This chapter covers
- The role of a data scientist and how it’s different from that of a software developer
- The greatest asset of a data scientist, awareness, particularly in the presence of significant uncertainties
- Prerequisites for reading this book: basic knowledge of software development and statistics
- Setting priorities for a project while keeping the big picture in mind
- Best practices: tips that can make life easier during a project
In the following pages, I introduce data science as a set of processes and concepts that act as a guide for making progress and decisions within a data-centric project. This contrasts with the view of data science as a set of statistical and software tools and the knowledge to use them, which in my experience is the far more popular perspective taken in conversations and texts on data science (see figure 1.1 for a humorous take on perspectives of data science). I don’t mean to say that these two perspectives contradict each other; they’re complementary. But to neglect one in favor of the other would be foolish, and so in this book I address the less-discussed side: process, both in practice and in thought.
