Data processing method, data processing model, system and computing device

Abstract

The embodiment of the present application provides a data processing method, a data processing model, a system and a computing device. The method includes the following steps: obtaining data generated in a data processing event; converting the data into patterned information corresponding to a preset mode in a preset data processing model; supplementing dimension information for the patterned information according to the event record of the data processing event; wherein the dimension information is the basis for determining whether the patterned information belongs to the processing object of a processing task. The technical solution provided by the embodiment of the present application has a higher versatility in the data processing process; even if the business changes, the previously generated patterned information will not be affected. In addition, supplementing the patterned information with dimensional information is, firstly, to facilitate subsequent data processing, such as data accounting, auditing, etc.; secondly, it is easy to map to specific accounting subjects to access the existing data accounting system.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a data processing method, a data processing model, a system and a computing device. Background Art

[0002] Financial accounting is an important part of business management. The so-called accounting is to reflect the business situation in the form of accounting subjects, such as how much receivables occurred this month, how much actual payment was received, how much revenue was confirmed, etc. At the same time, each accounting subject can be refined, for example, receivables can be classified or receivables from a key customer can be separately summarized.

[0003] The more diversified and complex the business of an enterprise is, the greater the challenge of financial accounting will be. In the existing accounting scheme, the accounting subjects are closely related to the actual business; once the business of the enterprise is adjusted, it is very likely that the accounting subjects will need to be adjusted adaptively; this will bring many problems. Obviously, the existing accounting scheme can no longer adapt to the scenario of rapid development of existing business. Summary of the invention

[0004] The embodiments of the present application provide a data processing method, a data processing model, a system and a computing device that solve or partially solve the problems existing in the prior art.

[0005] In one embodiment of the present application, a data processing method is provided. The method comprises:

[0006] Get the data generated in the data processing event;

[0007] Converting the data into patterned information corresponding to a preset pattern in a preset data processing model;

[0008] Supplementing dimension information for the patterned information according to the event record of the data processing event;

[0009] The dimension information is the basis for determining whether the patterned information belongs to the processing object of a processing task.

[0010] In another embodiment of the present application, a data processing model is provided. The data processing model is used to convert input data into patterned information corresponding to a preset mode; wherein the data processing model includes a conversion unit; the conversion unit includes at least one model domain; the model domain includes at least one preset mode; each model domain in the at least one model domain corresponds to a domain category; each preset mode in the at least one preset mode corresponds to a category, and provides corresponding data conversion rules for the input data.

[0011] In another embodiment of the present application, a data processing system is provided. The data processing system includes:

[0012] The server is used to provide various types of transaction services and record various data processing events;

[0013] A first processing device, connected to the server, for generating corresponding accounting vouchers for data processing events;

[0014] a second processing device, arranged between the server and the first processing device, for converting data generated in a data processing event into patterned information corresponding to a preset mode in a preset data processing model; after supplementing dimension information for the patterned information according to an event record of the data processing event, sending the patterned information to the first processing device, so that the first processing device generates a corresponding accounting voucher based on the patterned information;

[0015] The dimension information is the basis for determining whether the patterned information belongs to the processing object of an accounting processing task.

[0016] In another embodiment of the present application, a data processing method is provided. The method comprises:

[0017] acquiring data from at least one data processing system;

[0018] Performing pattern processing on the data to obtain first pattern information;

[0019] Adding dimension information to the first patterned information based on association information related to the data;

[0020] Determine a corresponding data processing category for adding the first schematized information of the dimension information;

[0021] Perform a processing operation corresponding to the data processing category on the first patterned information.

[0022] In another embodiment of the present application, a data processing method is provided. The method comprises:

[0023] In response to a data query event, determining target dimension information specified in the data query event;

[0024] Acquire at least one patterned information added with the target dimension information;

[0025] Based on the at least one patterned information, a corresponding data report is generated.

[0026] In another embodiment of the present application, a data processing method is provided. The method comprises:

[0027] In response to an execution instruction of a data processing task, obtaining a data processing category specified by the data processing task;

[0028] Acquire at least one schematized information that has a mapping relationship with the data processing category;

[0029] A processing operation corresponding to the data processing category is performed on the at least one patterned information to generate a corresponding data report.

[0030] In another embodiment of the present application, a data processing method is provided. The method comprises:

[0031] In response to an execution instruction of a data audit task, obtaining two target preset modes having an associated relationship specified by the audit task;

[0032] Respectively obtaining pattern information corresponding to the two target preset modes;

[0033] Perform data audit on all acquired patterned information to obtain processing results.

[0034] In another embodiment of the present application, a computing device is provided. The computing device includes a memory and a processor, wherein:

[0035] The memory is used to store programs;

[0036] The processor is coupled to the memory and is configured to execute the program stored in the memory to:

[0037] Get the data generated in the data processing event;

[0038] Converting the data into patterned information corresponding to a preset pattern in a preset data processing model;

[0039] Supplementing dimension information for the patterned information according to the event record of the data processing event;

[0040] The dimension information is the basis for determining whether the patterned information belongs to the processing object of a processing task.

[0041] In another embodiment of the present application, a computing device is provided. The computing device includes a memory and a processor, wherein:

[0042] The memory is used to store programs;

[0043] The processor is coupled to the memory and is configured to execute the program stored in the memory to:

[0044] acquiring data from at least one data processing system;

[0045] Performing pattern processing on the data to obtain first pattern information;

[0046] Adding dimension information to the first patterned information based on association information related to the data;

[0047] Determine a corresponding data processing category for adding the first schematized information of the dimension information;

[0048] Perform a processing operation corresponding to the data processing category on the first patterned information.

[0049] In another embodiment of the present application, a computing device is provided. The computing device includes a memory and a processor, wherein:

[0050] The memory is used to store programs;

[0051] The processor is coupled to the memory and is configured to execute the program stored in the memory to:

[0052] In response to a data query event, determining target dimension information specified in the data query event;

[0053] Acquire at least one patterned information added with the target dimension information;

[0054] Based on the at least one patterned information, a corresponding data report is generated.

[0055] In another embodiment of the present application, a computing device is provided. The computing device includes a memory and a processor, wherein:

[0056] The memory is used to store programs;

[0057] The processor is coupled to the memory and is configured to execute the program stored in the memory to:

[0058] In response to an execution instruction of a data processing task, obtaining a data processing category specified by the data processing task;

[0059] Acquire at least one schematized information that has a mapping relationship with the data processing category;

[0060] A processing operation corresponding to the data processing category is performed on the at least one patterned information to generate a corresponding data report.

[0061] In another embodiment of the present application, a computing device is provided. The computing device includes a memory and a processor, wherein:

[0062] The memory is used to store programs;

[0063] The processor is coupled to the memory and is configured to execute the program stored in the memory to:

[0064] In response to an execution instruction of a data audit task, obtaining two target preset modes having an associated relationship specified by the audit task;

[0065] Respectively obtaining pattern information corresponding to the two target preset modes;

[0066] Perform data audit on all acquired patterned information to obtain processing results.

[0067] The technical solution provided by an embodiment of the present application converts the data generated in the data processing event into patterned information by presetting a data processing model that is not related to the business. Since the data processing process is separated from the accounting subjects that are strongly related to the business, the versatility of the data processing process is higher. Even if the business changes, the previously generated patterned information will not be affected. In addition, the dimensional information is supplemented for the patterned information, firstly, to facilitate subsequent data processing, such as data accounting, auditing, etc.; secondly, to facilitate mapping to specific accounting subjects to access the existing data accounting system. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0069] Figure 1 This is a schematic diagram of the existing financial accounting system architecture;

[0070] Figure 2 A flowchart of a data processing method provided in one embodiment of the present application;

[0071] Figure 3 A schematic diagram of a topological structure of an implementation example of a data processing model provided by an embodiment of the present application;

[0072] Figure 4 A schematic diagram of a data processing model according to an embodiment of the present invention;

[0073] Figure 5 A schematic diagram of a data processing system provided in one embodiment of the present application;

[0074] Figure 6A flowchart of a data processing method provided by another embodiment of the present application;

[0075] Figure 7 A flowchart of a data processing method provided in yet another embodiment of the present application;

[0076] Figure 8 A flowchart of a data processing method provided in yet another embodiment of the present application;

[0077] Fig. 9 A flowchart of a data processing method provided in yet another embodiment of the present application;

[0078] Fig.10 A schematic diagram of the structure of a data processing device provided in one embodiment of the present application;

[0079] Fig.11 A schematic diagram of the structure of a data processing device provided in another embodiment of the present application;

[0080] Fig.12 A schematic diagram of the structure of a data processing device provided in yet another embodiment of the present application;

[0081] Fig.13 A schematic diagram of the structure of a data processing device provided in yet another embodiment of the present application;

[0082] Fig.14 A schematic diagram of the structure of a data processing device provided in yet another embodiment of the present application;

[0083] Fig.15 A schematic diagram of the structure of a computing device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0084] The business of existing enterprises is becoming more diversified and complex, which poses a huge challenge to financial accounting. The biggest challenge is the diversity of business. New businesses are springing up like mushrooms after rain, which poses a huge challenge to the rapid access and accuracy of financial accounting. At the same time, the huge amount of data is also a challenge to complete detailed accounting.

