Introduction

In October 2012, the Harvard Business Review (Davenport and Patil 2012) published an article Data Scientist: The Sexiest Job of the 21st Century that is often cited as the beginning of data scientist being a term for describing a profession on the job market. The term “data scientist” had been used in various capacities prior to this, but this article mainly contributed to the role gaining mainstream recognition as a distinct profession. It has since become a highly sought-after job role in many industries due to the increasing importance and volume of data in decision-making processes. “Originally presented as a catalyst for change in management processes, it swiftly became apparent that data could enhance objectivity in decision-making. Consequently, the term ‘data science’ gained widespread popularity, leading to advocacy efforts from practitioners and researchers across various disciplines. The most significant academic initiatives came from the fields of statistics and computer science. This prompted many educational institutions to offer classes and develop curricula centered around data science. As of the writing of this book, numerous universities offer data science degrees. However, the consensus on defining the boundaries and contents of this emerging field is still in the process. Often, when data science is taught, it is typically explained through the lens of specific tools used for certain tasks. This has led to many books of the type “Using data tool XYZ to boost sales in your business.” On the other hand, there is a wealth of well-written statistics books that present the algebraic fundamentals necessary for various forms of uncertainty modeling.