Data analysis method, electronic equipment and storage medium

Abstract

The invention relates to a data analysis method, electronic equipment and a storage medium. The method comprises: in response to a fault analysis request, obtaining fault information of a terminal device, the fault information comprising device information of the terminal device and description information of a generated fault; an analysis result corresponding to the fault information is output, the analysis result is obtained by conducting failure analysis on the fault information, and the analysis result at least comprises at least one of the fault type, the fault reason, the fault solution and the failure duration of the terminal equipment. According to the method, the analysis process is simplified, and the analysis efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of data analysis, and in particular, to a data analysis method, an electronic device, and a storage medium. Background Art

[0002] During the actual use, storage, transportation, reliability testing, etc. of a terminal device, it will be affected by various environmental stress conditions such as high temperature, electricity, and water vapor, and thus may fail. The reasons for the failure of the terminal device are complex and diverse. In order to improve the quality life of the terminal device, scientific and reasonable cause analysis is required.

[0003] In the related art, when a terminal device fails, a service outlet needs to accept the failure service of the terminal device. Then, a technician performs a failure analysis on the terminal device to determine the type of failure, the cause of the failure, and the failure solution of the terminal device. This manual failure analysis method has a relatively complex analysis process and low analysis efficiency. Summary of the Invention

[0004] To overcome the problems existing in the related art, the present disclosure provides a data analysis method, an electronic device, and a storage medium.

[0005] According to a first aspect of an embodiment of the present disclosure, a data analysis method is provided. The method includes:

[0006] In response to a failure analysis request, obtain failure information of a terminal device, where the failure information includes device information of the terminal device and description information of the generated failure;

[0007] Output an analysis result corresponding to the failure information, where the analysis result is obtained by performing a failure analysis on the failure information, and the analysis result includes at least one of at least one of the type of failure, the cause of the failure, the failure solution, and the failure duration of the terminal device.

[0008] In some embodiments, before the step of outputting the analysis result corresponding to the failure information, the method further includes:

[0009] Based on historical analysis data, perform a failure analysis on the failure information to obtain an analysis result; the historical analysis data is used to represent historical failures and the analysis results of the historical failures.

[0010] In some embodiments, the method further includes:

[0011] Perform statistics on the failure information to obtain statistical information of the failure information;

[0012] The performing a failure analysis on the failure information based on the historical analysis data to obtain an analysis result includes:

[0013] Based on the historical analysis data, perform a failure analysis on the fault information and the statistical information to obtain the analysis result.

[0014] In some embodiments, the performing a failure analysis on the fault information and the statistical information based on the historical analysis data to obtain the analysis result includes:

[0015] Based on the multi-layer architecture of the data warehouse, perform data processing on the fault information and the statistical information to obtain data to be analyzed;

[0016] Based on the historical analysis data and the data to be analyzed, perform coupling to obtain the analysis result.

[0017] In some embodiments, the multi-layer architecture includes a first data layer, a second data layer, a third data layer, a fourth data layer, and a fifth data layer. The performing data processing on the fault information and the statistical information based on the multi-layer architecture of the data warehouse to obtain data to be analyzed includes:

[0018] Based on the first data layer, obtain the fault information and the statistical information;

[0019] Based on the second data layer, perform data filtering on the fault information and the statistical information to obtain filtered fault information and filtered statistical information;

[0020] Based on the third data layer, aggregate the filtered fault information and the filtered statistical information according to multiple preset dimensions to obtain information for each preset dimension;

[0021] Based on the fourth data layer, perform data calculation on the information for each preset dimension respectively to obtain the index parameters corresponding to each preset dimension;

[0022] Based on the fifth data layer, determine the index parameters of multiple preset dimensions as the data to be analyzed.

[0023] In some embodiments, the outputting the analysis result corresponding to the fault information includes:

[0024] In response to detecting a query operation, query and output the analysis result.

[0025] In some embodiments, the method further includes:

[0026] In the case of obtaining the analysis results corresponding to multiple terminal devices of the target type, based on the analysis results corresponding to the multiple terminal devices and the activation quantity, determine the failure information corresponding to each failure type, where the activation quantity is the number of activated terminal devices among the terminal devices of the target type, and the failure information corresponding to the failure type is used to characterize the proportion of the terminal devices that have the failure of the failure type every day among the activated terminal devices, and the target type is any one of multiple device types;

[0027] Based on the failure information corresponding to each failure type, determine the failure curve corresponding to each failure type.

[0028] In some embodiments, the method further includes:

[0029] Based on the failure information corresponding to each failure type, predict the available duration of any terminal device of the target type.

