Data analysis is a difficult process largely because few people candescribe exactly how to do it. It's not that there aren't any peopledoing data analysis on a regular basis. It's that the process by whichwe state a question, explore data, conduct formal modeling, interpretresults, and communicate findings, is a difficult process to generalizeand abstract. Fundamentally, data analysis is an art. It is not yetsomething that we can easily automate. Data analysts have many tools attheir disposal, from linear regression to classification trees to randomforests, and these tools have all been carefully implemented oncomputers. But ultimately, it takes a data analyst—a person—to find away to assemble all of the tools and apply them to data to answer aquestion of interest to people.This book writes down theprocess of data analysis with a minimum of technical detail. What wedescribe is not a specific "formula" for data analysis, but rather is ageneral process that can be applied in a variety of situations. Throughour extensive experience both managing data analysts and conducting ourown data analyses, we have carefully observed what produces coherentresults and what fails to produce useful insights into data. This bookis a distillation of our experience in a format that is applicable toboth practitioners and managers in data science.