In the rush to learn big data, programming languages are becoming more central to solid analysis. The most popular so far has only one letter: R.
R is an open source language used for developing correlations. It is typically used with big data analysis on semi-structured data such as product reviews, images, and likes. It is powering the heart of statistics modeling, programming, and data visualization.
Because big data interest has skyrocketed, so has the interest and usage for R. A Data Informed article noted that in a survey data scientists 70% of those surveyed are using R alongside other programming languages. In fact some applications include R into their interface for more cohesive analysis.
For those professionals still learning, the good news is that there are several resources available for R programming. Here are a few resources for those who want to get acquainted with R:
R-bloggers: This blog covers a number of R programming concerns and related topics. The best aspect about the site is a community with varying aspects of the R programming language - Over 450 contributors offer their insights and best practice techniques. A job posting for R-related positions also appears on the site. Check out more at the R-bloggers site.
Deducer: Touted as an SPSS alternative, this open source interface is designed for professionals who do not have a full background in data science. The GUI is free to download at the Deducer site.
R-studio: Another free open source GUI available, R-studio is designed to make programming in R more user friendly and easier to edit.
Datacamp: Datacamp is similar to a number of online course sites - Udemy, Udacity, +Tuts - yet it focuses exclusively on data science. Datacamp provides free training on R as well as a general overview of what a data scientist is. Additional resources are also available at the Datacamp site.
Data Science Central is a great site that offers insights into current data concerns such as Hadoop and data visualization. The site offers a comprehensive summary of initial data analysis techniques using R in the page Summary of R via Data Science Central. Data for some to the explanations are also available via a zip file on the page.
Advanced R
There is an online book for more advance techniques called, strangely enough, Advanced R by Hudly Wickham. The site provides an overview of data structure and functional programming, with a special emphasis of package development.
