Data processing method and device based on computing platform and electronic equipment

Abstract

The invention provides a data processing method and device based on a computing platform, equipment and a storage medium, which can be applied to the technical fields of big data technology and financial science and technology. The data processing method based on the computing platform comprises the following steps: sending a data acquisition request to a target data source, wherein the data acquisition request is used for requesting to acquire target data associated with a target object; receiving target data associated with the target object from a target data source; processing the target data to generate a standard data table corresponding to the target object; a target template matched with the standard data table is determined from a plurality of processing templates stored in the computing platform, and the processing templates are used for processing the standard data table according to preset service logic; processing the standard data table by using the target template to obtain processed resource data; and calling an output interface to output the processed resource data in a target form.

Description

Technical Field

[0001] The present disclosure relates to the financial field and the technical field of big data processing, and in particular to a data processing method, device, electronic device and storage medium based on a computing platform. Background Art

[0002] With the development of computer technology, more and more computer technologies are being applied in the financial field. In related technologies, the storage and calculation of financial data in financial institutions rely on third-party systems. Since third-party systems have the risk of data leakage, and financial institutions can only obtain financial data and calculated financial resources from third-party systems, the security of the obtained financial data cannot be ensured.

[0003] In addition, due to the opaque calculation methods of financial data by third-party systems, financial institutions are unable to flexibly adjust the financial data calculated by third-party institutions, resulting in complex financial data adjustment operations and low adjustment efficiency. Summary of the invention

[0004] In view of the above problems, the present disclosure provides a data processing method, device, electronic device and storage medium based on a computing platform.

[0005] According to a first aspect of the present disclosure, a data processing method based on a computing platform is provided, comprising:

[0006] Sending a data acquisition request to a target data source, wherein the data acquisition request is used to request acquisition of target data associated with a target object;

[0007] Receiving the target data associated with the target object from the target data source;

[0008] Processing the target data to generate a standard data table corresponding to the target object;

[0009] Determining a target template that matches the standard data table from a plurality of processing templates stored in the computing platform, wherein the processing template is used to process the standard data table according to a preset business logic;

[0010] Processing the standard data table using the target template to obtain processed resource data;

[0011] The output interface is called to output the above processed resource data in target form.

[0012] According to an embodiment of the present disclosure, after receiving the target data associated with the target object from the target data source, the method further includes:

[0013] Displaying the target data in a first interactive interface, wherein the first interactive interface further includes a field to be input corresponding to the target data;

[0014] In response to the user's input operation, obtaining the field value of the field to be input;

[0015] The above-mentioned processing of the above-mentioned target data to generate a standard data table corresponding to the above-mentioned target object also includes:

[0016] The target data and the field values ​​of the fields to be input are processed to generate a standard data table corresponding to the target object.

[0017] According to an embodiment of the present disclosure, the method further includes:

[0018] In response to unsuccessful reception of the target data associated with the target object from the target data source, displaying abnormal reception information on the second interactive interface; and

[0019] In response to the user's import operation on the second interactive interface, the import file is acquired and parsed to obtain the target data.

[0020] According to an embodiment of the present disclosure, the step of determining a target template matching the standard data table from a plurality of processing templates stored in the computing platform includes:

[0021] Determine a target processing model according to the first standard data in the standard data table, wherein the first standard data is used to characterize the attributes of the target data;

[0022] determining a plurality of process templates associated with the target process model; and

[0023] The target template is determined from the plurality of processing templates according to the second standard data in the standard data table, wherein the second standard data is used to characterize the information of the entity that publishes the target object.

[0024] According to an embodiment of the present disclosure, the method further includes:

[0025] Periodically sending a data verification request to the above target data source;

[0026] Receiving verification data returned by the target data source;

[0027] Comparing the verification data with the target data to obtain a first verification result; and

[0028] In response to the first verification result indicating an abnormality, the first verification result is pushed to the user through a preset channel.