[0085] For financial accounting, the most common way is through traditional ERP systems, such as SAP, Oracle, Kingdee, etc. However, its financial accounting capabilities are not provided separately, but included in its various business modules, such as accounts receivable, accounts payable, inventory, procurement, sales, etc. It is more suitable for the internal management needs of enterprises, but cannot quickly support complex upstream businesses. Figure 1Another commonly used implementation scheme is shown, which is to establish an accounting engine module; convert the business data of different upstream business systems and financial related systems (such as accounts receivable system, accounts payable system, etc.) into accounting subjects, and then generate accounting vouchers, and then send the accounting vouchers to the database for corresponding accounting. Because accounting subjects are closely related to business, Figure 1 The solution shown can also be called a business chimney access solution, which brings about low access efficiency and high maintenance costs. Once the upstream business changes or the accounting subjects are adjusted, the impact is huge. At the same time, the data provided to the accounting engine module by different upstream business systems is already summary dimension data, so it is impossible to perform detailed level accounting and detailed level income cost accounting.

[0086] To this end, various embodiments of the present application are proposed to provide a solution with good versatility to cope with the rapid development of enterprise business. In order to enable people in the technical field to better understand the solution of the present application, the technical solution in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application.

[0087] In some processes described in the specification, claims and the above-mentioned figures of this application, multiple operations appearing in a specific order are included, and these operations may not be executed or executed in parallel in the order in which they appear in this article. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit "first" and "second" to different types. In addition, the following embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0088] Figure 2 FIG. 1 is a flow chart showing a data processing method provided by an embodiment of the present application. Figure 2 As shown, the method includes:

[0089] 101. Get the data generated in the data processing event.

[0090] 102. Convert the data into patterned information corresponding to a preset pattern in a preset data processing model.

[0091] 103. Supplement dimension information for the patterned information according to the event record of the data processing event.

[0092] The dimension information is the basis for determining whether the patterned information belongs to the processing object of an accounting processing task.

[0093] In the above 101, the data processing event can be simply understood as: the event that the user pays or prepays the corresponding remuneration for the service provided by the service provider through the application client, or the event that the third-party service provider needs to pay the corresponding remuneration to the first service provider for providing services to the user through the service platform provided by the first service provider, etc. This embodiment does not specifically limit this. The data processing event may include but is not limited to: transaction amount, transaction event description information, etc.; for example, *** account successfully received 100, confirmed income 100, etc.

[0094] In the above 102, the data processing model includes at least one model domain; the model domain contains at least one preset mode. In an achievable technical solution, this step 102 "based on the data processing model, converting the data into patterned information corresponding to a preset mode in the data processing model" can specifically include the following steps:

[0095] 1021. In the at least one model domain, determine a target model domain to which the data belongs.

[0096] 1022. Determine an adapted target preset mode for the data in at least one preset mode contained in the target model domain.

[0097] 1023. Convert the data into pattern information corresponding to the target preset mode.

[0098] In a specific implementation, each model domain included in the data processing model may correspond to a domain category. Accordingly, the above step 1021 "determine the target model domain to which the data belongs in the at least one model domain" may specifically include:

[0099] S11. Identify the domain category to which the data belongs.

[0100] It should be noted here that the process of identifying the data can be simply understood as the recognition of the semantics of the data. Assuming that in the financial accounting application scenario, the recognition of data can be understood as: the recognition of the financial semantics of the data. As shown in Table 1 below:

[0101] Table 1: Financial semantics corresponding to different data

[0102]

[0103] In addition, different revenue recognition methods or payment methods will also reflect different financial semantics:

[0104] For example, for deferred revenue recognition, when confirming receipt, the financial semantics is to debit customer receivables of 100 and credit deferred revenue of 100; when deferred revenue of 10 is recognized in each period, the financial semantics is to debit deferred revenue of 10, credit revenue of 9.4, and tax of 0.6.

[0105] For another example, if the actual collection is not made through **payment tools but through the use of advance payment deduction, the financial meaning is to credit the customer's receivables of 100 and debit the advance payment of 100.

[0106] It should be noted here that the data identification mentioned in this embodiment can be achieved by referring to the technical means in the prior art, and this embodiment does not make any specific limitation on this.

[0107] Furthermore, based on the financial semantics of the data, the domain category to which the data belongs can be determined. For example, the financial semantics of the above data "confirm receipt of 100" is "borrow customer receivables 100", and it can be determined that the domain category to which the data belongs is the order domain. See the example shown in Table 2 below:

[0108] Table 2: Correspondence between data, financial semantics and domain categories

[0109]

[0110] In specific implementation, the correspondence between financial semantics and domain categories can be pre-configured, and by querying the correspondence, the domain category to which a certain data belongs can be obtained. Alternatively, based on a pre-set calculation model (such as a neural network model), the financial semantics of the data is used as the input of the calculation model, and the domain category to which the data belongs can be obtained by executing the calculation model. Of course, other methods can also be used for implementation, and this embodiment does not specifically limit this.

[0111] S12: Use the model domain in the at least one model domain that corresponds to the financial classification category to which the data belongs as the target model domain.

[0112] Furthermore, each preset mode contained in the model domain corresponds to a category. Accordingly, the above step 1022 "determine an adapted target preset mode for the data in at least one preset mode contained in the target model domain" can be implemented by the following steps:

[0113] S21. Identify the item category to which the data belongs.

[0114] S22. Using, among at least one preset mode contained in the target model domain, a preset mode corresponding to the financial item to which the data belongs as the template preset mode.

[0115] Similarly, the identification of data in S21 above may be semantic identification of data. For example, in a financial accounting application scenario, the financial semantics of the data are identified; then, based on the result of the financial semantic identification, the item category to which the data belongs is determined.

[0116] For example, the financial meaning of the above data "Confirm receipt of goods 100" is "Debit customer receivable 100", and it can be determined that the item category to which the data belongs is the receivables under the order domain. See the example shown in Table 3 below:

[0117] Table 3: Correspondence between data, financial semantics, domain categories, and item categories

[0118]

[0119] Although there are many different business systems in specific application scenarios, they all contain specific financial semantics. For example, e-commerce transaction systems, whether they are self-operated or platform-based, all involve revenue. Other management systems will involve procurement and expenses. Therefore, based on the analysis of actual business, multiple domain categories can be divided, such as: revenue domain, prepayment domain, expense domain, organization domain, settlement domain, prepaid domain, etc. Each domain category can contain one or more preset modes corresponding to item categories.

[0120] In a specific implementation, the data processing model in this embodiment can be characterized as Figure 3 The structure shown. Figure 3 As shown, the data processing model includes at least one model domain among the following: income domain, prepayment domain, expense domain, organization domain, settlement domain, and prepaid domain. The income domain contains at least one preset mode among the following: receivables mode, collection order mode, and receivables allocation mode. The prepayment domain contains at least one preset mode among the following: income transfer mode, prepayment receivables mode, prepayment usage record mode, and prepayment collection order mode. The expense domain contains at least one preset mode among the following: expense order mode, payable order mode. The settlement domain contains at least one preset mode among the following: payment order mode, payable order mode. The prepaid domain contains at least one preset mode among the following: prepayment payable order mode, and prepayment usage record mode. The organization domain contains: at least one third-party service provider's running order mode.

[0121] Continue to see Figure 3 As shown, an association relationship may be configured between two preset modes belonging to different model domains, so as to utilize the association relationship to perform data audit tasks between the two different model domains.

[0122] For example, Figure 3 In the example shown, the data processing model contains at least one of the following relationships:

[0123] There is a transfer relationship between the expense order model and the receivable allocation model;

[0124] There is a reduction relationship between the collection order mode and the payment order mode;

[0125] The payment receipt mode and the pre-collection usage record mode have a pre-collection relationship;

[0126] The collection order model and the third-party service provider's transaction order model have an institutional collection relationship;

[0127] The receipt mode and the prepaid usage record mode have a prepaid relationship;

[0128] The payment order mode has an institutional payment relationship with the prepaid usage record mode;

[0129] There is an institutional payment relationship between the payment order model and the third-party service provider's transaction order model;

[0130] There is an institutional collection relationship between the prepayment receipt and the third-party service provider's transaction slip model.

