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Analytics with R Programming

Naresh Yadav
published on:2019-04-08
Analytics with R Programming

Analytics 2.0 issues are radically different. Specifically, they have three features that have problems with Analytics 1.0: rely heavily on statistical methods, which work on large data and require seamless integration with Web technologies.

R is designed for statistical computing, with thousands of packages containing almost all statistical application applications available, which are fully compatible with the first feature. In fact, this may be the only way to make such a complete approach.

Consider filling R as LEGO pieces. When the problem requires a different method, just plug in a different R set. It's that simple. In addition, R can hold more data points than Excel by default. You can even write R code on low-cost parallel computers and use it in the cloud to analyze large data sets and Amazon Web Services (AWS) cases. Finally, you can easily integrate web technologies with R for web analytics applications.