[0029] According to an embodiment of the present disclosure, the method further includes:

[0030] When the first verification result indicates that the M first fields are abnormal, the M first fields are displayed through a third interactive interface, where M≥2;

[0031] In response to a selection operation of the user on the third interactive interface, determining N second fields from the M first fields, M≥N≥1;

[0032] The N second fields are added to the whitelist of the computing platform so that the N second fields are not verified during the next data verification process.

[0033] According to an embodiment of the present disclosure, after the first verification result is pushed to the user through the preset channel, the following steps are included:

[0034] In response to receiving an operation request for processing the first verification result, determining a request type and a user sending the operation request;

[0035] When it is determined that the request type is a query type and the user is the first user or the second user, the query result is displayed on the fourth interactive interface, wherein the first user only has the authority to view the first verification result, and the second user has the authority to view and process the first verification result;

[0036] When it is determined that the request type is an exception handling type and the user is a second user, an operation box is displayed on the fifth interactive interface so that the user can input an exception handling strategy through the operation box.

[0037] According to an embodiment of the present disclosure, the method further includes:

[0038] Batch obtain P processing models and / or processing templates stored in the computing platform at a preset time, where P≥2;

[0039] Based on the model mapping relationship or the template mapping relationship stored in the computing platform, verify the P processing models and / or the processing templates to obtain a second verification result;

[0040] In response to the second verification result indicating that the verification result is normal, obtaining verification resource information at the current moment from the target data source; and

[0041] The verification resource information is compared with the resource data obtained by using the P processing models and / or the processing templates to obtain a third verification result.

[0042] A second aspect of the present disclosure provides a financial data processing device based on a computing platform, comprising:

[0043] A sending module, used to send a data acquisition request to a target data source, wherein the data acquisition request is used to request to acquire target data associated with a target object;

[0044] A receiving module, used for receiving the target data associated with the target object from the target data source;

[0045] A generating module, used for processing the target data to generate a standard data table corresponding to the target object;

[0046] A matching module, used to determine a target template that matches the standard data table from a plurality of processing templates stored in the computing platform, wherein the processing template is used to process the standard data table according to a preset business logic;

[0047] A processing module, used for processing the standard data table using the target template to obtain processed resource data;

[0048] The output module is used to call the output interface to output the processed resource data in the target form.

[0049] The third aspect of the present disclosure provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the data processing method based on the computing platform.

[0050] The fourth aspect of the present disclosure further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to execute the above-mentioned data processing method based on the computing platform.

[0051] The fifth aspect of the present disclosure also provides a computer program product, including a computer program, which implements the above-mentioned data processing method based on the computing platform when executed by a processor.

[0052] The embodiment of the present disclosure obtains target data associated with a target object from a target data source, processes the target data, and generates a standard data table corresponding to the target object; determines a target template that matches the standard data table from a plurality of processing templates stored in a computing platform, processes the standard data table using the target template, obtains processed resource data, and finally exports the resource data in a target form. Since the embodiment of the present disclosure introduces a computing platform, the processing template stored in the computing platform is used to match and calculate the standard data table to obtain the required resource data, so that the purpose of flexibly calculating and adjusting the target data can be achieved by only obtaining the original target data from the data source, thereby improving the security of the resource data. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The above contents and other purposes, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0054] Figure 1 The application scenario of the data processing method based on the computing platform according to the embodiment of the present disclosure is schematically shown;

[0055] Figure 2 A flowchart of a data processing method based on a computing platform according to an embodiment of the present disclosure is schematically shown;

[0056] Figure 3 A flowchart of a method for acquiring target data according to an embodiment of the present disclosure is schematically shown;

[0057] Figure 4 A flowchart of a method for determining a target template according to an embodiment of the present disclosure is schematically shown;

[0058] Figure 5 A flowchart of a method for obtaining a first verification result according to an embodiment of the present disclosure is schematically shown;

