In recent times, the young discipline of computer science coupled with a mature one—statistics—to create a new field called "data science." But it's also a culmination of old fields that blend data analysis and software engineerings, such as decision sciences, operations research, data mining, analytics, or mathematical modeling. The discipline emerged to designate a new profession called data scientists, who are expected to make sense of the big data.

The analysis of data is related to the Information Age, which is defined by the advent of computers and the internet. It's fascinating to see how so many fields got together to create the unique discipline of data science. From early computers to the Internet of Things (IoT), every leap of technological innovation has enerated data in some form or the other. As individuals and businesses realized that user data could be traded for large sums of money; the indiscriminate collection of data became a trend for them.

The exploratory role of data scientists

The Big Data is real and is here to stay. It's an omnipresent tool that analysts use to draw knowledge and conclusions. Today, organizations collect data as an end in itself, rather than a means to achieve an end. It is independent of other characteristics that define the Information Age, gaining its role and value in the game.

There are four major types of innovations that have taken place in the history of computing: computing power, communication, and networking between computers, collection and use of big data, and statistical analysis of data. Each of these innovations took place in five stages, which are:

  • Potential problem recognition.
  • The invention of computing technologies.
  • Recognition of computing technology as a valuable resource.
  • Adoption of technology.
  • Refinement of ideas through new versions, integrations and capabilities.


A modern-day data scientists is nothing less than an explorer. He or she has must survey the landscape, take notes of the environment, and delve into unchartered realms to see what happens. They must examine anything interest they come across, think through it, learn from it, and apply their knowledge somehow.

The ubiquitous nature of data makes it possible for data scientists to identify and analyze a pre-existing data world. The wealth of data is so massive that not everyone can understand it all, thereby getting dubbed as a separate world in itself that's worth exploring.

As such, it won't be wrong to say that data is the key to most business and marketing-related answers. The method of data analysis hasn't changed, but where such studies take place certainly has. The process can surely reveal powerful insights that can improve the way individuals and businesses make major decisions today.