Most articles and publications use the term freely, with the assumption that it is universally understood. However, data science – its methods, goals, and applications – evolve with time and technology.

Data science 25 years ago referred to gathering and cleaning datasets then applying statistical methods to that data. In 2018, data science has grown to a field that encompasses data analysis, predictive analytics, data mining, business intelligence, machine learning, and so much more.

In general, Data Science is not a single dimension, it’s like a combination of various disciplines that are focusing on analyzing data and finding the best solutions based on them.

Like a Rockstar
It is not a one thing, you do few weeks course and you become professional. It require domain expertise, decision making skills, ability to interpret results, ability to connect various dots to produce something meaningful, ability to handle mistakes and make something out of it, ability to expand technically and domain wise, ability to research data in depth, ability to play with numbers, ability not to stick on one solution - optimize again and again.
Like a Boss
These are a lot of abilities that looks easy but believe me, these come from doing work on regular basis. One has to be dedicated toward the field. Technical skills you can learn but if you want to make effective out of something. We have to understand it from starting, we must have a good knowledge on the specific domain, must know numbers-  is a bonus!