[0059] Figure 6 A flowchart of a method for determining a second field according to an embodiment of the present disclosure is schematically shown;

[0060] Figure 7 A flowchart of a method for obtaining a third verification result according to an embodiment of the present disclosure is schematically shown;

[0061] Figure 8 A flowchart of a method for acquiring resource data according to an embodiment of the present disclosure is schematically shown;

[0062] Fig. 9 A flowchart of a first verification result verification method according to an embodiment of the present disclosure is schematically shown;

[0063] Fig.10 A structural block diagram schematically shows a data processing device based on a computing platform according to an embodiment of the present disclosure; and

[0064] Fig.11 A block diagram of an electronic device suitable for a data processing method based on a computing platform according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0065] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0066] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0067] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0068] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0069] In the technical solution of the present disclosure, the user information (including but not limited to user personal information, user image information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0070] With the development of computer technology, more and more computer technologies are being applied in the financial field. In related technologies, the storage and calculation of financial data in financial institutions rely on third-party systems. Since third-party systems have the risk of data leakage, and financial institutions can only obtain financial data and calculated financial resources from third-party systems, the security of the obtained financial data cannot be ensured.

[0071] In addition, due to the opaque calculation methods of financial data by third-party systems, financial institutions are unable to flexibly adjust the financial data calculated by third-party institutions, resulting in complex financial data adjustment operations and low adjustment efficiency.

[0072] An embodiment of the present disclosure provides a data processing method based on a computing platform, including: sending a data acquisition request to a target data source, the data acquisition request is used to request to acquire target data associated with a target object; receiving target data associated with a target object from the target data source; processing the target data to generate a standard data table corresponding to the target object; determining a target template that matches the standard data table from a plurality of processing templates stored in the computing platform, wherein the processing template is used to process the standard data table according to a preset business logic; processing the standard data table using the target template to obtain processed resource data; and calling an output interface to output the processed resource data in a target form.

[0073] Figure 1 The application scenario of the data processing method based on the computing platform according to the embodiment of the present disclosure is schematically illustrated.

[0074] like Figure 1 As shown, the application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, and a server 105. The network 104 is used to provide a medium for a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0075] The user may use at least one of the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications may be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0076] The first terminal device 101, the second terminal device 102, and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0077] The server 105 may be a server that provides various services, such as a background management server (only as an example) that provides support for websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0078] It should be noted that the data processing method based on the computing platform provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the data processing device based on the computing platform provided in the embodiment of the present disclosure can generally be set in the server 105. The data processing method based on the computing platform provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the data processing device based on the computing platform provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105.

[0079] For example, the terminal device sends a data acquisition request to the server, and the server can receive target data associated with the target object from the first terminal device 101, the second terminal device 102, and the third terminal device 103. After receiving the target data associated with the target object, the server 105 processes the target data, generates a standard data table corresponding to the target object, and determines a target template matching the standard data table from multiple processing templates stored in the server 105, processes the standard data table using the target template, obtains processed resource data, and the server 105 calls the output interface to output the processed resource data in the form of a target.

[0080] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0081] The following will be based on Figure 1 The scene described by Figure 2 to Figure 9 The data processing method based on the computing platform of the disclosed embodiment is described in detail.

[0082] Figure 2 The flowchart of the data processing method based on the computing platform according to the embodiment of the present disclosure is schematically shown.

[0083] like Figure 2As shown, the method 200 includes operations S210 to S260.

[0084] In operation S210 , a data acquisition request is sent to a target data source, where the data acquisition request is used to request acquisition of target data associated with a target object.

[0085] According to an embodiment of the present disclosure, the target data source is a third-party system for providing the required data resources, which may be a database. The third-party system may be a paid database that has a subscription relationship with the computing platform, or an open source database.

[0086] According to an embodiment of the present disclosure, the target object may be a financial object issued by a bank or other enterprise in the financial field, for example, a bond or the like.

