- Posted by: DIRECT ADMISSION
- Category: Blog
A field that didn’t even exist 20 years back, Data Science is projected to grow in demand by 28% by the year 2020 (source: report by IBM). In its 2017 U.S Emerging Jobs report, LinkedIn ranked Machine Learning Engineers, Data Scientists and Big Data Engineers among the top emerging jobs (which have grown by up to 650% since 2012).
With such big growth numbers associated with it, Data Science as a field is turning many heads in the technology and business spaces.
Big Data, Data Analytics, Machine Learning and Data Scienceare the big buzzwords doing the round these days and you are bound to have heard them at least once. So what is all this hype about? What are the differences between them? And is Data Science a viable career option in India?
So let’s first understand what these fields are all about and then delve into the career opportunities, path and the skills required to be successful in this domain.
What is Data Science?
Data Science is a broad field that has data at its core, as the name suggests. This data is accumulated, arranged and analysed to examine its effect on businesses. Data scientists choose and build appropriate algorithms and models to analyze data better and uncover insights from it.
Netflix’s use of viewership data to give better movie recommendations, and Facebook’s use of past interactions to give more targetted ads to users, are all examples of data being put to use to gain a deeper level of understanding.
In this way, Data scientists are like detectives, finding patterns out of data to help businesses make smarter decisions.
They also help create the algorithms behind products and websites that make use of huge amounts of data to make recommendations. For example, Google Maps estimates your ETA based on huge amounts of data accumulated from other people on the same route using the app.
Data Scientists convert raw data into valuable information for businesses. For this, they possess knowledge in many different areas including software development, data munging, databases, mathematics, statistics, machine learning and data visualization.