Data Analytics is a highly trending technology in the market right now. With almost all companies making informed decisions using huge chunks of data, the demand for data analysts, data engineers and data scientists is at an all time high.
While all of that is well and good, the problem lies in selected a tool to work with this data. There are several tools in the market that can be used for analytics. These include traditional methods like SQL and Excel to modern programming techniques like R, Python and Scala. With so many tools available, how do you choose the perfect tool?
In this blog, we will discuss five of the main reasons R is the best programming language for analytics and why you should become a certified data analyst this year.
Open-Source and Cross-Platform Compatible
R, unlike most other tools, is a free, open-source software that can be used for many purposes—analytics being one of these.Adding on the fact that it has a plug-and-play nature makes it even more convenient to use. As it is an open source language and comes with no license restrictions, you can make any modifications to the source code you deem necessary for your intents and purposes.
Another huge advantage of R is run R on several operating systems and over different configurations ofsoftware and hardware. Because of its-platform compatibility, R can run seamlessly on any operating system including Windows, Mac or Linux.
This becomes even more important when your corporate is architected over one platform and your clients work on different types of systems.
Comprehensive Library and Large Community
From the get-go, R gives you access to more than 10,000 packages and millions of built-in functions catering to all types of project requirements. These packages include libraries for Data Visualization, Machine Learning, Data Manipulation, Statistical Modeling, Imputation and several others built to make an analysts job easier. In fact, you can almost always find a package that fits your requirement and can make it easier to complete your project.
In the rare case when you can’t find an existing package, you can spin up your own package and share it with the R community because of the open-source nature of this software. That brings us to the next advantage—Rhas a huge community to tap into whenever you need any kind of assistance. Collaborations, mentoring, socializing and a whole lot more is possible over this software’s community.
R contains several packages such as ggplot2, ggvis and plotlythat can help you create stunning visualizations. Unlike other software, these libraries allow you to create high definition graphs that can be used without any modifications.
As an example, the below graph is a scatter-plot created using plotly.
This functionality of R has earned it a permanent place in the pharma and medical industry for analytics.
Interactive Web Apps
It would be a developer’s greatest dream to be able to create interactive applications directly using a data analysis software. It might seem like a crazy idea, but R can do this. A package called shiny enables R to do just that. With the help of this library, you can easily create interactive web pages and multi-layered dashboard designs right from your R Console.
These shiny web apps can be hosted on any cloud service like Amazon Web Services, Microsoft Azure, Google Cloud Platform etc.
R was Built by Statisticians for Statisticians
If all that wasn’t enough, understand the fact that R was specifically built by expert statisticians. The core logic behind the language is meant for statistical analysis which makes it ideal in all sorts of business needs.
From simple regression algorithms to complex decision trees, R can handle all kinds of workflows and is easy for any data analyst to work with.
Add on the fact that this software is being using by several top companies and you will come close to understanding the perks of the analytics tool.
Top companies that are using R in the industry right now include:
- Facebook for behavioral analysis in relation to status updates and profile picture updates
- Google for advertising effectiveness and economic forecasting
- Twitter for data visualization and semantic clustering
- Ford to improve vehicle designs
The median salary of a professional skilled in R is estimated to be around $130,467 per year as reported on Indeed.com. Job roles in this domain include:
- Data Analyst
- Data Scientist
- Quantitative Analyst
- Financial Analyst
R is a programming language that is being used for analytics in almost all domains in the market right now. Its advantages make it ideal for business analytics and because of its open-source nature, you can make necessary modifications to the software to achieve your end goals. All in all, R is the perfect language for analytics.
So, what are you waiting for?
If you are looking to get into an interesting and dynamic career, upskill to data analytics using R and start your journey down this extensive domain