[0087] According to an embodiment of the present disclosure, the target data is used to characterize basic information related to the target object. For example, if a bond in financial data is used as the target object, the target data may be data characterizing basic information of the target object, such as the issuance time, maturity time, issuing entity, and other information of the target object.

[0088] In operation S220 , target data associated with a target object is received from a target data source.

[0089] According to an embodiment of the present disclosure, after sending a request to obtain target data, the client receives basic information data related to the target object retrieved from the database for subsequent processing.

[0090] In the embodiment of the present disclosure, the third-party system as the target data source is only used to store data related to multiple objects. The computing platform sends a request to the target data source, and the data acquisition request may include identification information of the target object to be acquired, so that the target data source determines the target data associated with the target object according to the identification information of the target object, and returns the target data to the computing platform.

[0091] According to an embodiment of the present disclosure, the computing platform can obtain target data associated with the target data from the target data source through a data acquisition request. Since the target data returned by the target data source only includes the basic financial data of the target object, the processing operation for the target object is implemented by the computing platform. Therefore, the computing platform can decouple data storage and data computing, at least partially solving the data leakage problem caused by the storage of processed financial data by a third-party system.

[0092] In operation S230, the target data is processed to generate a standard data table corresponding to the target object.

[0093] According to an embodiment of the present disclosure, the standard data table includes target data acquired from a target data source. By displaying the standard data table, basic information associated with the target object can be displayed.

[0094] According to an embodiment of the present disclosure, the standard data table may also include other data required by the computing platform in addition to the target data, such as a data processing number.

[0095] According to an embodiment of the present disclosure, processing the target data includes: determining multiple field names to be extracted based on the data processing rules of the computing platform; obtaining field values ​​corresponding to the multiple field names from the target data; and generating a standard data table based on the multiple field names and the field values ​​corresponding to the multiple field names.

[0096] According to an embodiment of the present disclosure, when the target data does not include a field value corresponding to a field name, the field value corresponding to the field name is set to 0. Alternatively, when the target data does not include a field value corresponding to a field name, the information input by the user is used as the field value corresponding to the field name.

[0097] In operation S240, a target template matching the standard data table is determined from a plurality of processing templates stored in the computing platform, wherein the processing template is used to process the standard data table according to a preset business logic.

[0098] According to an embodiment of the present disclosure, the computing platform can also be used to match complex computing methods with stored processing templates, and has functions such as resource information management, resource information verification, and resource information display.

[0099] According to an embodiment of the present disclosure, a processing template is used to process a standard data table according to a preset business logic. The preset business logic may be a business processing logic related to financial data, such as preprocessing, financial resource calculation, business process processing, etc., which is not specifically limited here.

[0100] For example, the processing template can match the field information in the template with the field data in the standard data table according to the pre-set reasoning rules. There are many different types of processing templates stored in the computing platform. Different target data can be matched through different processing templates to improve the accuracy of processing target data.

[0101] In operation S250, the standard data table is processed using the target template to obtain processed resource data.

[0102] According to the embodiments of the present disclosure, after matching the data information in the standard data table with the data information in the processing template, the processed resource data can be obtained by performing mathematical operations, logical reasoning and the like on the matched target data.

[0103] According to an embodiment of the present disclosure, the above-mentioned resource data may be financial data after processing the target data. For example, if bonds are used as the target data, the resource data may be financial data such as predicted bond yields, market prices, and durations.

[0104] In operation S260, an output interface is called to output the processed resource data in an object form.

[0105] According to an embodiment of the present disclosure, after the computing platform identifies the processed resource data, it can directly output the resource data in text form by calling the output interface; it can also call the output interface to process the resource data into image form and export it.

