Data is ubiquitous and is proliferating at a pace that no human or technology can control its rapid growth. As per the statement released by the American multinational technological giant IBM, 2.5 billion Gigabyte (GB) of data has been generated each day as on 2012. While an article posted on the globally renowned business magazine Forbes predicted that 1.7 Megabyte (MB) of new data would be produced per second by 2020 or even before. This immensely expanding data storage can be explained with an example. We make nearly 40,0000 search queries per second only on Google search engine, other search engine excluded, which makes the number of annual search queries to more than 1.2 trillion. Isn’t it unbelievable and breathtaking?
Seeing such a huge set of data expansion, it is quite evident that the field of Data is going to witness no dearth of career opportunities in near future. However, a lot of people get confused between the terms Data Science, Big Data and Data Analytics. Here, we are sharing some piece of information that will resolve this dilemma. Data Science, a field that came into the existence in this very decade, is a multidisciplinary field and an amalgamation of data mining, technology, algorithm development and software engineering. In a nutshell, it is the field that not only analyses and observes the given raw data and discovers insights, but also find the recurrence of the specific events or actions and helps decide what is best for the business. Further, Data Science helps improve business growth via its ability to mine customers’ data and transactions and create the suitable campaigns accordingly. With the technological