Data Analyst Development Guide

In today's data-driven world, "how to use" a model that has already been formed is usually not a problem. You can get the result with a piece of software or a few lines of programming. The problem usually lies in "when to use" the model and "what happens after it is used up". "Data Analyst Development Guide" focuses on the latter two things. "Data Analyst Development Guide" has 27 chapters in total, divided into business understanding (Chapter 1~4), indicator design (Chapter 5~7), data modeling (Chapter 8~16), value presentation (Chapter 17~19) and practical advanced chapter (Chapter 20~27). The purpose of the business understanding chapter is to enable readers to establish a correct mindset, understand data, and become familiar with the business; the indicator design chapter learns some techniques for converting data into expert data; the data modeling chapter uses R language as the computing platform to implement the entire process of data analysis; the value presentation chapter mainly discusses how to write valuable data analysis reports; and the practical advanced chapter enables readers to apply the learned thinking methods and implementation tools to solve practical problems and turn data into value through the analysis of 8 classic cases. This book can be read by technical personnel related to data science, and can also be used as a teaching material or training material for data science-related majors in colleges and universities, as well as a reference reading for data analysis enthusiasts.