[0106] The embodiment of the present disclosure obtains target data associated with a target object from a target data source, processes the target data, and generates a standard data table corresponding to the target object; determines a target template that matches the standard data table from a plurality of processing templates stored in a computing platform, processes the standard data table using the target template, obtains processed resource data, and finally exports the resource data in a target form. Since the embodiment of the present disclosure introduces a computing platform, the processing template stored in the computing platform is used to match and calculate the standard data table to obtain the required resource data, so that the purpose of flexibly calculating and adjusting the target data can be achieved by only obtaining the original target data from the data source, thereby improving the security of the resource data.

[0107] According to an embodiment of the present disclosure, after receiving target data associated with a target object from a target data source, it also includes: displaying the target data in a first interactive interface, wherein the first interactive interface also includes a field to be input corresponding to the target data; and obtaining a field value of the field to be input in response to an input operation of a user.

[0108] According to an embodiment of the present disclosure, an interactive interface is used to implement an interactive process between a user and a computer. The user can input instructions to the computer through the interactive interface to perform operations, and the computer can also display information to the user through the interactive interface.

[0109] According to an embodiment of the present disclosure, the first interactive interface is used to display target data associated with the target object obtained from the data source, and can provide viewing and operation options to the user. Wherein, on the first interactive interface, the target data can be displayed to the user in the form of a table, a histogram, etc.

[0110] According to an embodiment of the present disclosure, the first interactive interface also includes fields to be input and data source import fields corresponding to the target data, wherein the fields to be input are mandatory when obtaining bond information, and the fields to be input can be entered through interactive operations with the user. Except for the fields to be input, the remaining fields are non-mandatory and can be directly obtained from the target data source, i.e., the database.

[0111] According to an embodiment of the present disclosure, after the user performs a manual input operation on a field to be input on the first interactive interface, the field value corresponding to the field can be obtained.

[0112] According to an embodiment of the present disclosure, processing the target data to generate a standard data table corresponding to the target object also includes: processing the target data and field values ​​of the fields to be input to generate a standard data table corresponding to the target object.

[0113] According to an embodiment of the present disclosure, after obtaining the target data and the field values ​​of the fields to be input, the field values ​​in the target data and the field values ​​of the fields to be input are extracted, and the extracted field values ​​are imported into a table to automatically generate a standard data table corresponding to the target object.

[0114] As a specific embodiment of the present disclosure, a standard data table can be generated directly based on the target data obtained from the target data source; or a standard data table can be generated based on the target data obtained from the target data source and the field values ​​entered by the user on the computing platform.

[0115] For example, in the financial field, taking bond A as the target object, accessing the bond's currency information and issuer information from the Bloomberg database shows that bond A is a foreign currency bond and is issued by financial company B. After obtaining the target data, the bond information manager fills in the bond's issuing country as C on the first interactive interface. Therefore, by extracting the field values ​​of the above data, a standard data table as shown in Table 1 can be generated:

[0116] Currency Issuer Issuing Country Bond A foreign currency Financial Company B C

[0117] Table 1 Standard data table of an embodiment

[0118] The embodiment of the present disclosure displays the target data accessed by the third-party system to the user through the first interactive interface, and sets the fields to be input to provide the user with manual input field information to achieve flexible adjustment operations on resource data, thereby improving the efficiency of resource adjustment.

[0119] According to an embodiment of the present disclosure, the data processing method based on the computing platform also includes:

[0120] In response to unsuccessful reception of target data associated with a target object from a target data source, abnormal reception information is displayed on a second interactive interface; and in response to an import operation by a user on the second interactive interface, an import file is acquired and parsed to obtain the target data.

[0121] According to an embodiment of the present disclosure, the second interactive interface is used to display an abnormal reception information prompt box displayed when the target data is not successfully received. The second interactive interface can also be used to provide users with a file import bar for manually importing files for missing or erroneous abnormal data, so as to correct or supplement the abnormal data.

[0122] According to an embodiment of the present disclosure, the abnormal reception information may be a prompt information generated when the target data returned from the target data source is not successfully received after sending a data acquisition request to the target data source. Among them, abnormal situations such as missing target data or incorrect data will be determined as unsuccessful reception of target data.

