Data Science

by John D. Kelleher

As its name suggests, data science is fundamentally dependent on data. In its most basic form, a datum or a piece of information is an abstraction of a real-world entity (person, object, or event). The terms variable, feature, and attribute are often used interchangeably to denote an individual abstraction. Each entity is typically described by a number of attributes. For example, a book might have the following attributes: author, title, topic, genre, publisher, price, date published, word count, number of chapters, number of pages, edition, ISBN, and so on. A data set consists of the data relating to a collection of entities, with each entity described in terms of a set of attributes. In its most basic form,1 a data set is organized in an n * m data matrix called the analytics record, where n is the number of entities (rows) and m is the number of attributes (columns). In data science, the terms data set and analytics record are often used interchangeably, with the analytics record being a particular representation of a data set.