Intelligent data processing method and system

Abstract

An intelligent data processing method includes following steps: collecting and storing operation data of product operation equipment, and analyzing and classifying; finding and providing a product solution according to the operation data after being analyzed and classified; according to the product solution, modifying a product or displaying content of the solution. The invention further providesan intelligent data processing system. A lot of time and manpower are not needed to analyze and solve problems, and the system intelligently analyzes problems from massive data and is combined with anartificial intelligence system to constantly improve solution screening ability and select an optimal solution to finally solve the problems, so that a problem solving system is formed; once restoration fails, related personnel is notified timely for solution, so that the system can constantly improve screening programs and improve problem solving level.

Description

technical field [0001] The invention belongs to the field of big data, specifically relates to the field of data collection, and is an intelligent method for a data collection platform. Background technique [0002] At present, there are many data collection platforms on the market, mainly for the collection of product client crash data, server error logs, operational data and other related data. At present, the collection platforms on the market are still stagnant in simple collection, analysis, and statistical modes, and have not yet entered the era of intelligence. These platforms only perform simple classification, statistics, and analysis of data. To solve the above problems, it still takes a lot of money The cost of manpower and time, the efficiency is relatively low, and sometimes, it takes a long time from when the program has a problem to when the program finds the problem. In many cases, when data crashes, program developers need to find the problem, then check th...

AI Technical Summary

Problems solved by technology

At present, the collection platforms on the market are still stagnant in simple collection, analysis, and statistical modes, and have not yet entered the era of intelligence. These platforms only perform simple classification, statistics, and analysis of data. To solve the above problems, it still takes a lot of money Manpower and time costs, the efficiency is relatively low, and sometimes, it takes a long time from when the program has a problem to when the program finds the problem

In many cases, when data crashes, program developers need to find the problem, then check the problem and solve the problem by themselves. When the user group is constantly losing, the developers cannot analyze the reasons in time. They can only look at a bunch of statistical charts to obtain the retention rate. Facing the reality of the continuous loss of users, they seem at a loss and do not analyze the data accurately. , for no clear reason

Furthermore, developers spend a lot of time analyzing product data. When they encounter problems and don’t know the reason, they can only guess based on experience, which is easy to get wrong results, and has a negative impact on improving the unfavorable situation of user loss.

On the other hand, due to the huge amount of crash data, error data, operation data, and other related collected data, developers cannot effectively combine these data to form an overall analysis system during manual analysis, so that they cannot be based on These analyzes make targeted repairs or improvements to the product, making it impossible for the user experience to improve quickly

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