[0123] According to an embodiment of the present disclosure, the import file imported by the user may be a data file associated with the target object, including a target data file of the same type and application scenario as the target object, having basic information of the target object, etc., which can complete or accurately supplement the target data.

[0124] According to an embodiment of the present disclosure, when the computing platform fails to successfully receive the target data from the database, abnormal reception information will be automatically displayed on the second interactive interface. The displayed content also includes missing or erroneous abnormal target data. For these abnormal target data, the user can import the import file associated with the abnormal target data through the file import bar on the second interactive interface. The computing platform will parse the import file to correct or supplement the abnormal target data, so as to obtain complete and accurate target data.

[0125] Figure 3 The flowchart of the method for acquiring target data according to an embodiment of the present disclosure is schematically shown.

[0126] like Figure 3 As shown, the method 300 for acquiring target data in this embodiment includes operations S301 to S306.

[0127] In operation S301 , the computing platform receives target data returned by a target data source.

[0128] In operation S302 , it is determined whether the computing platform successfully receives the target data from the target data source.

[0129] In operation S303, the abnormal reception information is displayed on the second interactive interface.

[0130] In operation S304, the import file imported by the user is acquired and parsed.

[0131] In operation S305, target data is determined.

[0132] In operation S306, the process ends in response.

[0133] After sending a data acquisition request to the target data source, the target data source returns the requested target data. In operation S301, the computing platform receives the target data returned by the target data source. Operation S302 determines whether the computing platform has successfully received the target data from the target data source. If so, the end process of S306 is executed. If not, operation S303 is executed to display a prompt box of abnormal reception information on the second interactive interface to remind the user, i.e., the information administrator, that the database information access has failed.

[0134] According to an embodiment of the present disclosure, after receiving the abnormal reception information, the user can import the file required to be associated with the target object into the file import column of the second interactive interface through a manual import operation, and the computing platform will execute operation S304 to obtain the import file imported by the user, and parse and identify the import file, and extract the complete and correct basic information of the target object by executing S305 to determine it as the target data.

[0135] In the event of an abnormality in target data access from a third-party platform, the embodiments of the present disclosure can supplement or correct the abnormal data in a timely manner through the user's manual import of files to support the computing platform to continue resource calculations, thereby achieving flexible adjustment of the target data and improving computing efficiency.

[0136] According to an embodiment of the present disclosure, a target template matching a standard data table is determined from a plurality of processing templates stored in a computing platform, including: determining a target processing model based on first standard data in the standard data table, wherein the first standard data is used to characterize properties of the target data; determining a plurality of processing templates related to the target processing model; and determining a target template from a plurality of processing templates based on second standard data in the standard data table, wherein the second standard data is used to characterize information of an entity that publishes a target object.

[0137] According to an embodiment of the present disclosure, the first standard data is used to characterize basic attribute information of the target data, such as the type of the target object, the data processing type, the deadline time, the target object processing rule, etc.

[0138] According to an embodiment of the present disclosure, the second standard data is used to characterize the entity information of the target object. The entity of the target object can be understood as the subject that publishes the target object, such as a bank, an enterprise, etc. The second standard data can be the operating unit or organization of the target object, the transaction channel, the location of the operating unit, etc.

[0139] According to an embodiment of the present disclosure, a target processing model refers to a computing model that can be used to match target data.

[0140] According to the embodiments of the present disclosure, the spline model is a type of model that uses a spline function to perform piecewise fitting on the discount function. According to the Weierstrass approximation theorem, any continuous function on a closed interval can be approximated by a set of polynomial functions. According to different spline functions, the spline model can generally be divided into a polynomial spline model, an exponential spline model, and a smoothing spline model.

[0141] According to an embodiment of the present disclosure, the polynomial spline model represents the discount function by a piecewise polynomial function. The discount function of the exponential spline model is basically a function that decreases exponentially as the term increases.