[0131] In the above 103, the event record of the data processing event may include but is not limited to: transaction time, event-related party information, transaction object, etc. Suppose that a user purchases a product through the network service provided by the service provider; then the event-related party information includes: the user's identifier (such as user login name, etc.) and the business identifier to which the network service belongs. For another example, a merchant opens a store on the service platform provided by the service provider, and the merchant needs to pay the corresponding usage fee for using the service platform; then the event-related party information includes: the merchant's identifier (such as the merchant's registered name, etc.) and the business identifier to which the service platform belongs.

[0132] In an achievable technical solution, the above step 103 of "supplementing dimension information to the schematized information according to the event record of the data processing event" may specifically include the following steps:

[0133] 1031. Extracting information of parties involved in the event from the event record of the data processing event;

[0134] 1032. Use the information of parties involved in the event as dimension information to supplement the patterned information.

[0135] The technical solution provided in this embodiment converts the account-related data generated in the data processing event into patterned information by presetting a data processing model that is not related to the business. Since the data processing process is separated from the accounting subjects that are strongly related to the business, the versatility of the data processing process is higher. Even if the business changes, the previously generated patterned information will not be affected. In addition, the patterned information is supplemented with dimensional information, which is convenient for subsequent data processing, such as data accounting, auditing, etc., and is easy to map to specific accounting subjects to access the existing data accounting system.

[0136] Furthermore, the method provided in this embodiment may also include the following steps:

[0137] 104. In response to an execution instruction of a data audit task, two target preset modes that are in an associated relationship and specified by the audit task are obtained.

[0138] 105. Obtain the patterning information corresponding to the two target preset modes respectively.

[0139] 106. Perform data audit on all acquired patterned information to obtain processing results.

[0140] Assume that the two target preset modes specified by the audit task are related to each other, namely: the receipt mode and the third-party service provider (such as a bank) statement mode; then all the patterned information converted into the receipt mode and all the patterned information converted into the third-party service provider (such as a bank) statement mode are obtained; then the patterned information of the receipt mode and the patterned information of the third-party service provider (such as a bank) statement mode are subjected to data audit processing.

[0141] In the technical solution provided in this embodiment, the established data processing models include income domain, prepayment domain, expense domain, prepayment domain and institution domain, and by establishing associations between some preset patterns in each domain, auditing between domains can be achieved.

[0142] Furthermore, the method provided in this embodiment may also include the following steps:

[0143] 107. In response to an execution instruction of an accounting task, obtain target dimension information specified by the accounting task.

[0144] 108. Obtain all schematized information having the target dimension information.

[0145] 109. Aggregate all the acquired patterned information and generate accounting reports.

[0146] Assuming that the target dimension information specified by the accounting task is a certain merchant ID, all the patterned information supplemented with the merchant ID is obtained, and then all the patterned information of the merchant ID is aggregated to obtain the corresponding accounting report. It can be seen that by adopting the technical solution provided by this embodiment, by setting the dimension information, the patterned information can be processed at a detailed level (such as financial accounting), which helps to perform automatic red-offset operations according to the transformation of upstream business data across account periods.

[0147] Of course, in specific implementation, the target dimension information specified by the accounting task can also be two, three, four, etc.; this embodiment does not make specific limitations on this.

[0148] Furthermore, the method provided in this embodiment may also include the following steps:

[0149] 110. Determine the accounting subject based on the dimensional information.

[0150] 111. Generate accounting vouchers corresponding to the accounting subjects based on the schematized information and the dimensional information.

[0151] In specific implementation, the correspondence between dimension information and accounting subjects may be preset. Accordingly, the above step 110 may be specifically: according to the preset correspondence between dimension information and accounting subjects, the accounting subject corresponding to the dimension information is obtained. For example, the dimension information includes: the business identifier of the service platform and the transaction object (i.e., the commission income of the service platform), and the corresponding accounting subject may be: the general ledger accounting subject.

[0152] It should be noted here that: regarding the creation of accounting subjects, please refer to the relevant content in the prior art, and this article does not make any specific limitations on this.

[0153] Figure 4 The schematic diagram of the principle architecture of the data processing model provided by an embodiment of the present application is shown. The data processing model is used to convert input data into patterned information corresponding to a preset mode. Figure 3 and Figure 4 As shown, the data processing model includes a conversion unit. The conversion unit includes at least one model domain; each model domain includes at least one preset mode; wherein each model domain in the at least one model domain corresponds to a domain category; each preset mode in the at least one preset mode corresponds to a category, and provides corresponding data conversion rules for the input data.

[0154] The data processing model provided by the technical solution of this embodiment converts the data generated in the data processing event into patterned information; because this model is separated from the accounting subjects that are strongly related to the business, the data processing process is more versatile; even if the business changes, the previously generated patterned information will not be affected. The data processing model provided by this embodiment is used for financial accounting, which is more versatile and easier to implement detailed data accounting.

[0155] Furthermore, an association relationship is configured between two preset modes belonging to different model domains, so as to perform the data audit task between the two different model domains by using the association relationship. Figure 3 Example shown:

[0156] The data processing model includes at least one model domain among the following: income domain, pre-collection domain, expense domain, organization domain, settlement domain, and pre-payment domain;

[0157] The income domain includes at least one of the following preset modes: a receivables mode, a collection mode, and a receivables allocation mode;

[0158] The pre-collection domain includes at least one of the following preset modes: transfer income mode, pre-collection receivables mode, pre-collection usage record mode, and pre-collection receipt mode;

[0159] The expense domain includes at least one of the following preset modes: expense order mode, payable order mode;

[0160] The settlement domain includes at least one of the following preset modes: a payment order mode and a payable order mode;

[0161] The prepaid domain includes at least one of the following preset modes: a prepaid bill mode and a prepaid usage record mode;

[0162] The organization domain includes: a flow sheet mode of at least one third-party service provider.

[0163] Continue to see Figure 3 In the example shown, the data processing model contains at least one of the following relationships:

[0164] There is a transfer relationship between the expense order model and the receivable allocation model;

[0165] There is a reduction relationship between the collection order mode and the payment order mode;

[0166] The payment receipt mode and the pre-collection usage record mode have a pre-collection relationship;

[0167] The collection order model and the third-party service provider's transaction order model have an institutional collection relationship;

[0168] The receipt mode and the prepaid usage record mode have a prepaid relationship;

[0169] The payment order mode has an institutional payment relationship with the prepaid usage record mode;

[0170] There is an institutional payment relationship between the payment order model and the third-party service provider's transaction order model;

[0171] There is an institutional collection relationship between the prepayment receipt and the third-party service provider's transaction slip model.

[0172] Furthermore, the data processing model provided in this embodiment may also include: a supplementing unit. The supplementing unit is used to supplement dimension information for the patterned information according to the event record of the data processing event. The dimension information is the basis for determining whether the patterned information belongs to the processing object of a processing task; and the data converted into the patterned information is generated in the data processing event.

[0173] Furthermore, the data processing model provided in this embodiment may also include: an accounting unit and / or an auditing unit. The accounting unit is used to respond to an execution instruction of an accounting task, obtain the target dimension information specified by the accounting task; obtain all the patterned information having the target dimension information; aggregate all the acquired patterned information to generate an accounting report. The auditing unit is used to respond to an execution instruction of a data auditing task, obtain two target preset patterns with an associated relationship specified by the auditing task; respectively obtain the patterned information corresponding to each of the two target preset patterns; perform data auditing on all the acquired patterned information to obtain a processing result.

[0174] Figure 5 FIG. 1 shows a schematic diagram of the structure of a data processing system provided by an embodiment of the present application. Figure 4 As shown, the data processing system provided in this embodiment includes:

[0175] The server 201 is used to provide various types of transaction services and record various data processing events;

[0176] A first processing device 202, connected to the server, for generating corresponding accounting vouchers for data processing events;

[0177] The second processing device 203 is arranged between the server and the first processing device, and is used to convert the data generated in the data processing event into patterned information corresponding to a preset mode in the preset data processing model; after supplementing the patterned information with dimension information according to the event record of the data processing event, the patterned information is sent to the first processing device, so that the first processing device generates a corresponding accounting voucher based on the patterned information;

[0178] The dimension information is the basis for determining whether the patterned information belongs to the processing object of a processing task.

