The learning of any skill has a process from shallow to deep, and data analysis is no exception. A complete knowledge system of data analysis is similar to a pyramid structure: the top layer is the cognition and business understanding of data value, the middle is the methodology of data analysis, and the bottom layer is the solution or specific operation method of data analysis. I divide the recommended books of data analysis into three sections, which is convenient for everyone to learn step by step.
Data analysis primary edition
The beginner edition is suitable for beginners of data analysis and people who have no overall concept of data analysis. It is common for fresh graduates and inexperienced career changers.
Recommended books for beginners
To put it simply, data analysis is one of the HeadFirst series published by O'Relly, which contains a large number of pictures and interesting case combinations. This book is easy to understand and vivid, which can give beginners a comprehensive understanding of the concept of analysis.
"Who says a rookie can't analyze data": This book introduces the basic methods and processes of data analysis in detail, and takes Excel forms as an example to illustrate the case. At the same time, this book also introduces the significance of data analysis in the workplace, which can help the workplace white get started quickly.
Naked statistics: The author was a scholar who pursued knowledge when he was young, and later found many places that can be applied to life from statistics. This is also the theme of this book, and it is lively and interesting to explain statistical knowledge in combination with life. It can avoid the boredom of Bayesian probability and stochastic analysis as soon as statistics are started.
There is also a similar book, Statistics Will Lie, which is widely known and helps people understand the statistical principles behind it by exposing "false digital information".
Advanced edition of data analysis
The advanced edition is aimed at the industry and requires analysts to have certain common sense and business understanding of data analysis; Suitable for website analysts, business analysts and data product managers.
Advanced recommended books
Mastering web analytics 2.0》:Analytics combines clickstream web analysis tools with qualitative data, test experiments and competitive intelligence tools, thus deducing detailed website strategy and operation layer scheme. Although this book is old, many cases of thought and flow analysis are still very enlightening. Now only second-hand books can be bought in China.
Similarly, web analytics in Action is a book about web analytics in China. Not as classic as the above, but better than the new one. Many cases and ideas are updated in time.
Simple statistics: belonging to the Headfirst series of books, it has the above-mentioned simple data analysis and helps readers to quickly understand the theoretical knowledge of statistics with interactive real-world plots.
Data Management: The author Huang Chengming explains the examples of data application in enterprises. After reading it, I benefited a lot Many examples cited in it are grounded. Although it is biased towards retail management, the road is unified and can be applied to many industries. At that time, according to the concept inside, Meituan planned to come up with data products for BD.
"MySQL will know what it will know": This is also an introductory book for me to learn SQL in those years. This is a thin booklet, which looks very fast. SQL is a cost-effective skill, simple and powerful. Any product/operation/analyst students who want to further improve their data analysis skills are advised to light up this skill point.
The first data analysis manual of Internet growth: the data analysis manual published by our company takes growth as the theme of the whole book. This manual introduces the growth methodology of Internet start-ups, the common methods of Internet data analysis (trend, transformation, retention, real-time, clustering, detailed investigation, heat map), and the applications of sub-sectors (such as SaaS, Internet finance, e-commerce, etc.). ).
Advanced edition of data analysis
High-level data analysis is more professional, such as data governance, business analysis of data combination, data visualization and so on. Of course, there are more in-depth things like data mining algorithms, which will not be blindly recommended without research.
Advanced recommended books
"Big Data": Written by Che Pinjue, former vice president of Alibaba's data, it expounds Alibaba's experience in managing data within the enterprise. The three axes of data management "save-communicate-use" and "from data operation to operational data" are well written and can be used for reference.
Lean data analysis: The advantage of this book is to divide enterprises into several major industry categories and explain the business model characteristics and analysis skills of each industry in different categories, which requires users to have high analytical ability and corresponding business knowledge.
The visual guide "The Guide to Information Graphics of The Wall Street Journal" made by the head of business analysis of The Wall Street Journal is essential and practical. I wrote a reading note "This is how the Wall Street Journal visualizes data" for your reference.
Classic Course of Data Warehouse: The information compiled by someone on the Internet is simple and clear, unlike normal data warehouse textbooks.
Of course, data analysis is a deep knowledge, and I only caught a glimpse of the tip of the iceberg. If you want to do a good job in data analysis, you must have many skills: you need to see the value of data clearly, understand the business, be familiar with the methodology of data analysis, and be proficient in the operation of data analysis software. While studying the above recommended books on data analysis, I will deepen my understanding in practice and use data to drive business and customer growth.