cornell University: Cornell recommends its researchers and students use R for all their research involving statistical computing.
- UCLA: California university, Los Angeles, uses R to teach data analysis and statistics to its students.
Apart from research, R has applications in IT companies.
2. R in the IT sector
IT companies use applications of R for their business intelligence and provide such services to other small, medium, and large-scale businesses. They also use it for their machine-learning products.
They use R to build data handling products and statistical computing tools and create other data manipulation services.
Some big IT companies that use R:
- IBM
- Accenture
- Paytm
- Infosys
- Tata consultancy services
- Wipro
R Programming languages use cases in IT Sectors
- Mozilla: it uses R to visualize web activity for its browser, firefox.
- Microsoft: with the azure machine learning platform, Microsoft employs R as a statistical engine. Xbox matchmaking system uses Microsoft.
- Foursquare: R contributes to foursquare’s recommendation system from behind the scenes.
- Google: Google uses r to improve search results, provide better search suggestions, assess the ROI of advertising campaigns, increase the efficiency of online advertising, and forecast economic activity.
3. R in finance
Other than the finance sector, which industry would deal more with statistics because R is a statistical programming language?
The banking industry makes extensive use of R and data science. For all financial operations and computations, R includes a comprehensive statistical suite. R and its libraries simplify moving averages, auto-regression, time-series analysis, stock-market modeling, financial data mining, and downside risk assessment.
R is also used to aid in the decision-making process in the corporate world. R’s data visualization capabilities can display the results of data analysis in various graphical representations, including high-quality candlestick charts, density plots, and drawdown plots.
This makes it easier for business people to understand the technical aspects of data analysis and the findings. American Express, JP Morgan, bajaj allianz insurance, and standard chartered are among the companies that employ R.
R uses cases in finance
- Lloyds of London: Lloyds of London uses R for risk analysis
- Bajaj Allianz insurance: Bajaj Allianz use R to create propensity models and recommendation engines. They also employ technology to mine data and provide actionable insights to improve customer service.
The digital revolution has dramatically changed the globe. The fact that marketplaces have shifted to the internet is one of the most noticeable developments. R is widely used in the e-commerce business for a variety of applications.
4. R in e-commerce
Analytics is helpful in the banking and retail industries for risk assessment and developing marketing strategies in terms of data science, e-commerce experience, and marketing and financing. They employ R to boost cross-product sales. When a customer buys a thing, the site suggests other items that will go well with their original purchase. These suggestions are also applicable to previous purchases made by the customer. Companies that operate on the internet, such as e-commerce sites, collect and process structured and unstructured data from various sources. R shows to be handy in this situation.
R is also used in marketing planning, targeted advertising, sales modeling, and financial data processing, among other things.
R use case in e-commerce
- Amazon: to boost cross-product recommendations, amazon uses R and data analysis.
- Flipkart: Flipkart used R to perform predictive analysis, which aids in the creation of targeted marketing.
Today, the most prevalent source of big data is social media. As a result, the social media business is home to the most advanced and cutting-edge data science applications.
5. Applications Of R in social media
Social media businesses user like Facebook for sentiment analysis and behavior analysis. They can change and improve their recommendations based on the user’s history and the mood and tone of their recent postings and viewed content. The advertising shown to the user is also changed based on the sentiment and history of the user. To improve user experience, R is also used to analyze traffic, user sessions, and content.
R use cases in social media
- Facebook: Facebook utilizes R To predict coworker interactions and update its social network graph.
- Twitter: Twitter uses r to perform semantic clustering. They also utilize it to visualize data.
The banking industry is another one that makes extensive use of R’s statistical calculation capabilities.
6. Applications Of R in banking
Banks use R for credit risk modeling and other risk analytics. R is frequently used in banks, along with other proprietary tools such as SAS. It’s also used for fraud detection, mortgage haircut modeling, statistical modeling, volatility modeling, loan stress test simulation, and client assessment, among other things.
Customer segmentation, customer quality, and customer retention are all calculated using R.
R use cases in banking
- ANZ: R is used by ANZ bank for credit risk modeling as well as mortgage loss models.
- Bank of America: r is used by bank of America for financial reporting and calculating financial losses.
When it comes to cutting-edge innovations, the healthcare business is not one to be left behind.
7. R is healthcare
You can crunch data and process information with R, which serves as a foundation for additional analysis and data processing. R is widely used in the healthcare industry in domains like genetics, drug discovery, bioinformatics, epidemiology, etc. It is used to assess and predict the spread of various diseases and assess genetic sequences, drug-safety data, and numerous combinations and permutations of medications and chemicals. The Bioconductor package in R allows you to analyze genomic data. Finally, r is a godsend for all preclinical drug and medical method trials.
R uses cases in healthcare
- Merck: for clinical studies and medication testing, Merck & co. Employ the R programming language.
Manufacturing organizations also use r to make big data and stay ahead of the competition.
8. Applications Of R in manufacturing
Several industrial companies use R to supplement their marketing and commercial strategies. Customer feedback is analyzed to assist and improve their goods. They also utilize the information to help them plan their marketing campaigns. Another application of R and data analytics is predicting demand and market trends to adjust manufacturing methods.