[0179] In a specific implementation, the server can be a service cluster composed of multiple servers, on which multiple business systems are deployed to provide corresponding categories of services. The first processing device and the second processing device can be two virtual devices deployed on the same physical device, or two different physical devices, which is not specifically limited in this embodiment.

[0180] It should be added here that: the second processing device in this embodiment can also realize other functions mentioned in the above embodiments, and the details can be found in the above description.

[0181] The first processing device may be deployed with an accounting engine module in the prior art. Figure 1 It can be seen that the difference of the technical solution provided by this embodiment is that a second processing device is added before the first processing device to complete the conversion process of the data generated in the data processing event to the patterned information corresponding to the preset mode (also called standardized information with stronger universality) through the data processing model. Because the second processing device only performs pattern conversion on the data, detailed data calculation can be achieved during data calculation. The comparison between the technical solution provided by this embodiment and the traditional method is as follows:

[0182] Traditional ERP (Enterprise Resource Planning) systems can comprehensively balance and optimize the management of an enterprise's comprehensive resources, including people, finance, information, time and space; however, the financial accounting capabilities of the ERP system are not provided separately, but are included in its various business systems, that is, the business and accounting relationships are coupled, and its applicable scenarios are relatively few; however, the access cost of each business system to the ERP system is low, and the maintenance cost is low; but the scalability of the ERP system is low.

[0183] Figure 1 The prior art shown, in order to support various complex businesses of the enterprise, adopts the idea of ​​separation of business and accounting (i.e., decoupling the relationship between business and accounting), and converts the data generated by different upstream business systems and financial-related systems (such as accounts receivable system, accounts payable system, etc.) into accounting subjects through the accounting engine module, and then generates accounting vouchers to be sent to the database. Figure 1 The existing technology shown has more applicable scenarios than the ERP system; however, the problems brought about by this implementation method are high access efficiency and high maintenance cost; once the upstream business system is changed or the accounting subjects are adjusted, the impact caused is huge. Figure 1 The scalability of the existing technology shown is higher than that of traditional ERP systems.

[0184] The technical solution provided in this embodiment is also based on the idea of ​​separation of business and accounting (i.e. decoupling of business and accounting), but Figure 1 The prior art shown in the figure adds a processing process of converting data into patterned information, shielding the accounting subjects that are closely related to the business. Even if the business changes, the previously generated patterned information will not be affected; compared with ERP systems and Figure 1 The existing technology shown in the figure, the technical solution provided in this embodiment has more applicable scenarios, and its maintenance cost and access cost are between ERP system and Figure 1 However, the scalability of the technical solution provided by this embodiment is the highest; specifically, it is manifested in: Figure 1 In the prior art shown, the data of the upstream business system has become data of summary dimension after being processed by the accounting engine module, which brings many limitations and makes it impossible to perform detailed-level accounting. However, the technical solution provided by this embodiment obtains patterned information after the data of the upstream business system is processed. This patterned information can be used for detailed-level accounting, and automatic red-offset processing can be performed according to the changes of the upstream business data across account periods, and account summary processing can also be performed, etc.

[0185] In summary, the technical solutions provided by the embodiments of the present application are based on data processing models, can provide more adaptable scenarios, have lower access and maintenance costs, and better scalability. In addition, the present application does not specifically limit what computer language is used for implementation and what software and hardware is used for implementation.

[0186] The technical solutions provided in the above embodiments mainly involve the field of financial applications. In fact, they can also be applied to other application fields that are highly related to actual business, so as to convert the original data that is highly related to the business into standard patterned information; and then supplement the patterned information with dimensional information, firstly, to facilitate subsequent data processing; secondly, to facilitate mapping to specific business scenarios so as to access the existing business processing system.

[0187] Figure 6 A flow chart of a data processing method provided by an embodiment of the present application is shown. As shown in the figure, the data processing method includes:

[0188] 301. Obtain data from at least one data processing system.

[0189] 302. Perform pattern processing on the data to obtain first pattern information.

[0190] 303. Add dimension information to the first patterned information based on association information related to the data.

[0191] 304. Determine a corresponding data processing category for adding the first schematized information of the dimensional information.

[0192] 305. Perform a processing operation corresponding to the data processing category on the first patterned information.

[0193] In the above 301, the data processing system may be Figure 1 or Figure 5 The business systems shown in the figure, accounts receivable systems or accounts payable systems, etc. The acquired data may be data generated by various data processing systems, such as transaction data, etc.

[0194] In specific implementation, the above 301 can be implemented using a data processing model. That is, the above “performing pattern processing on the data to obtain the first pattern information” includes:

[0195] 3011. Obtain a data processing model.

[0196] 3022. Using the data processing model, convert the data into first patterned information corresponding to a preset pattern in the data processing model.

[0197] Among them, regarding the data processing model in the above 3011 and the content of the above step 3022, please refer to the contents in the above embodiments, which will not be repeated here.

[0198] In the above 303, the associated information related to the data may include: information of the event participants that generated the data, the time when the data was generated, etc. Assume that a user spends A price to buy a commodity through the network service provided by the service provider; the corresponding business system generates payment data A; the associated information related to the payment data A may include: payment time, the user's identifier (such as user login name, etc.), the business identifier to which the network service belongs, the commodity identifier, etc.

[0199] In a specific application scenario, such as a financial application scenario, the data processing category is an accounting subject. Accordingly, the above step 304 "determine the corresponding data processing category for adding the first schematized information of the dimension information" includes:

[0200] According to the dimension information, mapping out the accounting subject corresponding to the first patterned information to which the dimension information is added;

[0201] Accordingly, the method provided in this embodiment may further include the following steps:

[0202] 306. Generate a bookkeeping voucher corresponding to the accounting subject according to the first schematized information to which the dimensional information is added.

[0203] 307. Save the record certificate locally or send it to a database for retrieval.

[0204] In an implementable technical solution, the dimension information includes at least one dimension item; accordingly, the above step 305 of "performing a processing operation corresponding to the data processing category on the schematized information" may include:

[0205] 3051. Acquire at least one second schematized information added with the same dimension item as the first schematized information;

[0206] 3052. Perform accounting processing operations corresponding to the accounting categories on the first patterned information and the at least one second patterned information to obtain corresponding accounting reports.

[0207] The technical solution provided in this embodiment processes the data into patterned information that is irrelevant to the business, so as to weaken or eliminate the strong correlation between the data and the business; even if the business changes, the previously generated patterned information will not be affected. The data processing category is determined for the patterned information with added dimensional information in order to map it to a specific business scenario so as to access the existing business processing system (such as an accounting system).

[0208] Figure 7 A schematic diagram of a data processing method according to another embodiment of the present application is shown. Figure 2 The embodiment shown is implemented on the basis of the embodiment shown, that is, the patterned information mentioned in this embodiment is implemented using Figure 2 The technical solution provided in the embodiment shown is generated. Specifically, Figure 7 As shown, the method includes:

[0209] 401. In response to a data query event, determine target dimension information specified in the data query event.

[0210] 402. Obtain at least one patterned information added with the target dimension information.

[0211] 403. Generate a corresponding data report based on the at least one patterned information.

[0212] In the above 401, the data query event may be a report query event triggered by a user through a client. For example, the user enters the target dimension information to be queried through the report query page provided by the client, and then clicks the "Query" control on the page, thus completing the triggering of the report query event.

[0213] In the above 402, at least one patterned information can be obtained from the server.

[0214] In an achievable technical solution, the target dimension information includes at least one dimension item; accordingly, the above 403 “generating a corresponding data table based on the at least one schematized information” may specifically include:

[0215] Aggregation processing of at least one dimension item is performed on the at least one schematized information to generate the data table.

[0216] Furthermore, the method provided in this embodiment may also include:

[0217] 404. In response to a report format customization event, obtain a customized report format generated in the customized event;

[0218] 405. Save the custom report format.

[0219] The above report format customization event can be realized by the user through the custom configuration function provided by the client. For example, the user sets the report format through the custom configuration page provided by the client. After the custom report format is set, it can be saved locally for subsequent calls.

[0220] Furthermore, the above 403 “generating a corresponding data table based on the at least one schematized information” may include:

[0221] 4031. In response to a report format selection event, obtain a target report format specified by the report format selection event;

[0222] 4032. Generate a data report corresponding to the target report format based on the at least one patterned information.

[0223] In the above 4031, the candidate report formats may include a custom report format and / or a system default report format. The user may trigger the report format selection event by clicking, for example, the user clicks to open a drop-down list, the drop-down list displays at least one report format, and selects one of the report formats to complete the selection of the report format.

