Recommended index: 8 stars.
This book covers all aspects of the work of data product managers, including the general ability of data products, the ability of complete data products, and the ability of strategic products. Data product managers in almost any direction can learn useful experience from this book. Generally speaking, it is difficult for a person's work to completely cover the whole process of data from production to application to destruction. It's great that 12 authors of this book deeply study data products in different directions and work together to contribute enough content in breadth and depth. It would be more perfect if the contents of visual reports and data applications could be added.
This book consists of 1 1 chapters, which can be roughly divided into four parts.
The first part contains chapter 1, which mainly introduces data products and related knowledge of data product managers. Including the classification of data products, the corresponding data product manager and capability model. It is helpful to introduce the recruitment interview guide for data product managers.
The second part consists of 2~3 chapters, mainly explaining the general abilities of data product managers, including data analysis and product roadmap. Data analysis is very detailed, so it is a good introductory textbook. The product roadmap does not conform to the positioning of this book, so it is of little use to junior and intermediate product managers for the time being. Just get to know it first.
The third part includes 4~9 chapters, and the main content is how to establish a complete data center, that is, data acquisition layer/governance layer/service layer/application layer. This part is the core content of this book, because the system is relatively large, and you can read it selectively according to your own work direction.
The data acquisition layer includes chapter 4, which mainly explains the buried point system. I remember reading somewhere else that the author said that application-oriented data products don't need to know the number of warehouses, so they only contain knowledge about embedding points. Personally, I think it is helpful to understand the infrastructure of data warehouse to understand the complete data flow. If you are interested, you can read other books, such as the first five chapters of Data Mining.
The data governance layer consists of 5, 6 and 8 chapters. The contents of these three chapters are all ok. In order, I think the data platform in Chapter 5 should be taken out separately and placed in front of Chapter 4, which will be better as a complete data platform. Chapter VI index system and Chapter VIII data management should be linked together.
Chapter 7 introduces how to build an A/B test system, which belongs to the application layer and should be placed behind the data service.
Chapter 9 introduces data services, mainly including API and SQL. There is nothing wrong with this piece.
The fourth part includes chapters 10 and 1 1, which mainly introduces two commonly used strategic products: search and user portrait. Just search this area. User portrait belongs to the combination of intermediate platform layer and application layer. Personally, I think it is better to introduce it in the third part first.
Personally, I think the reading order of this book should be like this:
Browse 1~3 first, and choose to skim or master according to your personal level.
Then 5, 4, 6, 1 1, 8, 9. This block contains a complete data center system.
Then there are 7 and 10, which contain data applications and strategy products respectively.
The first time I saw this book was in "Huazhang Fresh Reading", a column in which an e-book was published first and then a physical book was published. It is no exaggeration to say that I have studied the electronic version of this book at least three times. The reason is also very simple. This book is the only one on the market that basically covers the breadth and depth of the work of data product managers. The only drawback is that because it is co-authored by many people, the level is naturally high and low, so occasionally I feel a bit "theatrical". This book is worth learning by all data product managers.
PS: It is said that the author has another case collection to be published. What time? I've been waiting for a year. Hey (hide your face and cry).