Data collection method, device and terminal and memory medium

Abstract

The invention provides a data collection method, device and terminal and a memory medium. A data collection software development kit SDK is integrated into an application. The method comprises the steps that the data collection SDK automatically obtains operation data of the application; the data collection SDK converts obtained operation data of the application into a data file; and the data collection SDK uploads the data file to a server.

Description

technical field [0001] The present invention relates to the technical field of big data data collection, in particular to a data collection method, device, terminal and storage medium. Background technique [0002] With the development of the Internet, the collection and analysis of user behavior data plays an increasingly important role in the operation and decision-making of enterprises. [0003] At present, most of the data collection adopts the traditional data burying technology. The data burying technology needs to go through "sorting out online business, proposing burying requirements, evaluating burying schedule, technical personnel to integrate statistical codes and burying points, A series of processes such as "buried point test and acceptance"; the process is relatively complicated, the human resources are expensive, the development cycle is long, and some buried points will affect the logic of the application itself; in addition, once the product is launched, eve...

AI Technical Summary

Problems solved by technology

[0003] At present, most of the data collection adopts the traditional data burying technology. The data burying technology needs to go through "sorting out online business, proposing burying requirements, evaluating burying schedule, technical personnel to integrate statistical codes and burying points, A series of processes such as "buried point test and acceptance"; the process is relatively complicated, the human resources are expensive, the development cycle is long, and some buried points will affect the logic of the application itself; in addition, once the product is launched, even if there are missing buried points, only It can be supplemented by publishing, and the historical data cannot be traced back. It cannot flexibly meet the analysis needs of relevant analysts (such as: product managers, operations personnel, or background maintenance personnel who can obtain the authority to define indicators), and the efficiency is low.

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