[0224] Figure 8 A schematic diagram of a data processing method according to another embodiment of the present application is shown. Figure 2 The embodiment shown is implemented on the basis of the embodiment shown, that is, the patterned information mentioned in this embodiment is implemented using Figure 2 The technical solution provided in the embodiment shown is generated. Specifically, Figure 8 As shown, the method includes:

[0225] 501. In response to an execution instruction of a data processing task, obtain a data processing category specified by the data processing task.

[0226] 502. Obtain at least one piece of schematized information that has a mapping relationship with the data processing category.

[0227] 503. Perform a processing operation corresponding to the data processing category on the at least one patterned information to generate a corresponding data report.

[0228] The technical solution provided in this embodiment can be applied to a variety of application scenarios. Assuming it is applied to a financial scenario, the above data processing category can be specifically an accounting subject.

[0229] In the above 502, the data processing category is related to the dimension information corresponding to the schema information, that is, the above “obtaining at least one schema information having a mapping relationship with the data processing category” may specifically include:

[0230] Acquire dimension information that has a mapping relationship with the data processing category;

[0231] At least one of the patterned information to which the dimension information is added is acquired.

[0232] Fig. 9 A schematic diagram of a data processing method provided by another embodiment of the present application is shown. The method provided in this embodiment 9 is Figure 2 The embodiment shown is implemented on the basis of the embodiment shown, that is, the patterned information mentioned in this embodiment is implemented using Figure 2 The technical solution provided in the embodiment shown is generated. Specifically, Fig. 9 As shown, the method includes:

[0233] 601. In response to an execution instruction of a data audit task, obtain two target preset modes that are in an associated relationship and specified by the audit task.

[0234] 602. Obtain the patterning information corresponding to the two target preset modes respectively.

[0235] 603. Perform data audit processing on all acquired patterned information to obtain processing results.

[0236] The patterned information is obtained by processing the data using a data processing model-a preset pattern;

[0237] The data processing model includes at least one model domain; the model domain contains at least one preset mode; and an association relationship is configured between two preset modes belonging to different model domains.

[0238] For the steps 601 to 603 above, please refer to the above Figure 2 The contents of steps 104 to 106 in the illustrated embodiment are not described in detail here.

[0239] Fig.10 FIG. 1 is a schematic diagram showing the structure of a data processing device provided by an embodiment of the present application. Fig.10As shown, the data processing device includes: an acquisition module 11, a conversion module 12 and a supplementing module 13. The acquisition module 11 is used to acquire data generated in a data processing event; the conversion module 12 is used to convert the data into patterned information corresponding to a preset mode in a preset data processing model; the supplementing module 13 is used to supplement the patterned information with dimension information according to the event record of the data processing event. The dimension information is the basis for determining whether the patterned information belongs to the processing object of an accounting processing task.

[0240] The technical solution provided in this embodiment converts the account-related data generated in the data processing event into patterned information by presetting a data processing model that is not related to the business. Since the data processing process is separated from the accounting subjects that are strongly related to the business, the versatility of the data processing process is higher. Even if the business changes, the previously generated patterned information will not be affected. In addition, the patterned information is supplemented with dimensional information, which is convenient for subsequent data processing, such as data accounting, auditing, etc., and is easy to map to specific accounting subjects to access the existing data accounting system.

[0241] Furthermore, the data processing model includes at least one model domain; the model domain contains at least one preset mode. Accordingly, the conversion module 12 is also used for:

[0242] In the at least one model domain, determining a target model domain to which the data belongs;

[0243] Determine an adapted target preset mode for the data in at least one preset mode contained in the target model domain;

[0244] The data is converted into patterned information corresponding to the target preset mode.

[0245] Furthermore, each model domain included in the data processing model corresponds to a domain category. Accordingly, the conversion module 12 is further used to: identify the domain category to which the data belongs; and use the model domain corresponding to the domain category to which the data belongs in the at least one model domain as the target model domain.

[0246] Furthermore, each preset mode contained in the model domain corresponds to a category. Accordingly, the conversion module 12 is also used to: identify the category of the item to which the data belongs; and use the preset mode corresponding to the category of the item to which the data belongs in at least one preset mode contained in the target model domain as the template preset mode.

[0247] Further, the data processing model includes at least one model domain among the following: income domain, pre-collection domain, expense domain, organization domain, settlement domain, and prepayment domain;

[0248] The income domain includes at least one of the following preset modes: a receivables mode, a collection mode, and a receivables allocation mode;

[0249] The pre-collection domain includes at least one of the following preset modes: transfer income mode, pre-collection receivables mode, pre-collection usage record mode, and pre-collection receipt mode;

[0250] The expense domain includes at least one of the following preset modes: expense order mode, payable order mode;

[0251] The settlement domain includes at least one of the following preset modes: a payment order mode and a payable order mode;

[0252] The prepaid domain includes at least one of the following preset modes: a prepaid bill mode and a prepaid usage record mode;

[0253] The organization domain includes: a flow sheet mode of at least one third-party service provider.

[0254] Furthermore, an association relationship is configured between two preset modes belonging to different model domains, so as to utilize the association relationship to perform a data audit task between the two different model domains.

[0255] Furthermore, the data processing model contains at least one of the following relationships:

[0256] There is a transfer relationship between the expense order model and the receivable allocation model;

[0257] There is a reduction relationship between the collection order mode and the payment order mode;

[0258] The payment receipt mode and the pre-collection usage record mode have a pre-collection relationship;

[0259] The collection order model and the third-party service provider's transaction order model have an institutional collection relationship;

[0260] The receipt mode and the prepaid usage record mode have a prepaid relationship;

[0261] The payment order mode has an institutional payment relationship with the prepaid usage record mode;

[0262] There is an institutional payment relationship between the payment order model and the third-party service provider's transaction order model;

[0263] There is an institutional collection relationship between the prepayment receipt and the third-party service provider's transaction slip model.

[0264] Furthermore, the data processing device provided in this embodiment may also include:

[0265] The first acquisition module is used to respond to an execution instruction of a data audit task, acquire two target preset modes that are in a correlation relationship and are specified by the audit task; and respectively acquire the pattern information corresponding to each of the two target preset modes;

[0266] The first processing module is used to perform data audit processing on all acquired patterned information to obtain processing results.

[0267] Furthermore, the data processing device provided in this embodiment may also include:

[0268] A second acquisition module is used to respond to an execution instruction of a calculation task, acquire the target dimension information specified by the calculation task; and acquire all patterned information having the target dimension information;

[0269] The second processing module is used to aggregate all the acquired patterned information and generate accounting reports.

[0270] Furthermore, the supplementing module is also used to: extract event-related party information from the event record of the data processing event; and use the event-related party information as dimensional information to supplement the patterned information.

[0271] Furthermore, the data processing device provided in this embodiment may also include:

[0272] A determination module, used for determining an accounting subject based on the dimension information;

[0273] A generation module is used to generate accounting vouchers corresponding to the accounting subjects according to the patterned information and the dimensional information.

[0274] It should be noted here that: the data acquisition device provided in the above embodiment can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be found in the corresponding contents in the above method embodiments, which will not be repeated here.

[0275] Fig.11 FIG. 2 shows a schematic diagram of the structure of a data processing device provided by another embodiment of the present application. Fig.11 As shown, the data processing device includes: an acquisition module 21, a processing module 22, an adding module 23 and a determining module 24.

[0276] An acquisition module 21, used to acquire data of at least one data processing system;

[0277] A processing module 22, configured to perform pattern processing on the data to obtain first pattern information;

[0278] An adding module 23, configured to add dimension information to the first patterned information based on association information related to the data;

[0279] A determination module 24, configured to determine a corresponding data processing category for the first schematized information to which the dimension information is added;

[0280] The processing module 22 is further configured to perform a processing operation corresponding to the data processing category on the first patterned information.

[0281] The technical solution provided in this embodiment processes the data into patterned information that is irrelevant to the business, so as to weaken or eliminate the strong correlation between the data and the business; even if the business changes, the previously generated patterned information will not be affected. The data processing category is determined for the patterned information with added dimensional information in order to map it to a specific business scenario so as to access the existing business processing system (such as an accounting system).

[0282] Furthermore, the processing module 22 is also used to: obtain a data processing model; and use the data processing model to convert the data into first patterned information corresponding to a preset pattern in the data processing model.

[0283] Furthermore, the data processing category is an accounting subject; accordingly, the determination module 24 is also used to: map the accounting subject corresponding to the first schematized information with the dimension information added according to the dimension information. The data processing module may also include: a generation module and a storage module. The generation module is used to generate the accounting voucher corresponding to the accounting subject according to the first schematized information with the dimension information added; the storage module is used to save the record voucher locally; or, the data processing module also includes: a generation module and a sending module, wherein the generation module is used to generate the accounting voucher corresponding to the accounting subject according to the first schematized information with the dimension information added; the sending module is used to send the record voucher to the database for retrieval.

