Get Started To Do Big Data Analytics And Graphics On Large Datasets Using The Open Source R Programming Language.
Every analyst knows that great analysis and insight starts with the right data. Big Data Analytics is no different from it. To build the best performance models, it is essential to get the data in the best shape before running the analytics and building out the modeling process.
What programming/ Statistics language you use for Big Data Analytics/ Data Science/ Data Mining work?
So, start by installing R and RStudio on your desktop, and good thing is both are free. RStudio is simply GUI for R commander. There are half of dozen other RIDEs/GUIs and a dozen editors with some R support, but it is advice to not try them all.
R has the feature of scripting language which makes it easy to save and rerun analyses on updated data sets.
There are R packages and functions to load data from any reasonable source, not only CSV files. We have read.table() function, you can copy and paste data tables, read and connect Excel files to R, bring in SPSS and SAS data with accessing databases.
You can skip the coding part for standard data imports, as the RStudio Import Dataset menu item will help you to generate the correct commands by looking at the data from a text file or URL.
Install R on computer and connect to data in Hadoop
In order to perform Big Data Analytics with R, use packages contributed to open source including rhdfs and rhbase. R users can directly bring data from both the HDFS file system and the HBase database subsystems in Hadoop.