This can be understood very easily by differentiating the two words used above, Data and Science. Knowing and doing anything or everything with data is what data science is. Getting meaningful insights from raw data, making decisions is where data science is used. It has many pillars covering data analytics, machine learning (ML), deep learning (DL), natural language processing (NLP), Artificial intelligence (AI), and Big Data and a lot of other things.The core of data science is Statistics and Mathematics. While analyzing any data, one needs to build a model using statistical concepts and have to apply that model on any programming language such as Python or R.It may or may not require visualization tools to represent data and certain deployment concepts of ML, DL, or NLP. A data scientist is the one who knows all the above ideas and the several tools used in the project life cycle.