Data is the foundation of data products, and buried points are the starting points of data; if there are no buried points, data products are passive water. It can be said that burying is a key and unavoidable problem encountered in the Internet industry. The following is the inner OS of the students in different positions of the enterprise: Business products: what to bury and how to bury? Data products: non-standard burial, wrong burial, omission burial; Business development: high development cost, no understanding of data, redundant code; Data analysis: The burying rules cannot be found, and the cost of data analysis is high. Business classmates don’t know what to bury, and they don’t know what to bury; so they often implement functions but don’t do burying.
When data analysis is needed, they go to the data team for data, and the data team will ask back: " Did you bury it?" For data products, because they do not have a deep understanding of the business, there are often cases of omissions and wrong burials, resulting b2b data in countless desirable results in the end. Business development, in essence, they solve business-related problems, and data development is an extra job for them, so their development costs will increase with the demand for buried points, and may also be accompanied by the risk of project delay;
Buried development requirements can also lead to code redundancy. For data analysis, they use data more, and the rules of data burying cannot be found, so that they cannot be well analyzed by data-driven. 1. What is the process of data collection? Where does the data come from Browsing track: When users use our products, they will generate a behavior path and interactive actions on the page, such as visiting a certain page, clicking a certain product, etc. The core source of these data is our buried code collection. related actions;