[0030] According to a second aspect of the embodiments of the present disclosure, there is provided an electronic device, including

[0031] An information acquisition module, configured to obtain the failure information of the terminal device in response to a failure analysis request, where the failure information includes the device information of the terminal device and the description information of the generated failure;

[0032] A result output module, configured to output the analysis result corresponding to the failure information, where the analysis result is obtained by performing a failure analysis on the failure information, and the analysis result at least includes at least one of the failure type, failure cause, failure solution, and failure duration of the terminal device.

[0033] In some embodiments, the electronic device further includes:

[0034] A failure analysis module, configured to perform a failure analysis on the failure information based on historical analysis data to obtain an analysis result; the historical analysis data is used to characterize historical failures and the analysis results of the historical failures.

[0035] In some embodiments, the electronic device further includes:

[0036] An information statistics module, configured to perform statistics on the failure information to obtain the statistical information of the failure information;

[0037] The failure analysis module is configured to perform a failure analysis based on the failure information and the statistical information to obtain the analysis result.

[0038] In some embodiments, the failure analysis module is configured to:

[0039] Based on the multi-layer architecture of the data warehouse, data processing is performed on the fault information and the statistical information to obtain the data to be analyzed;

[0040] Based on the coupling of the historical analysis data and the data to be analyzed, the analysis result is obtained.

[0041] In some embodiments, the multi-layer architecture includes a first data layer, a second data layer, a third data layer, a third data layer, a fourth data layer, and a fifth data layer. The failure analysis module is configured to:

[0042] Based on the first data layer, obtain the fault information and the statistical information;

[0043] Based on the second data layer, perform data filtering on the fault information and the statistical information to obtain the filtered fault information and the filtered statistical information;

[0044] Based on the third data layer, aggregate the filtered fault information and the filtered statistical information according to multiple preset dimensions to obtain the information of each preset dimension;

[0045] Based on the fourth data layer, perform data calculation on the information of each preset dimension respectively to obtain the index parameters corresponding to each preset dimension;

[0046] Based on the fifth data layer, determine the index parameters of multiple preset dimensions as the data to be analyzed.

[0047] In some embodiments, the result output module is configured to query and output the analysis result in response to detecting a query operation.

[0048] In some embodiments, the electronic device further includes:

[0049] A failure information determination module, configured to, in the case of obtaining the analysis results corresponding to multiple terminal devices of a target type, determine the failure information corresponding to each fault type based on the analysis results corresponding to the multiple terminal devices and the activation quantity. The activation quantity is the number of activated terminal devices among the terminal devices of the target type. The failure information corresponding to the fault type is used to characterize the proportion of the terminal devices that generate faults of the fault type every day among the activated terminal devices. The target type is any one of multiple device types;

[0050] A failure curve determination module, configured to determine the failure curve corresponding to each fault type based on the failure information corresponding to each fault type.

[0051] In some embodiments, the electronic device further includes:

[0052] The available usage duration determination module is configured to predict the available usage duration of any terminal device of the target type based on the failure information corresponding to each type of failure.

[0053] According to a third aspect of the embodiments of the present disclosure, there is provided an electronic device, including:

[0054] A processor;

[0055] A memory for storing instructions executable by the processor;

[0056] Wherein, the processor is configured to execute the method described in the first aspect of the embodiments of the present disclosure.

[0057] According to a fourth aspect of the embodiments of the present disclosure, there is provided a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of an electronic device, enabling the electronic device to execute the method described in the first aspect of the embodiments of the present disclosure.

[0058] Adopting the above method of the present disclosure has the following beneficial effects:

[0059] For the method provided by the embodiments of the present disclosure, when a terminal device has a failure, in response to a failure analysis request, the failure information of the terminal device is obtained, the failure analysis is performed on the failure information to obtain an analysis result, and the analysis result is output. There is no need for technicians to perform analysis, realizing automatic analysis, simplifying the analysis process, and improving the analysis efficiency.

[0060] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present invention, and are used together with the specification to explain the principles of the present invention.

