We produce 2.5 quintillion bytes of data every single day showing no intention of slowing down. We’ve produced 90% of the entire data pool in just the past 10 years!
As we are diving even deeper into IoT (Internet of Things) technologies, Big Data rises to an entirely different level through automation of data collection. There’s but one question left – who’ll analyze it all?
There simply isn’t enough talent as of now. The industry is more than willing to pay top dollar for qualified data scientists, analysts, and architects, and yet there’s still a shortage of people.
Bizarrely enough, becoming a professional in the field isn’t even that hard. All you have to do is to dive into the fascinating world of programming.
I don’t do “programming”. I can’t do “programming”.
If these are the thoughts that bobbed up in your head, don’t worry. You are not alone.
Here’s the thing – programming is not rocket science. You can pick up the gist of it in but a couple of weeks. And with programming languages like R (the staple in the industry of Big data analysis) being ones of the most simple programming languages to learn, the sky is the limit!
According to HBR, Data Science is the sexiest career of the century. What’s really amazing about it is that, while made possible by the world of ever-advancing technology, it does not require any technical skills whatsoever. Many Data Analysts rely on tools as simple as Microsoft Excel or Google Analytics.
That said, no one says Data Scientists can’t pick up programming. Many of them rely on their coding skills to save time and automate statistical analysis.
The lion’s share of Data Scientists use R, a programming language designed to perform statistical analysis with figures and graphs.
The journey ahead
The internet is an awesome place. Remember the part about 2.5 quintillion bytes being uploaded on a daily basis?
Yes, the lion’s share of it is cat or food pics, but there’s also a lot of knowledge available online for free. There is a wide selection of online courses on practically everything, and programming is not an exception.
The Data Analysis with R course by Facebook will teach you the basics of R in as little as 6 simple lessons absolutely free of charge. The tools you’ll need in your journey such as R itself and the R studio won’t cost you a dime as well.
That said, there is a resource you’ll need in order to master R that resource being your own personal time with a sprinkle of dedication to the cause. Even then, the courses are simple and intuitive enough for you to analyze your first set of data in less than an hour after clicking the start button.
Not a walk in the park
Picking up programming nowadays is easier than ever before. Keeping up with the pace, on the other hand, now that’s a challenge. You’ll probably bash your head against the wall at least a couple of times before finding a working command.
But hey, you fell more than once when learning to walk, you failed a couple of tests on your road to graduation if you are into art your first couple of works while looking absolutely dashing on the old fridge, were technically a smoking pile of garbage.
The thing is, learning a new skill, programming or not, is always a challenge. Luckily, in the case of mastering R, everything is googleable.
“R is easy. The greatest difficulty I had was picking up enough R (and stats) lingo to be able to google for answers effectively”, says Barry Rountree, Ph.D. in Computer Science from the University of Arizona.
The world at your feet
While learning R is not the pinnacle of computer sciences it’s definitely a solid first stepping stone. Spend a couple of weeks understanding the logic behind the language, and you won’t be facing nearly as many challenges when picking up a more hardcore language like Python.
Additionally, nothing will stand between you and your prosperous career of a Data Sciences consultant – a role for which most businesses are looking to hire ASAP.
But the coolest thing about the whole deal of combining analytics and programming is that you’ll be able to do so much more than merely giving a piece of advice. You’ll learn to actually build new things.
All that in but a couple of weeks. How awesome is that?
To explore a career in Business Analytics, click here.