Data abnormal fluctuations detecting method and apparatus
A detection method and data anomaly technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of low accuracy, reduce the efficiency of locating the cause of abnormal data fluctuations, and difficult to locate, so as to improve the accuracy degree of effect
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Embodiment 1
[0023] figure 1 It is a flow chart of the method for detecting abnormal data fluctuations provided by Embodiment 1 of the present invention. The method of this embodiment can be executed by a device for detecting abnormal data fluctuations, which can be implemented by hardware and / or software. The device can Built into the server as part of it.
[0024] like figure 1 As shown, the abnormal data fluctuation detection method provided by the embodiment of the present invention specifically includes:
[0025] S101. Acquire data to be detected, where the data to be detected includes at least one index data.
[0026] The data to be detected in this embodiment may be various report data, for example, key performance indicator (KeyPerformance Indicators, KPI) data, various business data, and the like. Specifically, the data to be detected may be acquired from a database. The index data is the data generated by dividing the data representing different attributes in the data to be d...
Embodiment 2
[0037] figure 2 It is a flow chart of the method for detecting abnormal data fluctuations provided by the second embodiment of the present invention. On the basis of the above-mentioned embodiments, this embodiment preferably determines at least one of the at least one index data according to the preset data fluctuation detection method. The specific optimization of an abnormal fluctuation index data is as follows: obtaining the chain-month fluctuation amount and the year-on-year fluctuation amount of each index data in the at least one index data, the chain-link fluctuation amount is the range of change between today's value and yesterday's value of the index data, and the The year-on-year fluctuation is the change range between today’s value of the index data and the corresponding daily value of last week; according to the chain-month fluctuation and year-on-year fluctuation of each index data, as well as the chain-month setting range and year-on-year setting corresponding t...
Embodiment 3
[0064] Image 6 A schematic flow chart of the logic flow of abnormal data fluctuation detection provided by Embodiment 3 of the present invention is given. This embodiment is optimized on the basis of the foregoing embodiments, and a preferred embodiment is provided. Please refer to the foregoing embodiments for technical details not described in detail in this embodiment. like Image 6 As shown, the abnormal data fluctuation detection logic flow provided by this embodiment includes:
[0065] S601. Acquire data to be detected 61, where the data to be detected 61 includes at least one index data;
[0066] S602. Detect the at least one index data according to the preset data abnormal fluctuation detection method 62, and determine at least one abnormal fluctuation index data in the at least one index data;
[0067] S603. Based on the decision tree model 631 or hybrid online analysis and processing model 632 based on the abnormal fluctuation index data, a corresponding index ab...
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