[0062] Figure 1 is a schematic diagram of an application scenario shown according to an exemplary embodiment;

[0063] Figure 2 is a flowchart of a data analysis method shown according to an exemplary embodiment;

[0064] Figure 3 is a flowchart of a data analysis method shown according to an exemplary embodiment;

[0065] Figure 4 is a schematic diagram of a data analysis system shown according to an exemplary embodiment;

[0066] Figure 5 It is a schematic diagram of a failure type shown according to an exemplary embodiment;

[0067] Figure 6 It is a schematic diagram of a failure curve shown according to an exemplary embodiment;

[0068] Figure 7 It is a block diagram of an electronic device shown according to an exemplary embodiment;

[0069] Figure 8 It is a block diagram of an electronic device shown according to an exemplary embodiment. Detailed implementation manners

[0070] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present invention. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0071] In the related art, when a terminal device fails, a service outlet needs to accept the failure service of the terminal device. Then, a technician performs a failure analysis on the terminal device to determine the failure type, failure cause, and failure solution of the terminal device. This manual failure analysis method has a relatively complex analysis process and low analysis efficiency.

[0072] In another related art, an analysis solution for electronic components is provided, but it fails to cover the entire terminal device and is limited to the failure analysis of some electronic components in the terminal device. Since the terminal device contains various electronic components, the terminal device usually has various types of failures, and the failure causes are more complex than those of electronic components. In the related art, the analysis solution for electronic components is not applicable to the terminal device.

[0073] The method provided by the embodiments of the present disclosure, when a terminal device fails, in response to a failure analysis request, obtains the failure information of the terminal device, performs a failure analysis on the failure information to obtain an analysis result, and outputs the analysis result, without the need for a technician to analyze, realizing automatic analysis, simplifying the analysis process, and improving the analysis efficiency.

[0074] The embodiments of the present disclosure can be applied to data analysis scenarios of various terminal devices. For example, refer to Figure 1Schematic diagram of the application scenario shown. Taking the terminal device as a mobile phone as an example, for mass-produced mobile phones, users purchase mobile phones through a sales platform, and then users activate the mobile phones. During the user's usage process, if the mobile phone does not malfunction, there is no need for after-sales service. When the mobile phone malfunctions, if the main board malfunctions, the mobile phone is returned to the repair factory through the after-sales network point. After the repair factory repairs it, the repaired mobile phone is returned to the after-sales network point, and then the after-sales network point returns it to the user. Or, the repair factory re-lists the repaired mobile phone on the sales platform. If the secondary board or other components malfunction, the after-sales network point directly repairs it and then returns it to the user. In this process, the method provided by the embodiments of the present disclosure can be used to perform failure analysis on the malfunctions that occur in the mobile phone and give the analysis results, without the need for technicians to perform manual analysis.

[0075] The method provided by the embodiments of the present disclosure is executed by an electronic device, and the electronic device can be any terminal device such as a mobile phone, a tablet computer, a laptop computer, a server, a wearable device, etc.

[0076] Figure 2 It is a flowchart of a data analysis method shown according to an exemplary embodiment, which is executed by an electronic device. Refer to Figure 2 This method includes the following steps:

[0077] Step S201, in response to a failure analysis request, obtain the failure information of the terminal device. The failure information includes the device information of the terminal device and the description information of the generated failure.

[0078] Among them, the failure analysis request is used to request an analysis of the failure generated by the terminal device. The failure analysis request can be a request generated by the electronic device in response to the user's operation. The failure information is the information generated when the terminal device malfunctions. The failure information includes the device information of the terminal device. For example, the device information includes information such as the device type, device IMEI (International Mobile Equipment Identity), device purchase date, and device activation log of the device itself. The failure information also includes the description information of the generated failure. The description information is used to describe the situation detected by the terminal device when the failure occurs. Different failures correspond to different description information. For example, when the generated failure is a software application failure, the description information may include the log information when the application program malfunctions. Or, when the generated failure is a drop failure such as a cracked screen, the description information may include the drop height recorded by the acceleration sensor when the device drops and the energy generated during the collision, etc.

[0079] Step S202: Output the analysis result corresponding to the fault information. The analysis result is obtained by performing a failure analysis on the fault information, and the analysis result includes at least one of the fault type, fault cause, fault solution, and failure duration of the terminal device.

[0080] Among them, the analysis result includes at least one of the fault type, fault cause, fault solution, and failure duration of the terminal device. Among them, the fault type refers to the type of fault to which the generated fault belongs, the fault cause refers to the reason for the fault, the fault solution refers to the solution to solve the fault, and the failure duration refers to the duration between the time point when the fault occurs and the activation time point of the terminal device. The activation time point can be the time point when the user activates the terminal device for the first time after obtaining the terminal device, or the activation time point can also be the time point when the terminal device ends the last repair.

[0081] Output the analysis result, including: displaying the analysis result, playing the analysis result by voice, or outputting the analysis result in other output forms. The embodiments of the present disclosure do not limit the output form of the analysis result.

