Data Science is a set of specialized disciplines from various fields that analyze data and find optimal solutions. Previously, only mathematical statistics and applied mathematics addressed this; later, machine learning and artificial intelligence were adopted, adding computer science to the data analysis toolkit alongside mathematical statistics.
By analyzing large volumes of data, it becomes possible to make managerial decisions more effectively. The benefits of data analysis can be derived in virtually any applied field where sufficient data is available. To understand how to apply data analysis to a particular domain, one must have expertise in that domain.
Data science encompasses three distinct but overlapping areas:
- the skills of a mathematical statistician who can model datasets and extract the essential information from them;
- the skills of a computer scientist who can design and use algorithms for the efficient storage, processing, and visualization of data;
- domain expertise acquired through traditional study of the subject — the ability both to formulate the right questions and to examine the answers in the appropriate context.
With this in mind, I would recommend viewing data science not as a new field of knowledge to be studied, but as a new set of skills to apply within a domain you already know well.