R use case in manufacturing
- Ford motor company: Ford employs R to support its business strategy and monitor client sentiment about its products, which aids in developing future designs.
- John deere: R is used by john deere to estimate demand for its goods and spare parts. They also utilize it to anticipate crop yields and apply that information in their business plan and satisfy market demand and weather downturns.
Every government must deal with a vast amount of information. A country’s worth of data! Many government agencies also use R throughout the world.
9. Applications Of R in governmental use
Many government departments use r for record-keeping and census processing.
This aids them in enacting successful legislation and government. They also use it for critical services like drug regulation, weather forecasting, and disaster effect analysis, among other things.
R use case in government activities
- Food and drug administration: the FDA uses r to evaluate drugs and conduct preclinical trials. It also employs R to forecast potential reactions and medical problems by particular foods.
- National weather service: R is used by the national weather service to forecast weather and anticipate disasters. They also utilize it to display and analyze the areas affected by their forecasts and projection.
Which Companies Highly Use The Applications Of R Languages & Why Use It?
The following are the best companies in the world that now use the R programming language for analytics in 2023.
Companies That Use Applications of R | Who Uses The Applications Of R In These Companies? | Why do these Companies Use Applications of R Programming Language? |
1. Google | Analytical consultant, data scientist, cloud AI engineer | Exploratory data analysis, machine learning |
2. Deloitte Consulting | Backend developer, Data visualization developer, data scientist | Exploratory data analysis and machine learning |
3. Novartis | Senior data scientist, exploratory data analyst and Senior principal real-world evidence (RWE) research analyst | Statistical analysis, exploratory data analysis, machine learning, |
4. Snapdeal | Product analyst, data scientist | Machine learning, statistical analysis |
5. Amazon | Research scientist II, senior data scientist, transportation analyst | Exploratory data analysis, statistical analysis, machine learning |
6. Accenture | R programming application developer, data scientist, full stack developer, etc. | Exploratory data analysis, appplications software development, statistical analysis, etc. |
7. Cognizant | Data scientist, data engineer, data analyst | Exploratory data analysis, statistical analysis |
8. HCL Technologies | Technical lead, data scientist | Machine learning |
9. Infosys | Data science consultant, data science | Machine learning, exploratory data analysis |
10. Meta Platforms | People data solutions analyst, Data Scientist, Data science manager | Statistical analysis, exploratory data analysis |
Advantages of R Programming Language
R is a versatile programming language widely used for statistical computing, data analysis, and graphical representation of data. Its advantages include:
1. Open Source
R is an open-source language, which means it’s freely available for anyone to use, modify, and distribute. This fosters a vibrant community of developers who contribute to its growth and improvement.
2. Extensive Libraries
R boasts a vast collection of packages and libraries tailored for various statistical analyses, machine learning algorithms, data visualization, and more. These libraries make it easy to implement complex statistical methods and algorithms without having to reinvent the wheel.
3. Statistical Analysis
R was specifically designed for statistical analysis, making it exceptionally well-suited for tasks such as hypothesis testing, regression analysis, time-series analysis, clustering, and more. It offers a wide range of statistical functions and methods, making it a preferred choice for statisticians and data scientists.
4. Data Visualization
R provides powerful tools for data visualization, including the ggplot2 package, which offers a flexible and intuitive system for creating a wide variety of plots and graphics. With R, you can easily generate high-quality plots to explore and communicate your data effectively.
5. Integration with Other Languages
R can be seamlessly integrated with other programming languages such as Python, Java, and C++, allowing users to leverage the strengths of each language within a single workflow. This interoperability enhances R’s flexibility and extends its capabilities.
6. Community Support
R has a large and active community of users, developers, and contributors who share their knowledge, code, and best practices through forums, mailing lists, and online resources. This extensive support network ensures that users can find help and guidance whenever they encounter challenges or have questions.
7. Reproducibility and Documentation
R promotes reproducible research through its support for literate programming, which allows users to embed code, documentation, and visualizations in a single document. This makes it easier to reproduce analyses, share results, and collaborate with others.
Conclusion
We learned about the numerous sectors and companies that use R in this essay about the applications of R. we also looked into the varied uses of R in different businesses. Then we looked at example companies that use R to meet their diverse requirements.
R was used for academic purposes and research, but times have changed, and R is now used in every area, from IT to banking to healthcare. And if you need r programming help from our experts, then contact us.
Frequently Asked Questions
What is R most commonly used for?
R is widely used in data science by data miners and statisticians for statistical software development and data analysis.
What are the practical applications of R for data analysis?
One of the best everyday use R programming language applications for business analytics is clustering, building custom data collection, and analytical models.
Why do companies still use R?
R language stands out as a statistics software due to its compatible and fast online support. But, it is a complicated programming language to learn.
Is Excel the only software used in accounting?
While Excel is widely used in accounting, there are other specialized accounting software available, such as QuickBooks and SAP.
Can Excel handle large datasets efficiently?
Yes, Excel can handle large datasets, but it may require optimization techniques to improve performance.