[0284] Furthermore, the dimension information includes at least one dimension item; accordingly, the processing module 22 is further used for:

[0285] Acquire at least one second patterned information added with the same dimension items as the first patterned information;

[0286] The first patterned information and the at least one second patterned information are subjected to an accounting processing operation corresponding to the accounting category to obtain a corresponding accounting report.

[0287] It should be noted here that: the data acquisition device provided in the above embodiment can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be found in the corresponding contents in the above method embodiments, which will not be repeated here.

[0288] Fig.12 FIG. 2 shows a schematic diagram of the structure of a data processing device provided by another embodiment of the present application. Fig.12 As shown, the data processing device includes: a determination module 31, an acquisition module 32 and a generation module 33. The determination module 31 is used to determine the target dimension information specified in the data query event in response to the data query event; the acquisition module 32 is used to acquire at least one patterned information added with the target dimension information; the generation module 33 is used to generate a corresponding data report based on the at least one patterned information.

[0289] Furthermore, the target dimension information includes at least one dimension item; accordingly, the generating module 33 is further used to: perform aggregation processing of at least one dimension item on the at least one patterned information to generate the data table.

[0290] Furthermore, the data processing module also includes:

[0291] The acquisition module 32 is further used to respond to a report format custom event and acquire a custom report format generated in the custom event;

[0292] The saving module is used to save the custom report format.

[0293] Furthermore, the generating module 33 is also used for:

[0294] In response to a report format selection event, obtaining a target report format specified by the report format selection event;

[0295] Based on the at least one patterned information, a data report corresponding to the target report format is generated.

[0296] It should be noted here that: the data acquisition device provided in the above embodiment can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be found in the corresponding contents in the above method embodiments, which will not be repeated here.

[0297] Fig.13 FIG. 2 shows a schematic diagram of the structure of a data processing device provided by another embodiment of the present application. Fig.13 As shown, the data processing device includes: an acquisition module 41 and a processing module 42. Among them,

[0298] The acquisition module 41 is used to acquire the data processing category specified by a data processing task in response to an execution instruction of the data processing task; and is also used to acquire at least one patterned information having a mapping relationship with the data processing category;

[0299] The processing module 42 is used to perform a processing operation corresponding to the data processing category on the at least one patterned information to generate a corresponding data report.

[0300] Furthermore, the acquisition module 41 is also used to: acquire dimension information that has a mapping relationship with the data processing category; and acquire at least one of the patterned information added with the dimension information.

[0301] It should be noted here that: the data acquisition device provided in the above embodiment can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be found in the corresponding contents in the above method embodiments, which will not be repeated here.

[0302] Fig.14 FIG. 2 shows a schematic diagram of the structure of a data processing device provided by another embodiment of the present application. Fig.14 As shown, the data processing device includes: an acquisition module 51 and an audit module 52; wherein,

[0303] The acquisition module 51 is used to respond to an execution instruction of a data audit task, acquire two target preset modes that are in a related relationship and specified by the audit task; and is also used to respectively acquire the pattern information corresponding to each of the two target preset modes;

[0304] The audit module 52 is used to perform data audit processing on all acquired modeled information to obtain processing results.

[0305] Among them, the patterned information is obtained by processing data using a data processing model-a preset pattern; the data processing model includes at least one model domain; the model domain contains at least one preset pattern; and an association relationship is configured between two preset patterns belonging to different model domains.

[0306] Fig.15 FIG. 1 shows a schematic diagram of the structure of a computing device provided by an embodiment of the present application. Fig.15 As shown, the computing device includes: a memory 61 and a processor 62, wherein:

[0307] The memory 61 is used to store programs;

[0308] The processor 62 is coupled to the memory 61 and is configured to execute the program stored in the memory 61 to:

[0309] Get the data generated in the data processing event;

[0310] Converting the data into patterned information corresponding to a preset pattern in a preset data processing model;

[0311] Supplementing dimension information for the patterned information according to the event record of the data processing event;

[0312] The dimension information is the basis for determining whether the patterned information belongs to the processing object of an accounting processing task.

[0313] The memory 61 can be configured to store various other data to support operations on the computing device. Examples of such data include instructions for any application or method operating on the computing device. The memory 61 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.

[0314] When executing the program in the memory 61 , the processor 62 may realize other functions in addition to the above functions, and the details may refer to the description of the above embodiments.

[0315] Further, if Fig.15 As shown, the computing device also includes: a communication component 63, a display 64, a power component 65, an audio component 66 and other components. Fig.15 Only some components are shown schematically, and it does not mean that the computing device only includes Fig.15 Components shown.

[0316] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a computer, the steps or functions of the data processing method provided in the above embodiments can be implemented.

[0317] Another embodiment of the present application provides a computing device. The structure of the computing device is similar to that of the above computing device embodiment, which can be seen in the above Fig.15 The computing device includes a memory and a processor, wherein:

[0318] The memory is used to store programs;

[0319] The processor is coupled to the memory and is configured to execute the program stored in the memory to:

[0320] acquiring data from at least one data processing system;

[0321] Performing pattern processing on the data to obtain first pattern information;

[0322] Adding dimension information to the first patterned information based on association information related to the data;

[0323] Determine a corresponding data processing category for adding the first schematized information of the dimension information;

[0324] Perform a processing operation corresponding to the data processing category on the first patterned information.

[0325] In particular, when the processor executes the program in the memory, in addition to the above functions, other functions may also be implemented, for details, please refer to the description of the previous embodiments.

[0326] Another embodiment of the present application provides a computing device. The structure of the computing device is similar to the above computing device embodiment, which can be seen in the above Fig.15 The computing device includes a memory and a processor, wherein:

[0327] The memory is used to store programs;

[0328] The processor is coupled to the memory and is configured to execute the program stored in the memory to:

[0329] In response to a data query event, determining target dimension information specified in the data query event;

[0330] Acquire at least one patterned information added with the target dimension information;

[0331] Based on the at least one patterned information, a corresponding data report is generated.

[0332] In particular, when the processor executes the program in the memory, in addition to the above functions, other functions may also be implemented, for details, please refer to the description of the previous embodiments.

[0333] Another embodiment of the present application provides a computing device. The structure of the computing device is similar to the above computing device embodiment, which can be seen in the above Fig.15 The computing device includes a memory and a processor, wherein:

[0334] The memory is used to store programs;

[0335] The processor is coupled to the memory and is configured to execute the program stored in the memory to:

[0336] In response to an execution instruction of a data processing task, obtaining a data processing category specified by the data processing task;

[0337] Acquire at least one schematized information that has a mapping relationship with the data processing category;

[0338] A processing operation corresponding to the data processing category is performed on the at least one patterned information to generate a corresponding data report.

[0339] In particular, when the processor executes the program in the memory, in addition to the above functions, other functions may also be implemented, for details, please refer to the description of the previous embodiments.

[0340] Another embodiment of the present application provides a computing device. The structure of the computing device is similar to the above computing device embodiment, which can be seen in the above Fig.15 The computing device includes a memory and a processor, wherein:

[0341] The memory is used to store programs;

[0342] The processor is coupled to the memory and is configured to execute the program stored in the memory to:

[0343] In response to an execution instruction of a data audit task, obtaining two target preset modes having an associated relationship specified by the audit task;

[0344] Respectively obtaining pattern information corresponding to the two target preset modes;

[0345] Perform data audit on all acquired patterned information to obtain processing results.

[0346] In particular, when the processor executes the program in the memory, in addition to the above functions, other functions may also be implemented, for details, please refer to the description of the previous embodiments.

[0347] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0348] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0349] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A data processing method, characterized in that: include: Get the data generated in the data processing event; Convert the data into patterned information corresponding to a preset mode in a preset data processing model, wherein the data processing model is independent of the business, the data processing model includes at least one model domain corresponding to a domain category, the model domain contains at least one preset mode corresponding to an item category, and an association relationship is configured between two preset modes belonging to different model domains, so as to perform a data audit task between the two different model domains by using the association relationship; Supplementing dimension information for the patterned information according to the event record of the data processing event; The dimension information is a basis for determining whether the patterned information belongs to a processing object of a processing task; The method of converting the data into patterned information corresponding to a preset mode in a preset data processing model includes: identifying the domain category to which the data belongs; using the model domain corresponding to the domain category to which the data belongs in the at least one model domain as the target model domain; identifying the item category to which the data belongs; using the preset mode corresponding to the item category to which the data belongs in the at least one preset mode contained in the target model domain as the target preset mode; and converting the data into patterned information corresponding to the target preset mode; Among them, the data processing model includes at least one model domain among the following: income domain, prepayment domain; the income domain contains at least one preset mode among the following: accounts receivable mode, collection form mode, accounts receivable distribution mode; the prepayment domain contains at least one preset mode among the following: income transfer mode, prepayment accounts receivable mode, prepayment usage record mode, prepayment collection form mode.