[0082] The method provided by the embodiments of the present disclosure, when a fault occurs in the terminal device, in response to a fault analysis request, obtains the fault information of the terminal device, performs a failure analysis on the fault information to obtain an analysis result, and outputs the analysis result, without the need for technicians to analyze, realizes automatic analysis, simplifies the analysis process, and improves the analysis efficiency.

[0083] Figure 3 is a flowchart of a data analysis method shown according to an exemplary embodiment, which is executed by an electronic device. Refer to Figure 3 and the method includes the following steps:

[0084] Step S301: In response to a fault analysis request, obtain the fault information of the terminal device.

[0085] Among them, the fault analysis request is used to request an analysis of the fault generated by the terminal device. Optionally, the fault analysis request carries the fault information of the terminal device.

[0086] In some embodiments, refer to Figure 4 the schematic diagram of the data analysis system shown. Receive a fault analysis request through the after-sales service system, and in response to the fault analysis request, obtain the fault information. Among them, the fault analysis request can be a request automatically generated by the after-sales service system after detecting the fault information input by the user, or a request sent by the terminal device to the after-sales service system when the fault of the terminal device is not serious. The embodiments of the present disclosure do not limit this.

[0087] Step S302: Statistically analyze the fault information to obtain the statistical information of the fault information.

[0088] In the embodiments of the present disclosure, based on historical analysis data, failure analysis is performed on fault information to obtain an analysis result. The historical analysis data is used to characterize historical faults and the analysis results of historical faults. The historical analysis data serves as reference data for performing failure analysis, and the historical analysis data is data generated according to historical faults and the corresponding analysis results. Before performing failure analysis on the fault information, it is necessary to first process the fault information to obtain the data to be analyzed.

[0089] Among them, the statistical information is the information obtained after preliminary calculation of the fault information. According to the information specifically included in the fault information, corresponding statistics can be performed on the fault information so that the obtained statistical information is convenient for use in subsequent processing. For example, if the fault information includes the recorded drop height and the duration of the drop, the drop speed is calculated, etc. In the embodiments of the present disclosure, no limitation is imposed on the specific statistical algorithm.

[0090] In some embodiments, referring to Figure 4 the schematic diagram of the data analysis system shown in, the fault information is statistically analyzed through the quality management system to obtain statistical information. Among them, the fault information is transmitted to the quality management system through the after-sales service system.

[0091] Step S303: Based on the multi-layer architecture of the data warehouse, data processing is performed on the fault information and the statistical information to obtain the data to be analyzed.

[0092] In the embodiments of the present disclosure, a data warehouse is used to perform data processing on the fault information and the statistical information to obtain the data to be analyzed. Among them, the multi-layer architecture of the data warehouse includes a first data layer, a second data layer, a third data layer, a third data layer, a fourth data layer, and a fifth data layer. For example, referring to Figure 4 the schematic diagram of the data analysis system shown in, the first data layer is the source-attached data layer (Operational Data Store, ODS), the second data layer is the basic data layer (Operational Data Store, DWD), the third data layer is the general data layer (Operational Data Store, DWM), and the fourth data layer is the aggregated data layer (Data Mart, DM).

[0093] In some embodiments, based on the first data layer, fault information and statistical information are obtained; based on the second data layer, the fault information and statistical information are filtered to obtain filtered fault information and filtered statistical information; based on the third data layer, the filtered fault information and filtered statistical information are aggregated according to multiple preset dimensions to obtain information for each preset dimension; based on the fourth data layer, data calculations are respectively performed on the information for each preset dimension to obtain index parameters corresponding to each preset dimension; based on the fifth data layer, the index parameters of multiple preset dimensions are determined as data to be analyzed.

[0094] That is to say, the first data layer is used to obtain information from the after-sales service system and the quality management system; the second data layer is used to perform preliminary processing on the obtained information, and the preliminary processing includes data filtering, that is, screening the obtained information to remove some useless information and retain useful information; the third data layer is used to classify the filtered information into information of different preset dimensions according to preset dimensions. For example, the preset dimensions include dimensions such as time, location, and product; the fourth data layer is used to perform data processing on the information for each preset dimension to obtain an index parameter for the information of the preset dimension; the fifth data layer is used to establish a suitable data list and save the index parameters of multiple dimensions to the data list as data to be analyzed.

[0095] In some embodiments, referring to Figure 4 the schematic diagram of the data analysis system shown, the multiple architectures further include a temporary layer (TMP) and a dimension layer (Dimension, DIM). Among them, the temporary layer is used to store intermediate results generated during the data processing process or in other words, temporarily summarized data, so that when these temporary results or temporarily summarized data are needed later, they can be directly called from the temporary layer to reduce repeated calculations; the dimension layer is used to store the information for each preset dimension, and store the information for each preset dimension separately to facilitate the query of the information for each preset dimension and improve the flexibility of the query.

[0096] Step S304, coupling the historical analysis data and the data to be analyzed to obtain an analysis result.

[0097] Among them, coupling the historical analysis data and the data to be analyzed means: for multiple historical analysis data that are more than the data to be analyzed, the most coupled historical analysis data is determined from the multiple historical analysis data, and the analysis result in the most coupled historical analysis data is used as the analysis result corresponding to the data to be analyzed.

[0098] In some embodiments, referring to Figure 4Schematic diagram of the data analysis system shown. Historical analysis data is stored in the failure analysis database. After obtaining the data to be analyzed through the application data layer, the data to be analyzed is transmitted to the failure analysis database, and the analysis result is determined through this failure analysis database.

[0099] It should be noted that in the embodiments of the present disclosure, based on the historical analysis data, failure analysis is performed on the fault information and statistical information to obtain the analysis result. Step S303 takes the multi-layer architecture based on the data warehouse as an example to determine the data to be analyzed. In another embodiment, other data processing methods can also be used to process the fault information and statistical information to obtain the data to be analyzed. The embodiments of the present disclosure do not limit this.

[0100] Step S305, output the analysis result.

[0101] In some embodiments, outputting the analysis result includes two situations. One is that the electronic device directly pushes the analysis result to the user; the other is that in response to detecting a query operation, the analysis result is queried and output. That is to say, after the electronic device obtains the analysis result, it can directly push it to the user, or it can also push the analysis result to the user when the user queries.

[0102] Optionally, outputting the analysis result includes: displaying the analysis result, realizing the visualization of business data by displaying the analysis result, which is convenient for the user to view the analysis result; or, playing the analysis result by voice; or, outputting the analysis result in other output forms.

[0103] In some embodiments, the analysis result is displayed through a display interface. Optionally, referring to Figure 4 Schematic diagram of the data analysis system shown. The display interface is a BI (Business Intelligence) visualization tool dashboard. The BI visualization tool dashboard is customized according to the analysis result to be displayed. Multiple dimensions of results can be displayed through this BI visualization tool dashboard for hierarchical interactive drilling. For example, the device type, fault type, fault cause, fault solution, and failure duration are respectively displayed, etc., to achieve linkage cross-analysis and facilitate positioning of the failure cause.

[0104] The method provided by the embodiments of the present disclosure, when a terminal device fails, obtains the fault information of the terminal device, and then based on the historical analysis data, performs failure analysis on the fault information, and the analysis result can be obtained. There is no need for technicians to analyze, and automatic analysis can be realized based on the historical analysis data, which simplifies the analysis process and improves the analysis efficiency. Moreover, by displaying the analysis result, the whole process from after-sales work order entry to after-sales work order data processing and then to after-sales problem index analysis is realized to be online, visual, analyzable, monitorable, and warnable.

[0105] The above Figure 3 is a description of the process of obtaining the analysis result corresponding to a certain terminal device for that terminal device.

[0106] In some embodiments, for multiple terminal devices, according to the failure duration corresponding to different failures, they can be divided into different failure types. For example, referring to Figure 5 the schematic diagram of the failure types shown, the failure types include early failure, accidental failure, and wear-out failure. The failure duration corresponding to early failure is short, and the failure rate (hazard rate) is high; the failure duration corresponding to accidental failure is moderate, and the failure rate is low; the failure duration corresponding to wear-out failure is long, and the failure rate is high. Optionally, after obtaining the analysis result corresponding to the terminal device, the failure type corresponding to the current failure of the terminal device can be determined according to this analysis result.

[0107] In some embodiments, when adopting the Figure 3 embodiment shown above, after obtaining the analysis results corresponding to multiple terminal devices, the life prediction of the terminal devices can also be performed based on the analysis results corresponding to the multiple terminal devices. Before performing the life prediction, it is necessary to first calculate the failure rate.

[0108] In an example, refer to the number of faulty machines generated per day shown in Table 1 below:

[0109] Table 1

[0110]

[0111]

[0112] In Table 1, the date in the horizontal row refers to the usage date, and the date in the vertical row refers to the activation date. The value is the number of faulty machines generated. As shown in Table 1, 100 devices were activated on January 3. Then, the number of faulty machines generated on January 3 was 2, on January 4 was 1, on January 5 was 3, on January 6 was 1, on January 7 was 2, on January 8 was 2. The same applies to the devices activated on subsequent dates and will not be elaborated here. Based on the data in Table 1, the failure rate of the devices can be calculated in sequence. For example,

[0113] The failure rate for users using the device for 1 day is: (2 + 2 + 1 + 2 + 2 + 3) / (100 + 110 + 120 + 100 + 130 + 150) = 1.7%

[0114] The failure rate for users using the device for 2 days is: (1 + 4 + 2 + 3 + 2) / (100 + 110 + 120 + 100 + 130) = 2.1%

[0115] The failure rate for users using the device for 3 days is: (3 + 2 + 2 + 3) / (100 + 110 + 120 + 100) = 2.3%

[0116] The calculation of the subsequent failure rates will not be listed here. From the failure rates for usage from 1 - 3 days, it can be seen that the longer the usage, the higher the failure rate. That is to say, the longer the device is used, the greater the likelihood of failure.

[0117] In one example, the number of faulty devices produced each day in Table 1 above can also be represented as the number of devices returned with different failure durations as shown in Table 2 below:

[0118] Table 2

[0119]

[0120] In Table 2, the date in the horizontal row refers to the usage date, the date in the vertical row refers to the activation date, and the value is the number of faulty devices produced. For the data in Table 2, the failure rate during daily usage can be calculated in a similar manner to the data in Table 1 above, which will not be elaborated here.

[0121] Based on the above example, the failure duration under different usage days (time spans such as weeks / months, etc.) can be defined as the periodic failure duration, and then the failure type of the fault can be judged according to the curve trend corresponding to the failure rate. For example, refer to Figure 6 the change trends of the failure rates of the three fault types shown in the time dimension (weeks). Figure 6 In the first graph in, it is the failure curve of appearance - related faults. Since users pay attention to appearance defects when they first get the device, the failure duration is relatively high in the early stage for appearance - related faults, that is, the failure rate is relatively high; the second graph is the failure curve of screen - cracking faults. Since screen - cracking occurs randomly during any period of users' daily use, the difference in the failure curve of screen - cracking faults is small between the early stage and the medium - to - long term; the third graph is the failure curve of button - aging faults. Due to the increase in the usage duration by the user at the user end, the faults in the medium - to - long term are more obvious, and the failure curve shows a gradually rising trend.

[0122] From Figure 6 the shown failure curves, it can be seen that the change trends of the failure curves of different faults are different. The failure curves corresponding to the same fault type of multiple terminal devices can be determined, and then according to the change trend of the failure curve, it can be determined whether there is a mutation in the failure curve corresponding to this fault type in a certain time period. For example, in a certain time period, the curve should tend to be stable, but suddenly rises. When the failure curve mutates, technicians can timely learn about this mutation through the failure curve, enabling technicians to give early warnings and locate problems in advance, avoiding potential losses, and improving the forward - looking nature of device research and development.

[0123] In some embodiments, in the case of obtaining the analysis results corresponding to multiple terminal devices of a target type, based on the analysis results corresponding to the multiple terminal devices and the activation quantity, where the activation quantity is the number of activated terminal devices among the terminal devices of the target type, the failure information corresponding to each failure type is determined. The failure information corresponding to a failure type is used to represent the proportion of the terminal devices having the failure of the failure type per day among the activated terminal devices, and the target type is any one of multiple device types; based on the failure information corresponding to each failure type, the failure curve corresponding to each failure type is determined. Optionally, the failure information is the failure rate, and for the calculation of the failure information, refer to the calculation of the failure rate shown in Table 1 above.

[0124] In some embodiments, after obtaining the failure information corresponding to each failure type, based on the failure information corresponding to each failure type, the available usage duration of any terminal device of the target type is predicted, that is, the life of the terminal device is predicted. Optionally, based on the failure information corresponding to each failure type, cumulative failure information is determined, where the cumulative failure information is the proportion of the terminal devices having the failure of the failure type accumulated over multiple days among the activated terminal pole devices, and then based on the cumulative failure information, the available usage duration is predicted.

[0125] For example, referring to Table 2 above, for the data shown in Table 2 above, it can be calculated as follows:

[0126] The failure rate accumulated for 1 day is:

[0127] (2 + 2 + 1 + 2 + 2 + 3) / (100 + 110 + 120 + 100 + 130 + 150) = 1.7%

[0128] The failure rate accumulated for 2 days is:

[0129] (2 + 2 + 1 + 2 + 2 + 1 + 4 + 2 + 3 + 2) / (100 + 110 + 120 + 100 + 130) = 3.7%

[0130] The failure rate accumulated for 3 days is:

[0131] (2 + 2 + 1 + 2 + 1 + 4 + 2 + 3 + 3 + 2 + 2 + 3) / (100 + 110 + 120 + 100) = 5.8%

[0132] The calculation methods for the failure rates of other days are similar and will not be elaborated here.

[0133] It should be noted that the present disclosure embodiments do not limit the specific calculation method for predicting the available usage duration.

[0134] Figure 7 It is a block diagram of an electronic device shown according to an exemplary embodiment. Refer to Figure 7, the electronic device includes:

[0135] An information acquisition module 701, configured to acquire fault information of a terminal device in response to a fault analysis request, where the fault information includes device information of the terminal device and description information of the generated fault;

[0136] A result output module 702, configured to output an analysis result corresponding to the fault information, where the analysis result is obtained by performing a failure analysis on the fault information, and the analysis result includes at least one of a fault type, a fault cause, a fault solution, and a failure duration of the terminal device.

[0137] In some embodiments, the electronic device further includes:

[0138] A failure analysis module, configured to perform a failure analysis on the fault information based on historical analysis data to obtain an analysis result; the historical analysis data is used to characterize historical faults and analysis results of historical faults.

[0139] In some embodiments, the electronic device further includes:

[0140] An information statistics module, configured to perform statistics on the fault information to obtain statistical information of the fault information;

[0141] A failure analysis module, configured to perform a failure analysis based on the fault information and the statistical information to obtain an analysis result.

[0142] In some embodiments, the failure analysis module is configured to:

[0143] Based on a multi-layer architecture of a data warehouse, perform data processing on the fault information and the statistical information to obtain data to be analyzed;

[0144] Based on the historical analysis data and the data to be analyzed, perform coupling to obtain an analysis result.

[0145] In some embodiments, the multi-layer architecture includes a first data layer, a second data layer, a third data layer, a third data layer, a fourth data layer, and a fifth data layer. The failure analysis module is configured to:

[0146] Based on the first data layer, acquire the fault information and the statistical information;

[0147] Based on the second data layer, perform data filtering on the fault information and the statistical information to obtain filtered fault information and filtered statistical information;

[0148] Based on the third data layer, aggregate the filtered fault information and the filtered statistical information according to multiple preset dimensions to obtain information for each preset dimension;

[0149] Based on the fourth data layer, data calculations are performed on the information of each preset dimension respectively to obtain the index parameters corresponding to each preset dimension.

[0150] Based on the fifth data layer, the index parameters of multiple preset dimensions are determined as the data to be analyzed.

[0151] In some embodiments, the result output module 702 is configured to query and output the analysis result in response to detecting a query operation.

[0152] In some embodiments, the electronic device further includes:

[0153] A failure information determination module, configured to, in the case of obtaining the analysis results corresponding to multiple terminal devices of a target type, determine the failure information corresponding to each failure type based on the analysis results corresponding to the multiple terminal devices and the activation quantity, where the activation quantity is the number of activated terminal devices among the terminal devices of the target type, and the failure information corresponding to the failure type is used to represent the proportion of the terminal devices having the failure of the failure type generated per day among the activated terminal devices, and the target type is any one of multiple device types;

[0154] A failure curve determination module, configured to determine the failure curve corresponding to each failure type based on the failure information corresponding to each failure type.

[0155] In some embodiments, the electronic device further includes:

[0156] A serviceable duration determination module, configured to predict the serviceable duration of any terminal device of the target type based on the failure information corresponding to each failure type.

[0157] Regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated herein.

[0158] The embodiments of the present disclosure further provide an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein, the processor is configured to execute the data analysis method in the above embodiments.

[0159] Figure 8 It is a block diagram of an electronic device 800 shown according to an exemplary embodiment.

[0160] Referring to Figure 8 , the electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0161] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communication, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above methods. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0162] The memory 804 is configured to store various types of data to support the operation of the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0163] The power component 806 provides power to various components of the electronic device 800. The power component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

[0164] The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can not only sense the boundaries of touch or swipe actions but also detect the duration and pressure associated with the touch or swipe operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have focal length and optical zoom capabilities.

[0165] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), which is configured to receive external audio signals when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals can be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 further includes a speaker for outputting audio signals.

[0166] The I / O interface 812 provides an interface between the processing component 802 and a peripheral interface module, and the peripheral interface module can be a keyboard, a click wheel, buttons, etc. These buttons can include but are not limited to: a home button, a volume button, a power button, and a lock button.

