Here's what people are not talking about data science.

Data science or data analysis, two terms that are recklessly used these days to address anything that requires data driven results. In the past couple of years this field emerged more rapidly due to the emerging “BIG DATA”. 

WHAT IS BIG DATA?

Another term you might have already come across, to understand it fully let’s go back to the early ages of websites the time when all what a website was, some stupid corner on the internet stacked with a bunch of information, yes we are talking about “WEB-1.0”, the term used to describe the early age of web development. The feature which the then websites didn’t offered was interaction with the website, most of the websites were static, no actions were allowed other than reading. Then comes the more developed stage of the internet that is the "WEB 2.0", a whole new era of websites providing more interaction. Yes, the stage we moved to social media. Now, websites were a playground for users, they could not only just watch content but could also create and showcase it to the world.

That’s when came an exponential growth of users in social media and so a growth in user data, which became extremely beneficial for businesses, now the social media companies could target product specific customers for advertisements, development of products, multiple sale strategies and lot more. The data coming was a detailed representation of a large group of customers, how they behaves with different products in the market, what they choose, what they need everything could now be determined using their data.

NOW WHAT EXACTLY THIS DATA IS?
 This data is a collection of almost everything you do on a particular website your each click, what you like what you don't, the probability of you clicking on a piece content, and this is what these advance algorithms on Google, Facebook, YouTube, Snapchat, Twitter, Reddit and all other social media platforms do, they record this data, generate most relevant result and keep you engage over their platforms. Which is quite observable until you’re completely buried under your favorite content.

BUT CAN THIS DATA BE ONLY USED FOR SOCIAL MEDIA TO PROVIDE USERS WITH MOST RELEVANT CONTENT OR ADVERTISING THE TARGETED CUSTOMERS?

No, almost every field require data analysis like weather predictions, customer acquisition, social media, health care, research and development and these fields may look few but when expanded they become huge, health care and research maybe a little behind in adopting the techniques but they surely have started. They say that issues like diabetes and heart problems can be significantly controlled using data driven approach. A lot of problems actually requires a data driven approach.

Now, I’m sure you all are wondering why I haven’t yet mentioned anything about A.I (Artificial Intelligence) or Machine Learning or deep learning, when it is the most popular topic around us in the field of “Data Science”, and why not, since it is the cutting edge leading technology, isn’t the idea itself amusing that a machine can think. Well yes the machine can think, it may not be similar to us fellow humans but they do think. Then why the hell I’m not saying anything about them, it is the same reason why I wrote this post, data science is mostly associated with A.I, M.L and D.L, but the truth is these are mere technologies that are enhancing the work done by data-analysts, these are the cutting edge technologies that are expected to revolutionize the process. The standard procedure we use is not sufficient enough to carry out all the operations that we require, so we use these modern techniques to simplify our work. And since these topics are so popular no one talks about the base on which the whole structure of data analysis stands. There are questions, in the real world which require smart solutions, statistics is the very tool that helps us in answering these question efficiently and find solutions to our problem.