The data being talked about here will be in large numbers and individuals need to use methods to clean data and then convert it into a format that can be used by the company for gaining insights. This field is not just restricted to engineers and anyone interested in the domain can take up the course.
In today’s technologically advanced world the field is gaining immense popularity across different sectors. As a result of large chunks of data being created in every nook and corner, there is a need to draw valuable insights from the same. To put it in a simpler manner, data is what is driving the present generation. Using the right kind of tools and techniques, businesses get the leverage of drawing meaningful insights.
Now that we have understood what data science caters to, we will see the various job profiles one can opt for after studying data science.
A data engineer is a person who has the responsibility of taking care of huge chunks of data. He is the one who needs to clean it, extract it and prepare it so that others can understand it too.
If you are a data analyst your sole responsibility lies in mining the data. You will have to look for patterns, trends, and relationships and then come with your inferences.
A data scientist is someone who uses various tools and techniques and comes up with compelling data insights.
If you a machine learning expert you will have to work on different machine learning algorithms like clustering, classification, regression, random forest, etc.
Data Science is majorly applied in:
Dwelling into the field of data science is not so easy as it seems to be. Before understanding the complex processes involved in the field it is essential to understand what does it simply by a data scientist and what are the qualities that a data scientist needs to possess. Some of the skills include analytical mind, statistical thinking and a problem-solving approach to things to name a few. There are others as well. They are: