Data processing method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a data processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps that a target product data set is acquired from a data mart, multiple pieces of product data sent by a data management system are stored in the data mart, and the target product data set comprises the multiple pieces of product data; obtaining the data volume of the target product data set, and determining whether an alarm condition is satisfied based on the data volume and the historical data volume of the historical product data set obtained in the historical time period; if the alarm condition is met, executing an alarm operation; and if the alarm condition is not met, performing product production based on the target product data set. By adopting the method, the accuracy of the product data can be guaranteed, so that the safety problem caused by poor accuracy of the product data during product production based on the product data is avoided.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly to a data processing method, apparatus, computer device, computer-readable storage medium, and computer program product. Background Art

[0002] Product data, namely the Engineering Bill of Materials (EBOM), can be used to describe the structure and function of a product, including all components, sub-components, parts, and raw materials that make up the product, as well as related technical specifications and drawings.

[0003] In the prior art, a data management system sends product data to the downstream application side through a data mart. After receiving the product data, the downstream application side directly conducts product production based on the product data.

[0004] However, since the downstream application side cannot guarantee the accuracy of the product data, there are significant security issues in the product production based on the product data. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a data processing method, apparatus, computer device, computer-readable storage medium, and computer program product that can guarantee the accuracy of product data, thereby avoiding security issues caused by poor accuracy of product data during product production based on the product data.

[0006] In a first aspect, this application provides a data processing method, including:

[0007] Obtain a target product data set from a data mart, where the data mart stores multiple pieces of product data sent by a data management system, and the target product data set includes the multiple pieces of product data; obtain the data volume of the target product data set, and based on the data volume and the historical data volume of the historical product data set obtained within a historical period, determine whether an alarm condition is met; if the alarm condition is met, perform an alarm operation; if the alarm condition is not met, conduct product production based on the target product data set.

[0008] In some embodiments, the determining whether the alarm condition is met based on the data volume and the historical data volume of the historical product data set obtained within a historical period includes: determining a data volume change rate based on the data volume and the historical data volume; and determining that the alarm condition is met when the data volume change rate is greater than a preset change rate threshold.

[0009] In some embodiments, if the warning condition is met, a warning operation is performed, including: determining a target interval in which the data volume change rate is located among multiple data volume change rate intervals, where different data volume change rate intervals correspond to different warning intensities; determining a target warning intensity corresponding to the target interval according to the target interval, and issuing a warning according to the target warning intensity.

[0010] In some embodiments, the method further includes: detecting whether the data volume of the target product dataset is greater than a preset data volume threshold; if so, performing the step of determining whether the warning condition is met based on the data volume and the historical data volume of the historical product dataset obtained during the historical period; if not, performing the warning operation.

[0011] In some embodiments, the method further includes: after performing the warning operation, using the data management system and the data mart to re-obtain the target product dataset; performing data verification on the re-obtained target product dataset, and stopping the warning operation when the verification passes.

[0012] In some embodiments, the method further includes: when the verification fails, determining the number of times of re-obtaining the target product dataset using the data management system and the data mart; when the number of times is less than the number threshold, continuing to use the data management system and the data mart to re-obtain the target product dataset, and performing data verification on the re-obtained target product dataset; when the number of times is greater than or equal to the number threshold, continuing to perform the warning operation.

[0013] In some embodiments, the product production based on the target product dataset includes: obtaining change data for the multiple product data sent in real time by the data management system through a communication interface; merging the target product dataset and the change data to obtain merged data, and performing data verification on the merged data; when the verification passes, performing product production based on the merged data.

[0014] In a second aspect, the present application further provides a data processing device, including:

[0015] An acquisition module, configured to acquire a target product dataset from a data mart, where the data mart stores multiple product data sent by a data management system, and the target product dataset includes the multiple product data;

[0016] A determination module, configured to acquire the data volume of the target product dataset, and determine whether the warning condition is met based on the data volume and the historical data volume of the historical product dataset obtained during the historical period;

[0017] An execution module, configured to perform an alarm operation if the alarm condition is met; and perform product production based on the target product data set if the alarm condition is not met.

[0018] In some embodiments, the determination module is specifically configured to determine a data volume change rate based on the data volume and the historical data volume; and determine that the alarm condition is met when the data volume change rate is greater than a preset change rate threshold.

[0019] In some embodiments, the execution module is specifically configured to determine a target interval in which the data volume change rate is located among multiple data volume change rate intervals, and different data volume change rate intervals correspond to different alarm intensities; determine a target alarm intensity corresponding to the target interval according to the target interval, and perform an alarm according to the target alarm intensity.

[0020] In some embodiments, the determination module is further configured to detect whether the data volume of the target product data set is greater than a preset data volume threshold; if so, perform the step of determining whether the alarm condition is met based on the data volume and the historical data volume of the historical product data set obtained during a historical period; if not, perform the alarm operation.

[0021] In some embodiments, the execution module is further configured to, after performing the alarm operation, use the data management system and the data mart to re-obtain the target product data set; perform data verification on the re-obtained target product data set, and stop performing the alarm operation when the verification passes.

[0022] In some embodiments, the execution module is further configured to, when the verification fails, determine the number of times of re-obtaining the target product data set by using the data management system and the data mart; when the number of times is less than a number threshold, perform re-obtaining the target product data set by using the data management system and the data mart, and perform data verification on the re-obtained target product data set; when the number of times is greater than or equal to the number threshold, continue to perform the alarm operation.

[0023] In some embodiments, the execution module is specifically configured to obtain change data of the multiple product data sent in real time by the data management system through a communication interface; merge the target product data set and the change data to obtain merged data, and perform data verification on the merged data; when the verification passes, perform product production based on the merged data.

[0024] In a third aspect, the present application further provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of the method described in any one of the embodiments in the first aspect are implemented.

[0025] Fourthly, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in any one of the embodiments of the first aspect above are implemented.

[0026] Fifthly, the present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the method described in any one of the embodiments of the first aspect above are implemented.

[0027] For the above data processing method, device, computer device, computer-readable storage medium and computer program product, first obtain a target product data set from a data mart. The data mart stores multiple product data sent by a data management system, and the target product data set includes the multiple product data. Then, obtain the data volume of the target product data set, and based on the data volume and the historical data volume of the historical product data set obtained within a historical period, determine whether the alarm condition is satisfied; if the alarm condition is satisfied, perform an alarm operation; if the alarm condition is not satisfied, perform product production based on the target product data set. Since before performing product production based on the target product data set, it is first determined whether the alarm condition is satisfied by the data volume of the target product data set and the historical data volume of the historical product data set, the accuracy of product data can be guaranteed to a certain extent, and further, when performing product production based on product data, security problems caused by poor accuracy of product data can be avoided. Moreover, when the alarm condition is satisfied, performing an alarm operation in a timely manner can also effectively improve security. Description of the Drawings

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0029] Figure 1 It is an application environment diagram of the data processing method in an embodiment;

[0030] Figure 2 It is a flowchart of the data processing method in an embodiment;

[0031] Figure 3 It is a flowchart of an optional technical process for determining whether the alarm condition is satisfied based on the data volume and the historical data volume of the historical product data set obtained within a historical period;

[0032] Figure 4The flowchart of an optional technical process for performing an alarm operation when the alarm condition is met in an embodiment;

[0033] Figure 5 The flowchart of an optional technical process for detecting whether the data volume of the target product dataset is greater than a preset data volume threshold in an embodiment;

[0034] Figure 6 The flowchart of an optional technical process after performing the alarm operation in an embodiment;

[0035] Figure 7 The flowchart of an optional technical process in the case of failed verification in an embodiment;

[0036] Figure 8 The flowchart of an optional technical process for product production based on the target product dataset in an embodiment;

[0037] Figure 9 The flowchart of a data processing method in another embodiment;

[0038] Figure 10 The structural block diagram of a data processing device in an embodiment;

[0039] Figure 11 The internal structure diagram of a computer device in an embodiment;

[0040] Figure 12 The internal structure diagram of a computer device in another embodiment. Detailed implementation manners

[0041] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0042] Product data is the Engineering Bill of Materials (EBOM), which can be used to describe the structure and function of a product, including all components, sub-components, parts and raw materials that make up the product, as well as relevant technical specifications and drawings.

[0043] In the prior art, the data management system sends product data to the downstream application side through the data mart, and the downstream application side directly performs product production based on the product data after receiving it.

[0044] However, since the downstream application side cannot determine the accuracy of the received product data and cannot give an alarm in a timely manner when there are problems with the received product data, there are significant safety issues in product production based on the product data.

[0045] In view of this, the present application provides a data processing method, device, computer device, computer-readable storage medium, and computer program product. First, obtain a target product data set from a data mart. The data mart stores multiple pieces of product data sent by a data management system, and the target product data set includes the multiple pieces of product data. Then, obtain the data volume of the target product data set, and based on the data volume and the historical data volume of the historical product data set obtained within a historical period, determine whether the alarm condition is met. If the alarm condition is met, perform an alarm operation. If the alarm condition is not met, perform product production based on the target product data set. Since it is determined whether the alarm condition is met by the data volume of the target product data set and the historical data volume of the historical product data set before product production based on the target product data set, the accuracy of the product data can be guaranteed to a certain extent, thereby avoiding safety issues caused by poor accuracy of the product data during product production based on the product data. Moreover, when the alarm condition is met, performing an alarm operation in a timely manner can also effectively improve safety.

[0046] The data processing method provided by the embodiments of the present application may be executed by a computer device, and this method may be applied to an application environment as Figure 1 shown. Among them, the data management system may send multiple pieces of product data to the data mart so that the computer device can obtain a target product data set including multiple pieces of product data in the data mart.

[0047] In some possible cases, the computer device may be a terminal device, and the terminal device includes but is not limited to various personal computers, laptop computers, tablet computers, Internet of Things devices, etc.

[0048] In some possible cases, the computer device may also be a server. Optionally, the server may implement the data processing method provided by the embodiments of the present application through interaction with the terminal device. Among them, the server may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0049] In an exemplary embodiment, as Figure 2 shown, a data processing method is provided. Taking the application of this method to a computer device as an example, the method includes the following steps:

[0050] Step 201: Obtain a target product data set from a data mart.

[0051] Among them, the data mart stores multiple pieces of product data sent by the data management system, and the target product data set includes the multiple pieces of product data.

[0052] Product data is also the Engineering Bill of Material (EBOM). EBOM data contains basic information about all components, sub-components, parts, and raw materials of the product, such as name, material, specification, model, etc.

[0053] For example, taking a car as an example, its EBOM data can include the name, material, specification, and model of the engine; the name, material, specification, and model of the tires; the name, material, specification, and model of the body frame, etc.

[0054] Another example is a laptop. Its EBOM data can include the name, material, specification, and model of the CPU; the name, material, specification, and model of the memory module; the name, material, specification, and model of the display screen, etc.

[0055] The data mart is usually extracted from a data warehouse or other data sources. Compared with a data warehouse, the data mart has a smaller data scale, a relatively simple structure, and higher query performance, and can quickly respond to query requests.

[0056] The data management system is also the Product Lifecycle Management (PLM) system. PLM can integrate relevant information in all stages of the product's entire life cycle, such as product design data, manufacturing process data, and supply chain data. It can also integrate personnel information in all stages of the product's entire life cycle, such as the information of all personnel involved in product design, manufacturing, sales, service, etc.

[0057] In an alternative embodiment of the present application, the data management system can push all multiple pieces of product data to the data mart based on the T+1 mode at a preset time. Optionally, the preset time can be pre-set by technicians according to actual needs, such as 1:00 am every day. The T+1 mode refers to the previous day of the current date.

[0058] In an alternative embodiment of the present application, the target product data set can be obtained from the data mart. Optionally, after receiving the multiple pieces of product data pushed by the data management system, the data mart can actively push the multiple pieces of product data to the computer device, or the computer device can actively obtain it from the data mart.

[0059] In an alternative embodiment of the present application, after the data mart pushes multiple product data to the computer device, it can generate information for recording the push time and push status, so as to facilitate the tracing of the data link and the troubleshooting of problems. Optionally, the push status may include whether the push is successful and the reason for failure, and the reason for failure may be a network failure, a data format error, etc.

[0060] Step 202: Obtain the data volume of the target product data set, and determine whether the alarm condition is satisfied based on the data volume and the historical data volume of the historical product data set obtained within the historical period.

[0061] In an alternative embodiment of the present application, the data volume of the target product data set can be obtained. Optionally, a data volume detection task can be created based on the workflow orchestration platform (DS, DolphinScheduler) to obtain the data volume of the target product data set through the data volume detection task.

[0062] In an alternative embodiment of the present application, the historical period can be a period originally set by technicians according to actual needs, such as the past seven days, the past month, etc.

[0063] As described above, the data management system can push multiple product data to the data mart at a preset time, which can be 1:00 am every day. That is, the computer device can obtain the product data set every day. The product data set currently obtained by the computer device is the target product data set, and the product data set obtained by the computer device within the historical period is the historical product data set.

[0064] In an alternative embodiment of the present application, after the computer device obtains the historical product data set within the historical period, it can also obtain the data volume of the historical product data set based on the data volume detection task.

[0065] In an alternative embodiment of the present application, it can be determined whether the alarm condition is satisfied according to the data volume of the target product data set and the historical data volume of the historical product data set obtained within the historical period. Optionally, it can be determined whether the alarm condition is satisfied according to the difference between the data volume of the target product data set and the historical data volume of the historical product data set obtained within the historical period.

[0066] For example, when the absolute value of the difference between the data volume and the historical data volume is greater than the preset threshold, it is determined that the alarm condition is satisfied. When the absolute value of the difference between the data volume and the historical data volume is less than the preset threshold, it is determined that the alarm condition is not satisfied.

[0067] Step 203: If the alarm condition is satisfied, perform an alarm operation.

[0068] In an alternative embodiment of the present application, when it is determined that the warning condition is met based on the data volume and the historical data volume of the historical product dataset obtained within the historical period, a warning operation may be performed. Optionally, the warning operation may be a warning via an instant messaging software. For example, send a warning message to relevant work groups or individuals through the instant messaging software used within the enterprise.

[0069] Warning may also be given through an interface prompt. For example, on the display screen of a computer device, display warning information to the user in a prominent manner.

[0070] Warning may also be given through an email. For example, send an email notification to the person in charge of product data for warning.

[0071] Step 204: If the warning condition is not met, product production is performed based on the target product dataset.

[0072] In an alternative embodiment of the present application, when it is determined that the warning condition is not met based on the data volume and the historical data volume of the historical product dataset obtained within the historical period, product production may be performed based on the target product dataset. Optionally, information such as the product structure and technical specifications in the target product dataset may be parsed first to clarify the relationships between components and key indicators. Based on this, a production plan is formulated for product generation, such as a parts procurement plan, a production process plan, and a production capacity plan.

[0073] The data processing method provided by the embodiments of the present application first obtains a target product dataset from a data mart. The data mart stores multiple pieces of product data sent by a data management system, and the target product dataset includes the multiple pieces of product data. Then, the data volume of the target product dataset is obtained, and it is determined whether the warning condition is met based on the data volume and the historical data volume of the historical product dataset obtained within the historical period. If the warning condition is met, a warning operation is performed. If the warning condition is not met, product production is performed based on the target product dataset. Since it is determined whether the warning condition is met by the data volume of the target product dataset and the historical data volume of the historical product dataset before product production based on the target product dataset, the accuracy of product data can be guaranteed to a certain extent, thereby avoiding safety problems caused by poor accuracy of product data during product production based on product data. Moreover, when the warning condition is met, performing a warning operation in a timely manner can also effectively improve safety.

[0074] Please refer to Figure 3 , in an exemplary embodiment, an alternative technical process for determining whether the warning condition is met based on the data volume and the historical data volume of the historical product dataset obtained within the historical period is provided. As Figure 3 shown, the technical process may include the following steps:

[0075] Step 301: Determine the data volume change rate based on the data volume and the historical data volume.

[0076] The data volume change rate is used to characterize the degree of change in the data volume within a certain time period.

[0077] In an alternative embodiment of the present application, the data volume change rate can be determined based on the data volume and the historical data volume. Optionally, the distance change rate can be determined using the data volume change rate formula, the data volume, and the historical data volume. The data volume change rate formula can be: data volume change rate = data volume / historical data volume × 100%.

[0078] Alternatively, the data volume change rate can be determined using a pre-trained data volume change rate determination model, the data volume, and the historical data volume. The data volume and the historical data volume can be input into the data volume change rate determination model to obtain the data volume change rate output by the data volume change rate determination model.

[0079] Step 302: Determine that the alarm condition is satisfied when the data volume change rate is greater than the preset change rate threshold.

[0080] In an alternative embodiment of the present application, the preset change rate threshold can be pre-set by a technician according to actual needs. Optionally, the preset change rate threshold can be ±10% or ±20%.

[0081] In an alternative embodiment of the present application, after determining the data volume change rate based on the data volume and the historical data volume, the preset change rate threshold can be obtained, and it can be determined whether the data volume change rate is greater than the preset change rate threshold. If it is greater, it can be determined that the alarm condition is satisfied. If it is less than or equal, it can be determined that the alarm condition is not satisfied.

[0082] In an embodiment of the present application, by determining the data volume change rate based on the data volume and the historical data volume, and then determining whether the alarm condition is satisfied based on the data volume change rate, the accuracy of the target product data set can be guaranteed to a certain extent.

[0083] Please refer to Figure 4 , in an exemplary embodiment, an alternative technical process for satisfying the alarm condition and performing an alarm operation is provided. As Figure 4 shown, the technical process can include the following steps:

[0084] Step 401: Determine the target interval in which the data volume change rate is located among multiple data volume change rate intervals.

[0085] Among them, different data volume change rate intervals correspond to different alarm intensities.

[0086] In an alternative embodiment of the present application, the data volume change rate range can be preset by those skilled in the art according to actual needs. Optionally, the data volume change rate range can include a first range and a second range. The first range is greater than ±10% and less than ±20%, and the second range can be greater than ±20%.

[0087] As described above, different data volume change rate ranges correspond to different alarm intensities. If the data volume change range includes a first range and a second range, the alarm intensity corresponding to the first range can be the first alarm intensity, and the alarm intensity corresponding to the second range can be the second alarm intensity, and the second alarm intensity is higher than the first alarm intensity.

[0088] In an alternative embodiment of the present application, after determining the data volume change rate, the target range in which the data volume change rate is located among multiple data volume change rate ranges can be determined according to the data volume change rate and the data volume change rate range.

[0089] For example, if the data volume change rate is 15%, the target range can be determined as the first range. For another example, if the data volume change rate is 22%, the target range can be determined as the second range.

[0090] Step 402: Determine the target alarm intensity corresponding to the target range according to the target range, and issue an alarm according to the target alarm intensity.

[0091] In an alternative embodiment of the present application, after determining the target range, the target alarm intensity corresponding to the target range can be determined according to the target range. Optionally, the data volume change rate range - alarm intensity mapping relationship list can be used to determine the target alarm intensity according to the target range. The data volume change rate range - alarm intensity mapping relationship list can be shown in Table 1.

[0092] Table 1

[0093]

[0094] For example, if the target range is the first range, the target alarm intensity is the first alarm intensity. For another example, if the target range is the second range, the target alarm intensity is the second alarm intensity.

[0095] In an alternative embodiment of the application, after determining the target alarm intensity, an alarm can be issued according to the target alarm intensity. Optionally, the first alarm intensity can indicate sending medium-level alarm information to the person in charge of product data through instant messaging software and email to remind the relevant person in charge to pay attention to the changes in product data. The second alarm intensity can indicate sending high-level alarm information to the person in charge of product data through instant messaging software and email to remind the relevant person in charge to immediately handle the abnormal product data problem.

[0096] In an optional embodiment of the present application, after issuing an alarm according to the target alarm intensity, the alarm processing status and the alarm duration are obtained in real time; when the duration is greater than a preset time and the alarm status indicates unprocessed, an alarm will be issued according to an alarm intensity one level higher than the target alarm intensity.

[0097] The method of determining the target interval in which the data volume change rate is located among multiple data volume change rate intervals, determining the target alarm intensity corresponding to the target interval according to the target interval, and issuing an alarm according to the target alarm intensity realizes precise alarming by setting different data volume change rate intervals and setting different alarm intensities for different data volume change rate intervals, thereby improving the efficiency of data processing.

[0098] Please refer to Figure 5 , in an exemplary embodiment, an optional technical process for detecting whether the data volume of the target product dataset is greater than a preset data volume threshold is provided. As Figure 5 shown, the technical process may include the following steps:

[0099] Step 501, detect whether the data volume of the target product dataset is greater than a preset data volume threshold.

[0100] In an optional embodiment of the present application, the preset data volume threshold may be set in advance by a technician according to actual needs. Optionally, the preset data volume threshold may be 0.

[0101] In an optional embodiment of the present application, after the computer device obtains the target product dataset, it may first determine the data volume of the target product dataset. After determining the data volume of the target product dataset, it may obtain the preset data volume threshold and detect whether the data volume of the target product dataset is greater than the preset data volume threshold, that is, detect whether the target product dataset is empty.

[0102] Step 502, if yes, execute the step of determining whether the alarm condition is satisfied based on the data volume and the historical data volume of the historical product dataset obtained within the historical period.

[0103] In an optional embodiment of the present application, if it is detected that the data of the target product dataset is greater than the preset data volume threshold, then execute the step of determining whether the alarm condition is satisfied based on the data volume and the historical data volume of the historical product dataset obtained within the historical period.

[0104] Step 503, if no, execute the alarm operation.

[0105] In an optional embodiment of the present application, if it is detected that the data of the target product dataset is less than or equal to the preset data volume threshold, an alarm operation is performed.

[0106] In an alternative embodiment of the present application, the alarm may be issued according to the third alarm intensity, and the third alarm intensity may be to send alarm information including the table name of the target product data set, the detection time, etc. to the person in charge of product data through an instant messaging software and an email.

[0107] In an alternative embodiment of the present application, after the alarm is processed, the alarm processing result may also be obtained and evaluated.

[0108] Please refer to Figure 6 , in an exemplary embodiment, an alternative technical process after performing the alarm operation is provided, such as Figure 6 shown, and the technical process may include the following steps:

[0109] Step 601: Use the data management system and the data mart to re-obtain the target product data set.

[0110] In an alternative embodiment of the present application, after the computer device performs the alarm operation, it may use the data management system and the data mart to re-obtain the target product data set. Optionally, a data acquisition request may be sent to the data management system so that the data management system re-acquires the product data by calling the data acquisition interface, and pushes the re-acquired product data to the data mart, and then obtains the re-acquired target product data set pushed by the data management system from the data mart.

[0111] Step 602: Perform data verification on the re-obtained target product data set, and stop performing the alarm operation when the verification passes.

[0112] In an alternative embodiment of the present application, data verification may be performed on the re-obtained target product data set. Optionally, the data verification may include integrity verification, accuracy verification, and consistency verification.

[0113] Integrity verification can ensure that the product data remains intact during storage, transmission, and processing, without loss, omission, or tampering. Integrity verification can be performed by checking whether the value of each field conforms to the specified format, range, and constraint conditions. Accuracy verification can check whether the content of the product data is correct, that is, the information expressed by the product data matches the actual situation, established specifications, or expected results. Consistency verification can be used to check whether the product data remains consistent among different parts, different systems, or different time points, without contradictions or conflicts.

[0114] The method of re-obtaining the target product data set by using the data management system and the data mart, performing data verification on the re-obtained target product data set, and stopping the execution of the warning operation when the verification is passed. By performing data verification on the re-obtained target product data set, the accuracy of the target product data set is guaranteed, thereby avoiding security problems caused by poor accuracy of product data during product production based on product data.

[0115] In an alternative embodiment of the present application, after performing data verification on the re-obtained target product data set, if it is determined that the verification is passed, the warning operation can be stopped.

[0116] Please refer to Figure 7 , in an exemplary embodiment, an alternative technical process in the case of failed verification is provided, such as Figure 7 shown, the technical process may include the following steps:

[0117] Step 701: Determine the number of times of re-obtaining the target product data set by using the data management system and the data mart.

[0118] In an alternative embodiment of the present application, after performing data verification on the re-obtained target product data set, if it is determined that the verification fails, the number of times of re-obtaining the target product data set by using the data management system and the data mart can be determined.

[0119] For example, after a warning operation is performed because the data volume of the target product data set is less than the preset data volume threshold, the computer device can re-obtain the target product data set by using the data management system and the data mart, and the number of times is 1.

[0120] For another example, after a warning operation is performed because the data volume change rate meets the warning condition, the computer device can re-obtain the target product data set by using the data management system and the data mart, and the number of times is 1.

[0121] Step 702: When the number of times is less than the number threshold, continue to re-obtain the target product data set by using the data management system and the data mart, and perform data verification on the re-obtained target product data set.

[0122] In an alternative embodiment of the present application, the number threshold can be pre-set by a technician according to actual needs. For example, the number threshold can be 3, 5, etc.

[0123] In an alternative embodiment of the present application, when it is determined that the number of times is less than the number threshold, the target product data set can be re-obtained again by using the data management system and the data mart, and data verification is performed on the re-obtained target product data set.

[0124] For example, after an alarm operation is performed because the data volume of the target product dataset is less than the preset data volume threshold, the computer device can use the data management system and the data mart to re-obtain the target product dataset, and the number of times is 1. Since this number of times is less than the number threshold, the data management system and the data mart can be used again to re-obtain the target product dataset, and the number of times is 2.

[0125] For another example, after an alarm operation is performed because the data volume change rate meets the alarm condition, the computer device can use the data management system and the data mart to re-obtain the target product dataset, and the number of times is 1. Since this number of times is less than the number threshold, the data management system and the data mart can be used again to re-obtain the target product dataset, and the number of times is 2.

[0126] Step 703, when the number of times is greater than or equal to the number threshold, continue to perform the alarm operation.

[0127] In an alternative embodiment of the present application, when it is determined that the number of times is greater than or equal to the number threshold, the alarm operation can be continued.

[0128] For example, after an alarm operation is performed because the data volume of the target product dataset is less than the preset data volume threshold, the computer device can use the data management system and the data mart to re-obtain the target product dataset, and the number of times is 1. Since this number of times is less than the number threshold, the data management system and the data mart can be used again to re-obtain the target product dataset, and the number of times is 2. Assume that the number threshold is 2. Data verification is performed on the re-obtained target product dataset. If the verification fails, since the number of times is equal to the number threshold, the alarm operation is continued.

[0129] For another example, after an alarm operation is performed because the data volume change rate meets the alarm condition, the computer device can use the data management system and the data mart to re-obtain the target product dataset, and the number of times is 1. Since this number of times is less than the number threshold, the data management system and the data mart can be used again to re-obtain the target product dataset, and the number of times is 2. Assume that the number threshold is 2. Data verification is performed on the re-obtained target product dataset. If the verification fails, since the number of times is equal to the number threshold, the alarm operation is continued.

[0130] In an alternative embodiment of the present application, when the number of times is greater than or equal to the number threshold, the alarm will be issued at the highest alarm intensity. Optionally, the highest alarm intensity can be to send alarm information including the number of times, the time of each re-acquisition, and the data verification result to the person in charge of product data through instant messaging software and email.

[0131] Please refer toFigure 8 , in an exemplary embodiment, an optional technical process for product production based on the target product dataset is provided, such as Figure 8 shown, the technical process may include the following steps:

[0132] Step 801, obtain the change data for the multiple product data sent by the data management system in real time through the communication interface.

[0133] In an optional embodiment of the present application, the communication interface may be an Enterprise Service Bus interface (ESB). The ESB interface is a distributed software architecture channel that can implement functions such as message passing, protocol conversion, data format conversion, service routing, and orchestration.

[0134] In an optional embodiment of the present application, the data management system may send the change data for the multiple product data to the computer device through the ESB interface. The computer device may also actively obtain the change data for the multiple product data in the data management system through the ESB interface.

[0135] Step 802, merge the target product dataset and the change data to obtain merged data, and perform data verification on the merged data.

[0136] In an optional embodiment of the present application, the data verification includes consistency verification, and the consistency verification can be used to ensure the logic of the merged data.

[0137] In an optional embodiment of the present application, after the computer device obtains the change data for the multiple product data sent by the data management system in real time through the communication interface, it may merge the target product dataset and the change data to obtain merged data, and perform data verification on the merged data.

[0138] Optionally, data preprocessing can be performed on the target product dataset and the change data first to check and ensure data format compatibility, and at the same time perform data cleaning to remove duplicate, incorrect, or incomplete records, and then determine the merging basis. For example, it can be determined by keyword field matching or based on information such as timestamps and version numbers. Then, data merging can be performed using database operations, data processing tools, etc.

[0139] Step 803, in the case where the verification passes, perform product production based on the merged data.

[0140] In an alternative embodiment of the present application, after data verification of the merged data, if it is determined that the merged data passes the data verification, product production is performed based on the merged data. Optionally, information such as the product structure and technical specifications in the merged data can be parsed first to clarify the relationships between components and key indicators. Based on this, a production plan is formulated to generate products, such as a parts procurement plan, a production process plan, and a production capacity plan.

[0141] The method of obtaining the change data for the multiple product data sent in real time by the data management system through the communication interface, merging the target product data set and the change data to obtain merged data, and performing data verification on the merged data. After merging the target product data set and the change data, data verification can also be performed on the merged data, which can avoid security problems caused by poor accuracy of the merged data during product production based on the merged data.

[0142] In an exemplary embodiment, as Figure 9 shown, another data processing method is provided, and this method includes the following steps:

[0143] Step 901: Obtain a target product data set from a data mart. The data mart stores multiple product data sent by a data management system, and the target product data set includes the multiple product data;

[0144] Step 902: Obtain the data volume of the target product data set, and detect whether the data volume of the target product data set is greater than a preset data volume threshold; if not, perform an alarm operation; if so, determine the data volume change rate based on the data volume and the historical data volume of the historical product data set obtained within a historical period;

[0145] Step 903: In the case where the data volume change rate is less than a preset change rate threshold, it is determined that the alarm condition is not satisfied, and then obtain the change data for the multiple product data sent in real time by the data management system through the communication interface; merge the target product data set and the change data to obtain merged data, and perform data verification on the merged data; in the case where the verification passes, perform product production based on the merged data;

[0146] Step 904: In the case where the data volume change rate is greater than a preset change rate threshold, it is determined that the alarm condition is satisfied, then determine the target interval in which the data volume change rate is located among multiple data volume change rate intervals, determine the target alarm intensity corresponding to the target interval according to the target interval, and perform an alarm according to the target alarm intensity;

[0147] Step 905: After performing the alarm operation, use the data management system and the data mart to re-obtain the target product data set; perform data verification on the re-obtained target product data set, and stop performing the alarm operation if the verification passes.

[0148] Step 906: If the verification fails, determine the number of times of re-obtaining the target product data set by using the data management system and the data mart; if the number is less than the number threshold, continue to use the data management system and the data mart to re-obtain the target product data set, and perform data verification on the re-obtained target product data set; if the number is greater than or equal to the number threshold, continue to perform the alarm operation.

[0149] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the indications of the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages do not necessarily have to be executed at the same time, but can be executed at different times. The execution order of these steps or stages does not necessarily have to be sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0150] Based on the same inventive concept, an embodiment of the present application also provides a data processing device for implementing the data processing method involved above. The implementation solutions provided by this device for solving problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the data processing device provided below can refer to the limitations on the data processing method in the above text, and will not be repeated here.

[0151] In an exemplary embodiment, as Figure 10 shown, a data processing device 1000 is provided, including: an acquisition module 1001, a determination module 1002, and an execution module 1003, where:

[0152] The acquisition module 1001 is configured to obtain a target product data set from a data mart, where the data mart stores multiple pieces of product data sent by a data management system, and the target product data set includes the multiple pieces of product data;

[0153] The determination module 1002 is configured to obtain the data volume of the target product data set, and determine whether the alarm condition is satisfied based on the data volume and the historical data volume of the historical product data set obtained within the historical period;

[0154] An execution module 1003, configured to perform an alarm operation if the alarm condition is satisfied; and perform product production based on the target product data set if the alarm condition is not satisfied.

[0155] In an alternative embodiment of the present application, the determination module 1002 is specifically configured to determine a data volume change rate based on the data volume and the historical data volume; and determine that the alarm condition is satisfied if the data volume change rate is greater than a preset change rate threshold.

[0156] In an alternative embodiment of the present application, the execution module 1003 is specifically configured to determine a target interval in which the data volume change rate is located among a plurality of data volume change rate intervals, and different data volume change rate intervals correspond to different alarm intensities; determine a target alarm intensity corresponding to the target interval according to the target interval, and perform an alarm according to the target alarm intensity.

[0157] In an alternative embodiment of the present application, the determination module 1002 is further configured to detect whether the data volume of the target product data set is greater than a preset data volume threshold; if so, perform the step of determining whether the alarm condition is satisfied based on the data volume and the historical data volume of the historical product data set obtained within a historical period; if not, perform the alarm operation.

[0158] In an alternative embodiment of the present application, the execution module 1003 is further configured to, after performing the alarm operation, re-obtain the target product data set by using the data management system and the data mart; perform data verification on the re-obtained target product data set, and stop performing the alarm operation if the verification passes.

[0159] In an alternative embodiment of the present application, the execution module 1003 is further configured to, in the case where the verification fails, determine the number of times of re-obtaining the target product data set by using the data management system and the data mart; if the number of times is less than a threshold number of times, continue to re-obtain the target product data set by using the data management system and the data mart, and perform data verification on the re-obtained target product data set; if the number of times is greater than or equal to the threshold number of times, continue to perform the alarm operation.

[0160] In an alternative embodiment of the present application, the execution module 1003 is specifically configured to obtain change data of the multiple product data sent in real time by the data management system through a communication interface; merge the target product data set and the change data to obtain merged data, and perform data verification on the merged data; and perform product production based on the merged data if the verification passes.

[0161] Each module in the above data processing device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or stored in the memory of the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0162] In an exemplary embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 11 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store product data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a data processing method.

[0163] In an exemplary embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 12As shown in the figure. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, near field communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a data processing method. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse, etc.

[0164] Those skilled in the art can understand that Figure 11 and Figure 12 the structure shown in the figure is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0165] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0166] Obtain a target product data set from a data mart. The data mart stores multiple product data sent by a data management system. The target product data set includes the multiple product data; obtain the data volume of the target product data set, and based on the data volume and the historical data volume of the historical product data set obtained within a historical period, determine whether the warning condition is met; if the warning condition is met, perform a warning operation; if the warning condition is not met, perform product production based on the target product data set.

[0167] In one embodiment, when the processor executes the computer program, the following steps are further implemented: determining a data volume change rate based on the data volume and the historical data volume; and determining that the alarm condition is satisfied when the data volume change rate is greater than a preset change rate threshold.

[0168] In one embodiment, when the processor executes the computer program, the following steps are further implemented: determining a target interval in which the data volume change rate is located among a plurality of data volume change rate intervals, where different data volume change rate intervals correspond to different alarm intensities; determining a target alarm intensity corresponding to the target interval according to the target interval, and performing an alarm according to the target alarm intensity.

[0169] In one embodiment, when the processor executes the computer program, the following steps are further implemented: detecting whether the data volume of the target product data set is greater than a preset data volume threshold; if so, performing the step of determining whether the alarm condition is satisfied based on the data volume and the historical data volume of the historical product data set obtained within a historical period; if not, performing the alarm operation.

[0170] In one embodiment, when the processor executes the computer program, the following steps are further implemented: after performing the alarm operation, re-obtaining the target product data set by using the data management system and the data mart; performing data verification on the re-obtained target product data set, and stopping performing the alarm operation when the verification passes.

[0171] In one embodiment, when the processor executes the computer program, the following steps are further implemented: when the verification fails, determining the number of times of re-obtaining the target product data set by using the data management system and the data mart; when the number of times is less than a number threshold, continuing to re-obtain the target product data set by using the data management system and the data mart, and performing data verification on the re-obtained target product data set; when the number of times is greater than or equal to the number threshold, continuing to perform the alarm operation.

[0172] In one embodiment, when the processor executes the computer program, the following steps are further implemented: obtaining change data of the multiple product data sent by the data management system in real time through a communication interface; merging the target product data set and the change data to obtain merged data, and performing data verification on the merged data; and performing product production based on the merged data when the verification passes.

[0173] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0174] Obtain a target product data set from a data mart, where the data mart stores multiple product data sent by a data management system, and the target product data set includes the multiple product data; obtain the data volume of the target product data set, and determine whether an alarm condition is satisfied based on the data volume and the historical data volume of the historical product data set obtained within a historical period; if the alarm condition is satisfied, perform an alarm operation; if the alarm condition is not satisfied, perform product production based on the target product data set.

[0175] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: determine a data volume change rate based on the data volume and the historical data volume; in the case where the data volume change rate is greater than a preset change rate threshold, determine that the alarm condition is satisfied.

[0176] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: determine a target interval in which the data volume change rate is located among multiple data volume change rate intervals, and different data volume change rate intervals correspond to different alarm intensities; determine the target alarm intensity corresponding to the target interval according to the target interval, and perform an alarm according to the target alarm intensity.

[0177] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: detect whether the data volume of the target product data set is greater than a preset data volume threshold; if so, perform the step of determining whether the alarm condition is satisfied based on the data volume and the historical data volume of the historical product data set obtained within a historical period; if not, perform the alarm operation.

[0178] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: after performing the alarm operation, use the data management system and the data mart to re-obtain the target product data set; perform data verification on the re-obtained target product data set, and stop performing the alarm operation when the verification passes.

[0179] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: in the case where the verification fails, determine the number of times of re-obtaining the target product data set using the data management system and the data mart; in the case where the number of times is less than a threshold number of times, continue to use the data management system and the data mart to re-obtain the target product data set, and perform data verification on the re-obtained target product data set; in the case where the number of times is greater than or equal to the threshold number of times, continue to perform the alarm operation.

[0180] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtaining, through a communication interface, change data for the multiple product data sent in real time by the data management system; merging the target product data set and the change data to obtain merged data, and performing data verification on the merged data; and based on the merged data, performing product production when the verification is passed. In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the following steps:

[0181] Obtaining a target product data set from a data mart, where the data mart stores multiple product data sent by a data management system, and the target product data set includes the multiple product data; obtaining the data volume of the target product data set, and determining whether an alarm condition is satisfied based on the data volume and the historical data volume of a historical product data set obtained within a historical period; if the alarm condition is satisfied, performing an alarm operation; if the alarm condition is not satisfied, performing product production based on the target product data set.

[0182] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: determining a data volume change rate based on the data volume and the historical data volume; and determining that the alarm condition is satisfied when the data volume change rate is greater than a preset change rate threshold.

[0183] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: determining a target interval in which the data volume change rate is located among multiple data volume change rate intervals, where different data volume change rate intervals correspond to different alarm intensities; determining a target alarm intensity corresponding to the target interval according to the target interval, and performing an alarm according to the target alarm intensity.

[0184] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: detecting whether the data volume of the target product data set is greater than a preset data volume threshold; if so, performing the step of determining whether the alarm condition is satisfied based on the data volume and the historical data volume of a historical product data set obtained within a historical period; if not, performing the alarm operation.

[0185] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: after performing the alarm operation, re-obtaining the target product data set by using the data management system and the data mart; performing data verification on the re-obtained target product data set, and stopping performing the alarm operation when the verification is passed.

[0186] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: when the verification fails, determine the number of times of re-acquiring the target product data set by using the data management system and the data mart; when the number is less than the number threshold, continue to re-acquire the target product data set by using the data management system and the data mart, and perform data verification on the re-acquired target product data set; when the number is greater than or equal to the number threshold, continue to perform the warning operation.

[0187] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: obtain the change data for the multiple product data sent in real time by the data management system through the communication interface; merge the target product data set and the change data to obtain merged data, and perform data verification on the merged data; when the verification passes, perform product production based on the merged data.

[0188] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0189] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope recorded in the present application.

[0190] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A data processing method, characterized in that: The method comprises: Acquire a target product data set from a data mart, wherein the data mart stores a plurality of product data sent by a data management system, and the target product data set includes the plurality of product data; Acquire the data volume of the target product data set, and determine whether an alarm condition is met based on the data volume and the historical data volume of the historical product data set acquired in a historical period; If the alarm condition is met, the alarm operation is performed; If the alarm condition is not met, product production is performed based on the target product data set.

2. The method according to claim 1, characterized in that The determining whether the alarm condition is met based on the data volume and the historical data volume of the historical product data set acquired in the historical period includes: Determining a data volume change rate based on the data volume and the historical data volume; When the data volume change rate is greater than a preset change rate threshold, it is determined that the alarm condition is met.

3. The method according to claim 2, characterized in that If the alarm condition is met, the alarm operation is performed, including: Determine a target interval in which the data volume change rate is located among a plurality of data volume change rate intervals, where different data volume change rate intervals correspond to different alarm intensities; A target alarm intensity corresponding to the target interval is determined according to the target interval, and an alarm is issued according to the target alarm intensity.

4. The method according to claim 1, characterized in that The method further comprises: Detecting whether the data volume of the target product data set is greater than a preset data volume threshold; If so, a step of determining whether an alarm condition is satisfied based on the data volume and the historical data volume of the historical product data set acquired within the historical period is performed; If not, the alarm operation is performed.

5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: After executing the alarm operation, reacquiring the target product data set by using the data management system and the data mart; The target product data set that is reacquired is subjected to data verification, and if the verification passes, the alarm operation is stopped.

6. The method according to claim 5, characterized in that The method further comprises: If the verification fails, determining the number of times the target product data set is re-acquired using the data management system and the data mart; When the number of times is less than the number threshold, continue to use the data management system and the data mart to re-acquire the target product data set, and perform data verification on the re-acquired target product data set; When the number is greater than or equal to the number threshold, continue to perform the alarm operation.

7. The method according to claim 1, characterized in that The producing the product based on the target product data set includes: Acquire, through a communication interface, change data for the plurality of product data sent in real time by the data management system; Merging the target product data set and the change data to obtain merged data, and performing data verification on the merged data; When the verification is passed, product production is carried out based on the combined data.

8. A data processing device, characterized in that: The device comprises: An acquisition module, configured to acquire a target product data set from a data mart, wherein the data mart stores a plurality of product data sent by a data management system, and the target product data set includes the plurality of product data; A determination module, configured to obtain the data volume of the target product data set, and determine whether an alarm condition is met based on the data volume and the historical data volume of the historical product data set obtained within a historical period; The execution module is used to execute the alarm operation if the alarm condition is met; if the alarm condition is not met, perform product production based on the target product data set.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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