2. The method according to claim 1, characterized in that The data processing model further includes at least one model domain among the following: a fee domain, an institution domain, a settlement domain, and a prepayment domain; The expense domain includes at least one of the following preset modes: expense order mode, payable order mode; The settlement domain includes at least one of the following preset modes: a payment order mode and a payable order mode; The prepaid domain includes at least one of the following preset modes: a prepaid bill mode and a prepaid usage record mode; The organization domain includes: a flow sheet mode of at least one third-party service provider.

3. The method according to claim 2, characterized in that The data processing model contains at least one of the following relationships: There is a transfer relationship between the expense order model and the receivable allocation model; There is a reduction relationship between the collection order mode and the payment order mode; The payment receipt mode and the pre-collection usage record mode have a pre-collection relationship; The collection order model and the third-party service provider's transaction order model have an institutional collection relationship; The receipt mode and the prepaid usage record mode have a prepaid relationship; The payment order mode has an institutional payment relationship with the prepaid usage record mode; There is an institutional payment relationship between the payment order model and the third-party service provider's transaction order model; There is an institutional collection relationship between the prepayment receipt and the third-party service provider's transaction slip model.

4. The method according to claim 3, characterized in that In response to an execution instruction of a data audit task, obtaining two target preset modes having an associated relationship specified by the audit task; Respectively obtaining pattern information corresponding to the two target preset modes; Perform data audit on all acquired patterned information to obtain processing results.

5. The method according to claim 1, characterized in that In response to an execution instruction of a calculation task, obtaining target dimension information specified by the calculation task; Acquire all schematized information having the target dimension information; All the obtained patterned information is aggregated and processed to generate accounting reports.

6. The method according to claim 1, characterized in that According to the event record of the data processing event, the patterned information is supplemented with dimension information, including: Extracting information about parties involved in the event from the event record of the data processing event; The event-related party information is used as dimension information to supplement the patterned information.

7. The method according to claim 1, characterized in that Also includes: Based on the dimension information, determine the accounting subject; Based on the schematized information and the dimension information, an accounting voucher corresponding to the accounting subject is generated.

8. A data processing model, characterized in that: Used to convert input data into patterned information corresponding to a preset pattern; the data processing model includes a conversion unit; The conversion unit includes at least one model domain, and the model domain includes at least one preset mode; Among them, each model domain in the at least one model domain corresponds to a domain category; each preset mode in the at least one preset mode corresponds to a category, and provides corresponding data conversion rules for the input data respectively, the data processing model is independent of the business, and an association relationship is configured between two preset modes belonging to different model domains, so as to perform data audit tasks between two different model domains by using the association relationship; The step of converting the input data into patterned information corresponding to a preset mode includes: identifying the domain category to which the data belongs; using the model domain corresponding to the domain category to which the data belongs in the at least one model domain as the target model domain; identifying the item category to which the data belongs; using the preset mode corresponding to the item category to which the data belongs in the at least one preset mode contained in the target model domain as the target preset mode; and converting the data into patterned information corresponding to the target preset mode; Among them, the data processing model includes at least one model domain among the following: income domain, prepayment domain; the income domain contains at least one preset mode among the following: accounts receivable mode, collection form mode, accounts receivable distribution mode; the prepayment domain contains at least one preset mode among the following: income transfer mode, prepayment accounts receivable mode, prepayment usage record mode, prepayment collection form mode.

9. The data processing model according to claim 8, characterized in that: The data processing model further includes at least one model domain among the following: a fee domain, an institution domain, a settlement domain, and a prepayment domain; The expense domain includes at least one of the following preset modes: expense order mode, payable order mode; The settlement domain includes at least one of the following preset modes: a payment order mode and a payable order mode; The prepaid domain includes at least one of the following preset modes: a prepaid bill mode and a prepaid usage record mode; The organization domain includes: a flow sheet mode of at least one third-party service provider.

10. The data processing model according to claim 9, characterized in that: The data processing model contains at least one of the following relationships: There is a transfer relationship between the expense order model and the receivable allocation model; There is a reduction relationship between the collection order mode and the payment order mode; The payment receipt mode and the pre-collection usage record mode have a pre-collection relationship; The collection order model and the third-party service provider's transaction order model have an institutional collection relationship; The receipt mode and the prepaid usage record mode have a prepaid relationship; The payment order mode has an institutional payment relationship with the prepaid usage record mode; There is an institutional payment relationship between the payment order model and the third-party service provider's transaction order model; There is an institutional collection relationship between the prepayment receipt and the third-party service provider's transaction slip model.

11. The data processing model according to claim 8 or 9, characterized in that: Also includes: A supplementing unit, configured to supplement dimension information for the patterned information output by the conversion unit according to an event record of the data processing event; The dimension information is the basis for determining whether the patterned information belongs to the processing object of a processing task; and the data converted into the patterned information is generated in the data processing event.

12. The data processing model according to claim 8 or 9, characterized in that: Also includes: The accounting unit is used to respond to an execution instruction of an accounting task, obtain the target dimension information specified by the accounting task; obtain all the patterned information having the target dimension information; aggregate all the obtained patterned information to generate an accounting report; and / or The audit unit is used to respond to an execution instruction of a data audit task, obtain two target preset modes with a correlation relationship specified by the audit task; respectively obtain the patterned information corresponding to each of the two target preset modes; perform data audit processing on all the acquired patterned information to obtain a processing result.

13. A data processing system, characterized in that: include: The server is used to provide various types of services and record the data processing events corresponding to each service; A first processing device, connected to the server, for generating corresponding accounting vouchers for data processing events; A second processing device, arranged between the server and the first processing device, for converting data generated in a data processing event into patterned information corresponding to a preset pattern in a preset data processing model; After supplementing the dimension information for the schematized information according to the event record of the data processing event, the schematized information is sent to the first processing device so that the first processing device generates a corresponding accounting voucher based on the schematized information; The dimension information is a basis for determining whether the patterned information belongs to a processing object of a processing task; the data processing model is independent of the business, the data processing model includes at least one model domain corresponding to a domain category, the model domain contains at least one preset mode corresponding to an item category, and an association relationship is configured between two preset modes belonging to different model domains, so as to perform a data audit task between two different model domains by using the association relationship; The method of converting the data generated in the data processing event into patterned information corresponding to a preset mode in the preset data processing model includes: identifying the domain category to which the data belongs; using the model domain corresponding to the domain category to which the data belongs in the at least one model domain as the target model domain; identifying the item category to which the data belongs; using the preset mode corresponding to the item category to which the data belongs in the at least one preset mode contained in the target model domain as the target preset mode; and converting the data into patterned information corresponding to the target preset mode; Among them, the data processing model includes at least one model domain among the following: income domain, prepayment domain; the income domain contains at least one preset mode among the following: accounts receivable mode, collection form mode, accounts receivable distribution mode; the prepayment domain contains at least one preset mode among the following: income transfer mode, prepayment accounts receivable mode, prepayment usage record mode, prepayment collection form mode.

14. A data processing method, characterized in that: include: acquiring data from at least one data processing system; Acquire a data processing model, and use the data processing model to convert the data into first patterned information corresponding to a preset pattern in the data processing model, wherein the data processing model is independent of the business, the data processing model includes at least one model domain corresponding to a domain category, the model domain contains at least one preset pattern corresponding to an item category, and an association relationship is configured between two preset patterns belonging to different model domains, so as to perform a data audit task between the two different model domains by using the association relationship; Performing pattern processing on the data to obtain first pattern information; Adding dimension information to the first patterned information based on association information related to the data; Determine a corresponding data processing category for adding the first schematized information of the dimension information; Performing a processing operation corresponding to the data processing category on the first patterned information; The step of converting the data into first patterned information corresponding to a preset mode in the data processing model includes: identifying the domain category to which the data belongs; using the model domain corresponding to the domain category to which the data belongs in the at least one model domain as the target model domain; identifying the item category to which the data belongs; using the preset mode corresponding to the item category to which the data belongs in the at least one preset mode contained in the target model domain as the target preset mode; and converting the data into patterned information corresponding to the target preset mode; Among them, the data processing model includes at least one model domain among the following: income domain, prepayment domain; the income domain contains at least one preset mode among the following: accounts receivable mode, collection form mode, accounts receivable distribution mode; the prepayment domain contains at least one preset mode among the following: income transfer mode, prepayment accounts receivable mode, prepayment usage record mode, prepayment collection form mode.

