The data is all around us. Every electronic device that we are using is generating data. All this data is being collected by large Corporations, Research Institutes and Governments for Business, Research and Analysis purposes.
Not just today, data have always been collected in one form or another since ages. In the past, there were Government Registers, Company Registers, Survey Records, which used to collect bulk data and maintained this data manually, this process was expensive, inefficient and required a lot of effort.
Nowadays, all such data are collected simply using your electronic devices. Actually, all your electronic devices are generating data specific to you, be it your cell phone, your TV, your car, your laptop, your mobile applications, your fridge, your Social Media activities or even your washing machines. You are generating all this data every time you do something electronically. All this data is collected without you even noticing it.
The Electronic Usage is increasing at a fast pace today, a whole new range of IOT devices is being launched in the market on a regular basis. Everything is connected to the Internet now. Data is being synchronized on all devices, your social accounts know your preferences, your medical data is online, your purchase preferences are with Amazon, your search history is with Google, Your social accounts know much about your personal life. Your GPS devices know which places you often visit. In fact, social network companies now know where you are right now at this present moment, your friend circle, your family, your interests, your business. This is how powerful the electronic age is and all this data is being generated throughout the world every second.
There is a lot of opportunities that lies in all this data. In fact, data is now being hailed as the new Oil by Large Corporations. The quote straight away comes from the Silicon Valley. Without a doubt, there is immense scope in this field today.
However, all this data is available in a bulk or in unrefined form. This data is not usable unless it is refined. For this reason, we need tools to extract useful data from this bulk unrefined data. To convert this data into usable form, professions like Data Science, Data Analysis, Statistical Analysis, Data Mining and Machine Learning are implemented. These professionals help Companies and Governments to extract meaningful data that can be used for the future growth of a Company or even a Nation.
All your Data is in electronic form today, so you need Electronic tools to use this data. Traditional tools like MS Excel and SQL are no longer a viable solution for Big Data. We are talking about Gigabytes or in some cases Terabytes of data.
We need smart tools here to make this data useful. Today, programming tools like Python, SAS, MATLAB and Java are being used for Data Science. But the most powerful and most widely used tools which are actually built for dealing with Data in the first place is the Programming Language called R. R is hailed as one of the best tools for Data Science today, though it faces some tough competition with Python. R has been specifically designed to deal with high volumes of data. Basically, R is an implementation of the S programming and the syntax is highly inspired by Scheme. Ross Ihaka and Robert Gentleman created R at the University of Auckland in New Zealand. Also, R being open source is used throughout the World without any restrictions.
A lot of Large Corporations are using R heavily today, including Google, Facebook, Twitter, Airbnb etc.
Moreover, many competitions are helping online on Kaggle for Data Scientists. If you are good at data science, you can try your hand on many such courses which can be found on Kaggle. You’ll also find interesting data that can be downloaded for free from the site which you can use for testing purposes on your local computer. One such interesting data set that is available on Kaggle is for Titanic Passengers (people who survived the tragedy and the ones who didn’t). You can download this data on your computer and fetch interesting chunks of information from it.
Moreover, Indian Government regularly releases open data in the public domain. You will also find it interesting to work upon.
As per LinkedIn, Statistical Analysis and Data Mining was the second highest paid skill in 2016. The world of data science and machine learning is moving forward at a fast pace. This is actually the future and now is the right time to invest your efforts in Data Science. A Data Scientist will have many career options open to him/her and in a variety of Companies throughout the World.
Prominent Features of R
- The R language can be used for Procedural programming using functions, procedures, records, modules, and procedure calls. Classes, Objects and Generic functions can be used for OOP programming.
- Just like any other programming language, R comes with a library/packages.
- R is an interpreted language like Python and support REPL mode as well as script mode.
- R has been built from the ground up to effectively manipulate data and storage facilities.
- R allows to print the graphs for the performed analysis straightway on the computer screen.
- R has a steep learning curve, it is nowhere near Ruby, Python or Java.
- R comes with an optional IDE named RStudio.
- R comes with four inbuilt advanced data types, i.e. Vectors, Matrices, Lists, Data Frames. If you are working with any other language, you’ll probably have to create such data types yourself or use a library to mimic these types.
- R can easily deal with large volumes of data compared to other languages.
If you are looking to build your career in Data Science, R would be one of the best skills which you can acquire today.
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