Thursday, 9 April 2015

Michael Learns To R : Programming for Statistics and Data Management

Doesn't matter if you are a Manager thinking about investing in R , or a programmer hoping to learn some skill or the end user. The following are the reasons why you should use R

To begin with R is an elegant and comprehensive statistical and graphical programming language.. Worldwide, millions of statisticians and data scientists use R to solve their most challenging problems in fields ranging from computational biology to quantitative marketing. R has very powerful graphing functions that the user has to spend time learning, and widely this is one of the reason why many programmers don't invest in R. However R has become the most popular language for data science and an essential tool for Finance and analytics-driven companies like Google.

Why R ?

1. Its free :

Lets state the obvious at first, Its free!. R has no license restrictions. R software environment is written primarily in C, Fortran, and R. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems. It's also open-source. So anyone can examine the source code to see exactly what it’s doing. Your bug fixing just got lot easier with that.

2. Its the leading Tool:

R is the leading tool for statistics, data analysis, and machine learning. It is more than a statistical package; it’s a programming language, so you can create your own objects, functions, and packages.

3. Compatibility- Cross Platform:

It runs on a variety of platforms including Windows, Unix and MacOS. It is popularly used on GNU/Linux, Macintosh, and Microsoft Windows, running on both 32 and 64 bit processors. ˆ

4. Integrate:

R allows you to integrate with other languages (C/C++, Java, Python) and enables you to interact with many data sources: ODBC-compliant databases (Excel, Access) and other statistical packages (SAS, Stata, SPSS, Minitab).

5. Community:

Perhaps the best of all the R is supported by a community of more than 2 million users and thousands of developers worldwide. Whether you're using R to optimise portfolios, analyse genomic sequences, or to predict component failure times, experts in every domain have made resources, applications and code available for free, online. R has over 4800 packages available from multiple repositories specialising in topics like econometrics, data mining, spatial analysis, and bio-informatics. R has active user groups where questions can be asked and are often quickly responded to, often by the very people who developed the environment

Having said these things, I have to agree there are some challenges in the journey you take with R. Like R has a steep learning curve, Documentation is sometimes patchy and terse, and impenetrable to the non-statistician and The quality of some packages is less than perfect. However R hits the home run with more advantages as one of a kind programming tool for Statics and Data Management. You may wish to have a look at Multiple Source Data : Conversation of Consolidation & OLAP - Online Analytical Processing : Resource Guide .Contact us to know more about Data Warehouse and how it can benefit your organisation. Thanks for dropping by and Have a fantastic day!


Srivatsan Aravamudan

Srivatsan Aravamudan

Design and Communication

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