In their article Provost and Fawcett argue there are good reasons why it has been hard to pin down what data science is, for example data science is intricately intertwined with other key concepts also of growing importance, such as big data and data-driven decision making. Thus, for data science to serve business effectively it is important to i) understand its relationship to other important relatedconcepts and ii) to begin to identify the fundamental principles underlying data science. They conclude their article by providing, as examples, a partial list of fundamental principles underlying data science, for example, extracting useful knowledge from data to solve business problems can be treated systematically by following a process with reasonably well-defined stages.
Many major retailers apply data science throughout their businesses, from marketing to supply-chain management. Multiple firms have successfully differentiated themselves strategically with data science. Probably the broadest business applications are in marketing for tasks such as targeted marketing, online advertising, and recommendations for cross-selling. Data science can also be applied for general customer relationship management in order to analyze customer behavior in order to manage attrition and maximize expected customervalue.
Refrences: “Data Science and its relationship to Big Data and data driven decision making” Provost, F;Fawcett, T;