Analytics 2.0 problems are fundamentally different. Specifically, they have three characteristics that Analytics 1.0 problems don’t have: relying heavily on statistical methods, operating on big data, and requiring seamless integration with web technologies.
R is designed for statistical computing, with thousands of packages that contain the implementations of almost every available statistical methods, making it meet the first characteristic perfectly. In fact, it’s perhaps the only tool that does so in such a comprehensive fashion.
Think of R packages as Lego pieces. When a problem requires a different method, just plug in a different R package. It’s that simple. In addition, R can handle more data points than Excel by default. You can even write R code in a parallel fashion and use inexpensive commodity computers in the cloud to analyze large datasets, like Amazon Web Services (AWS) instances. Finally, you can easily integrate R with web technologies to make analytic web apps.
R training lets you learn R programming language that is deployed for varied purposes like graphics representation, statistical analysis and reporting. With this online R Programming & data analysis training you will be able to get a clear understanding of the core concepts, import data in various formats for statistical computing, data manipulation, business analytics, machine learning algorithms and data visualization. You will learn about the various functions, data structures, variables and flow of control. Learn how to go about doing R integration with Hadoop through practical R exercises.
style="color:grey;">R programming is a statistical language for Data Science specialization that is finding higher adoption rates today thanks to its extensible nature. It can be widely deployed for various applications and can be easily scaled. Taking up this R training to learn R tool will help you grab all those jobs that are being created at large companies offering very good pay scales.