[0167] The sensor component 814 includes one or more sensors for providing an assessment of the status of various aspects of the electronic device 800. For example, the sensor component 814 can detect the on / off state of the electronic device 800, the relative positioning of components, such as the display and keypad of the electronic device 800. The sensor component 814 can also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. The sensor component 814 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor component 814 can also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor component 814 can further include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0168] The communication component 816 is configured to facilitate communication between the electronic device 800 and other devices in a wired or wireless manner. The electronic device 800 can access a wireless network based on communication standards, such as WiFi, 2G, or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0169] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above method.

[0170] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the above instructions can be executed by a processor 820 of the electronic device 800 to complete the above method. For example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0171] The embodiments of the present disclosure also provide a non-transitory computer-readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the data analysis method in the above embodiments.

[0172] Those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include common general knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and embodiments are only to be considered as exemplary, and the true scope and spirit of the present invention are pointed out by the following claims.

[0173] It should be understood that the present invention is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A data analysis method, characterized in that, The method includes: In response to a fault analysis request, obtaining fault information of a terminal device, where the fault information includes device information of the terminal device and description information of the generated fault; Outputting an analysis result corresponding to the fault information, where the analysis result is obtained by performing a failure analysis on the fault information, and the analysis result includes at least one of the fault type, fault cause, fault solution, and failure duration of the terminal device.

2. The method according to claim 1, wherein Before the step of outputting the analysis result corresponding to the fault information, the method further includes: Based on historical analysis data, performing a failure analysis on the fault information to obtain an analysis result; the historical analysis data is used to characterize historical faults and the analysis results of the historical faults.

3. The method according to claim 2, wherein The method further includes: Performing statistics on the fault information to obtain statistical information of the fault information; The performing a failure analysis on the fault information based on the historical analysis data to obtain an analysis result includes: Based on the historical analysis data, performing a failure analysis on the fault information and the statistical information to obtain the analysis result.

4. The method according to claim 3, characterized in that, The performing a failure analysis on the fault information and the statistical information based on the historical analysis data to obtain the analysis result includes: Based on the multi-layer architecture of the data warehouse, performing data processing on the fault information and the statistical information to obtain data to be analyzed; Based on the historical analysis data and the data to be analyzed, performing coupling to obtain the analysis result.

5. The method according to claim 4, characterized in that The multi-layer architecture includes a first data layer, a second data layer, a third data layer, a third data layer, a fourth data layer, and a fifth data layer. The performing data processing on the fault information and the statistical information based on the multi-layer architecture of the data warehouse to obtain data to be analyzed includes: Based on the first data layer, obtaining the fault information and the statistical information; Based on the second data layer, performing data filtering on the fault information and the statistical information to obtain filtered fault information and filtered statistical information; Based on the third data layer, aggregating the filtered fault information and the filtered statistical information according to multiple preset dimensions to obtain information for each preset dimension; Based on the fourth data layer, respectively performing data calculations on the information for each preset dimension to obtain index parameters corresponding to each preset dimension; Based on the fifth data layer, determining the index parameters of multiple preset dimensions as the data to be analyzed.

6. The method according to claim 1, characterized in that The outputting an analysis result corresponding to the fault information includes: In response to detecting a query operation, querying and outputting the analysis result.

7. The method according to claim 1, wherein The method further includes: In the case of obtaining analysis results corresponding to multiple terminal devices of a target type, based on the analysis results corresponding to the multiple terminal devices and the activation quantity, determining failure information corresponding to each fault type, where the activation quantity is the number of activated terminal devices among the terminal devices of the target type, and the failure information corresponding to the fault type is used to characterize the proportion of the terminal devices that generate faults of the fault type every day among the activated terminal devices, and the target type is any one of multiple device types; Based on the failure information corresponding to each type of failure, determine the failure curve corresponding to each type of failure.

8. The method according to claim 7, wherein The method further includes: Based on the failure information corresponding to each type of failure, predict the available duration of any terminal device of the target type.

9. An electronic device, characterized in that, It includes: An information acquisition module, configured to acquire the failure information of the terminal device in response to a failure analysis request, where the failure information includes the device information of the terminal device and the description information of the generated failure; A result output module, configured to output an analysis result corresponding to the failure information, where the analysis result is obtained by performing a failure analysis on the failure information, and the analysis result at least includes at least one of the failure type, failure cause, failure solution, and failure duration of the terminal device.

10. An electronic device, characterized in that, It includes: A processor; A memory for storing instructions executable by the processor; Wherein, the processor is configured to execute the method according to any one of claims 1-8.

11. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is enabled to execute the method according to any one of claims 1-8.

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