Why it’s the right time to explore a career in Data Science

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My current job does not deal with data analysis. My current role is not even anywhere close to data science. I am not from an engineering background and have no experience in programming. I have no exposure to data related projects in me organization. Should I do a course in data analytics? If these are the kind of questions which you have, then you should take up an appropriate course in the exciting field of data analytics. Let’s figure out why.

To predict the future better, we need to have a decent understanding of the past. The 1700 was the era of industrial revolution which was driven by steam powered engines. Prior to that, it was the age of mechanically driven machines powered by humans or animals. In the 1800’s a breakthrough happened, the invention of electricity which replaced steam power by electric power, in most of the industries. 

People were indeed super excited about electricity. They built electric cars in the early 1900’s but it didn’t take off due to lack of appropriate battery technology. 

The first half of 1900 was the era dominated by electro-mechanical, manufacturing, construction, automobile and Petro-chemical based sectors. The mid-20th century onwards there was a lot of traction around the electronics, tele-communication and semiconductor industry which led to the evolution of the computer as we know today. The late 20th century (1980’s to 2000) was the glorious period of IT & software technology. 

Several people who had identified the above industry trends early and found themselves in the sweet spot at the right time and place have reaped humungous benefits. Every one of  these industries has a saturation point beyond which the advancements are not exponential, so is the career growth opportunities for most of the folks associated with these industries. However, the good news is that there is another booming sector revolving around DATA in the advent of this 21st century. Indeed, it’s popular known as the 4th industrial revolution (1st – Steam, 2nd – Electricity and the 3rd being semi-conductors and computers) 

This 4th industrial revolution is more about intelligent and interconnected systems. Intelligence in the context of computing depending on two major factors. 

The DATA and the analysis that needs to be carried out on the data to make an intelligent decision. The whole idea of making a system intelligent or to make an intelligent decision as an individual in context of a business, involves a gamut of activities in collecting & analysing data. It involves data collection, data cleaning, applying statistical techniques, using machine learning algorithms or deep learning techniques. There are a plethora of technologies and tools for each of the above-mentioned areas. There are already a lot of products built and delivered successfully by a few large organizations who are the pioneers in this area of work and its hard to miss them. 

The auto spell check feature when you message using your phones, voice enabled search features in your smart phones and Alexa like devices, google maps,  google search engine, recommendation systems when you shop through e-commerce sites like Amazon, song and movie recommendations which pop up in your systems  through services like Netflix, YouTube, Amazon Prime Video etc. All of these are heavily based on data analysis. This whole saga of playing around with data systematically is popularly known as DATA SCIENCE.  

Irrespective of what is your nature of work, if you are a knowledge worker, you need to be data savvy. Apart from the major giants like Google, Microsoft, Amazon, Yahoo, IBM etc a lot more organizations are investing in building capabilities around data science and actively looking to hire the right candidates who is data smart. According to a report published by Forbes, the industry spending around AI is going to be close to 75 billion dollars by 2022. If you are someone who would want to catapult your career growth, looking for a career  transition into data science, a fresher looking for a job or a candidate in a management position who is most likely going to build or manage a team of data scientists, you should consider exploring this field of data science and the best way to go about it is by enrolling in a course which suits your profile.