R has become one of the most popular language for statistics, visualization and analytics in the last decade. Many companies like Facebook, Google, Ford Motor Company and millions of people Worldwide from different fields are using R language.
Facebook uses R for the analysis of status updates. All the charts used for analysis are created using ggplot2 package. Graphical powers of R is also used in Facebook’s social network graph. They also uses R to predict colleague interaction.
Google uses R to predict economic activity. It has used R to fit autoregressive models to retail sales, automotive sales, home sales, and passenger arrival data. Google also analysis data from set-top boxes, to determine the number of viewers for each ad. They are able to know how many viewers stay on-channel, versus those who switch over. This information is used to measure each ad’s effectiveness compared to a statistical model. Also it uses R to make online marketing more effective. They also R for statistical analysis and visualization, to ensure that its advertisers are always getting the best for their marketing investment.
Other than social networking sites many banks are also using R. For example ANZ bank, thefourth largest bank in Australia has used R to fit models for mortgage loss because of the flexibility of R to adapt to new modelling situations and generate predictions, summaries, etc.
In the USA, R is used in Food and Drug administration and in National weather service. National weather services uses R to forecast river flooding and other weather related predictions. It also generates graphics representing real-time hydrologic ensemble (probabilistic) forecasts.
Some other examples of the companies that uses R language are Ford Motor Company and John Deere. Ford does statistical analysis using R, while farming equipment manufacturer John Deere uses R for forecasting demand for equipment, to forecasting crop yields.
People have used R in the manufacturing field for predictive analytics for some time now. Predictive analytics plays an important part to optimize operational efficiency and to reduce risk in the manufacturing field. Usually in this field the data is of good quality so there isn’t much need of data cleaning. The main challenge lies in the data exploration and extracting the information from it. Here R is very useful due to number of tools and packages for data exploration. For example ggplot2 package is used for visual data exploration or one can use iplots package for interactive multivariate data exploration.
Another important use of R is to produce elegant and flexible reports. Knitr package in R gives dynamic and automated reports which saves time and effort. Even in the case of big data which is often time consuming to deal with, Knitr generates reports automatically. It tries to give beautiful output by default and it is fully customizable to incorporate with different types of demand.
Believe it or not, R is even used in journalism. Infact, the New York Times uses R for data visualization. It’s true, R is indeed gaining popularity because of its flexibility and it’s powerful data analysis and visualization. It is praised by established media and at the same time it has become an essential tool for companies in various sectors.
For analysts looking to make a mark in the analytics industry, remember that R is a crucial skill to have. Infact companies are more and more hiring analysts with expertise in multiple skills, so take note of how the industry is evolving and get trained in the skills in demand, to always have the edge.
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