15. The method according to claim 14, characterized in that The data processing category is accounting subjects; as well as Determining a corresponding data processing category for adding the first schematized information of the dimension information includes: According to the dimension information, mapping out the accounting subject corresponding to the first patterned information to which the dimension information is added; The method further comprises: Generate a bookkeeping voucher corresponding to the accounting subject according to the first schematized information with the dimension information added thereto; The accounting voucher is saved locally or sent to a database for retrieval.

16. The method according to claim 15, characterized in that The dimension information includes at least one dimension item; as well as Performing a processing operation corresponding to the data processing category on the patterned information includes: Acquire at least one second patterned information added with the same dimension items as the first patterned information; The first patterned information and the at least one second patterned information are subjected to account processing operations corresponding to the accounting subjects to obtain corresponding account statements.

17. A data processing method, characterized in that: include: In response to a data query event, determining target dimension information specified in the data query event; Acquire at least one patterned information added with the target dimension information, wherein the at least one patterned information added with the target dimension information is obtained according to the data processing method of claim 1; Based on the at least one patterned information, a corresponding data report is generated.

18. The method according to claim 17, characterized in that The target dimension information includes at least one dimension item; And, based on the at least one patterned information, generating a corresponding data table, including: Aggregation processing of at least one dimension item is performed on the at least one schematized information to generate the data table.

19. The method according to claim 17, characterized in that Also includes: In response to a report format customization event, obtaining a customized report format generated in the customized event; Save the custom report format.

20. The method according to claim 17, characterized in that Based on the at least one patterned information, a corresponding data table is generated, including: In response to a report format selection event, obtaining a target report format specified by the report format selection event; Based on the at least one patterned information, a data report corresponding to the target report format is generated.

21. A data processing method, characterized in that: include: In response to an execution instruction of a data processing task, obtaining a data processing category specified by the data processing task; Acquire dimension information that is mapped to the data processing category, and acquire at least one of the schematized information added with the dimension information; wherein the at least one of the schematized information added with the dimension information is obtained according to the data processing method of claim 1; A processing operation corresponding to the data processing category is performed on the at least one patterned information to generate a corresponding data report.

22. A data processing method, characterized in that: include: In response to an execution instruction of a data audit task, obtaining two target preset modes having an associated relationship specified by the audit task; Respectively obtaining pattern information corresponding to the two target preset modes; Perform data audit on all acquired modeled information to obtain processing results; Wherein, the patterned information is obtained by processing the data using a data processing model-a preset mode; The data processing model includes at least one model domain corresponding to a domain category; the model domain contains at least one preset mode corresponding to an item category; an association relationship is configured between two preset modes belonging to different model domains, so as to perform a data audit task between the two different model domains by using the association relationship; The data processing model identifies the domain category to which the data belongs; uses the model domain corresponding to the domain category to which the data belongs in the at least one model domain as the target model domain; identifies the item category to which the data belongs; uses the preset mode corresponding to the item category to which the data belongs in the at least one preset mode contained in the target model domain as the target preset mode; and converts the data into patterned information corresponding to the target preset mode; Among them, the data processing model includes at least one model domain among the following: income domain, prepayment domain; the income domain contains at least one preset mode among the following: accounts receivable mode, collection form mode, accounts receivable distribution mode; the prepayment domain contains at least one preset mode among the following: income transfer mode, prepayment accounts receivable mode, prepayment usage record mode, prepayment collection form mode.

23. A computing device, characterized in that comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is configured to execute the program stored in the memory to: Get the data generated in the data processing event; Converting the data into patterned information corresponding to a preset pattern in a preset data processing model; Supplementing dimension information for the patterned information according to the event record of the data processing event; The dimension information is the basis for determining whether the patterned information belongs to the processing object of a processing task; the data processing model is independent of the business, the data processing model includes at least one model domain corresponding to the domain category, the model domain contains at least one preset mode corresponding to the item category, and an association relationship is configured between two preset modes belonging to different model domains, so as to perform the data audit task between the two different model domains by using the association relationship; The step of converting the data into patterned information corresponding to a preset mode in the preset data processing model includes: identifying the domain category to which the data belongs; using the model domain corresponding to the domain category to which the data belongs in the at least one model domain as the target model domain; identifying the item category to which the data belongs; using the preset mode corresponding to the item category to which the data belongs in the at least one preset mode contained in the target model domain as the target preset mode; and converting the data into patterned information corresponding to the target preset mode; Among them, the data processing model includes at least one model domain among the following: income domain, prepayment domain; the income domain contains at least one preset mode among the following: accounts receivable mode, collection form mode, accounts receivable distribution mode; the prepayment domain contains at least one preset mode among the following: income transfer mode, prepayment accounts receivable mode, prepayment usage record mode, prepayment collection form mode.

24. A computing device, characterized in that comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is configured to execute the program stored in the memory to: acquiring data from at least one data processing system; Acquire a data processing model, and use the data processing model to convert the data into first patterned information corresponding to a preset pattern in the data processing model, wherein the data processing model is independent of the business, the data processing model includes at least one model domain corresponding to a domain category, the model domain contains at least one preset pattern corresponding to an item category, and an association relationship is configured between two preset patterns belonging to different model domains, so as to perform a data audit task between the two different model domains by using the association relationship; add dimension information to the first patterned information based on the association information related to the data; Determine a corresponding data processing category for adding the first schematized information of the dimension information; Performing a processing operation corresponding to the data processing category on the first patterned information; Wherein, using the data processing model, converting the data into first patterned information corresponding to a preset mode in the data processing model includes: identifying the domain category to which the data belongs; using the model domain corresponding to the domain category to which the data belongs in the at least one model domain as the target model domain; identifying the item category to which the data belongs; using the preset mode corresponding to the item category to which the data belongs in at least one preset mode contained in the target model domain as the target preset mode; converting the data into patterned information corresponding to the target preset mode; Among them, the data processing model includes at least one model domain among the following: income domain, prepayment domain; the income domain contains at least one preset mode among the following: accounts receivable mode, collection form mode, accounts receivable distribution mode; the prepayment domain contains at least one preset mode among the following: income transfer mode, prepayment accounts receivable mode, prepayment usage record mode, prepayment collection form mode.

25. A computing device, characterized in that comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is configured to execute the program stored in the memory to: In response to a data query event, determining target dimension information specified in the data query event; Acquire at least one patterned information added with the target dimension information, wherein the at least one patterned information added with the target dimension information is obtained according to the data processing method of claim 1; Based on the at least one patterned information, a corresponding data report is generated.

26. A computing device, characterized in that comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is configured to execute the program stored in the memory to: In response to an execution instruction of a data processing task, obtaining a data processing category specified by the data processing task; Acquire dimension information that is mapped to the data processing category, and acquire at least one of the schematized information added with the dimension information; wherein the at least one of the schematized information added with the dimension information is obtained according to the data processing method of claim 1; A processing operation corresponding to the data processing category is performed on the at least one patterned information to generate a corresponding data report.

27. A computing device, characterized in that comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is configured to execute the program stored in the memory to: In response to an execution instruction of a data audit task, obtaining two target preset modes having an associated relationship specified by the audit task; Respectively obtaining pattern information corresponding to the two target preset modes; Performing data audit processing on all acquired patterned information to obtain processing results, wherein the patterned information is obtained by processing data using a preset pattern of a data processing model; the data processing model includes at least one model domain corresponding to a domain category; the model domain contains at least one preset pattern corresponding to an item category; an association relationship is configured between two preset patterns belonging to different model domains, so as to perform a data audit task between the two different model domains using the association relationship; The data processing model identifies the domain category to which the data belongs; uses the model domain corresponding to the domain category to which the data belongs in the at least one model domain as the target model domain; identifies the item category to which the data belongs; uses the preset mode corresponding to the item category to which the data belongs in the at least one preset mode contained in the target model domain as the target preset mode; and converts the data into patterned information corresponding to the target preset mode; Among them, the data processing model includes at least one model domain among the following: income domain, prepayment domain; the income domain contains at least one preset mode among the following: accounts receivable mode, collection form mode, accounts receivable distribution mode; the prepayment domain contains at least one preset mode among the following: income transfer mode, prepayment accounts receivable mode, prepayment usage record mode, prepayment collection form mode.

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