[0142] For example, a spline curve model is set, and the model is used to fit the discount function through actual price information, and then the obtained discount function is used to price the bond. The optimal objective function in the fitting process is expressed as:

[0143]

[0144] Among them, pi represents the actual market price of the bond, Represents the model price of the bond.

[0145] According to another embodiment of the present disclosure, in order to ensure the continuity and smoothness of the curve, a third-order exponential spline function is generally used, and its form is as follows:

[0146]

[0147] Among them, u can represent the instantaneous forward interest rate when the value date is infinitely far in the future. In order to satisfy the smoothness of the discount function and the continuity of the derivation, the derivatives of all orders should be equal at the nodes, that is, the following constraints should be satisfied:

[0148]

[0149] According to another embodiment of the present disclosure, for example, a computational model may be constructed using a linear interpolation method or a third-order spline model, wherein the third-order spline model may choose to use a smoothing spline model, which may characterize the balance between the sample points and the processing template in the optimization objective function, and the linear interpolation method refers to a method of using a straight line connecting two known quantities to determine the value of an unknown quantity between the two known quantities.

[0150] For example, in the application scenario of using linear interpolation to calculate yield data in the financial field, two RIC codes with adjacent maturities can be selected. By default, the yields of the non-standard maturities of the two RIC codes are connected into a straight line. The yield corresponding to the required term can be obtained by the following calculation method:

[0151]

[0152] Among them, Y t represents the required term rate of return; t represents the term corresponding to the required rate of return (in years); T i Indicates the upcoming non-standard term of the RIC code that is less than the required term (in years); T i+1 Indicates the non-standard term of the RIC code that is near and greater than the term requested (in years); Y i Indicates the yield of the non-standard term of the RIC code that is less than the required term; Y i+1 Indicates the yield of the nearby RIC code non-standard term that is greater than the requested term.

[0153] According to an embodiment of the present disclosure, after a standard data table is generated using target data, the first standard data in the standard data table, i.e., the type of target object, data processing type, deadline time target object processing rules and other data information fields are used to distinguish and map to corresponding computing models, and the computing model that matches these fields is selected as the target processing model.

[0154] According to an embodiment of the present disclosure, a plurality of processing templates having at least one identical attribute information field with a target processing model are selected from a plurality of processing templates stored in a computing platform.

[0155] According to an embodiment of the present disclosure, after determining multiple processing templates, the second standard data in the standard data table, i.e., the fields of data information such as the target object's business unit or organization, transaction channels, and business unit location are matched with multiple processing templates one-to-one, and the processing template that successfully matches the processing model can be used as the target template.

[0156] According to an embodiment of the present disclosure, there may be multiple target templates, and different target templates may correspond to the same target processing model.

[0157] For example, in the financial data calculation scenario in the financial field, the basic information used to match the target template in the calculation platform may include information such as type, issuer, circulation market, risk home country, construction method, template number, etc., where for financial data, its type and corresponding fields may be currency (CRN_CY), the fields corresponding to the issuer may be (INDUSTRY_GROUP, MARKET_ISSUE), the fields corresponding to the circulation market may be (MARKET_ISSUE), the fields corresponding to the risk home country may be (ULT_PARENT_CNTRY_OF_RISK), and the target template may be a yield curve template. For financial data A, its basic information is: currency is A1, issuer is A2, circulation market is A3, and risk home country is A4. For financial data B, its basic information is: currency is B1, issuer is B2, circulation market is B3, and risk home country is B4. The target processing models of financial data A and B both use the third-order spline model, but after calculation according to the third-order spline model, the target template that can be matched to financial data A is yield curve template A, and the target template that can be matched to financial data B is yield curve template B. It can be seen that when financial data A and B use the same calculation model, different fields corresponding to different basic information of financial data A and B can be matched to different yield curve templates.

[0158] Figure 4 The flowchart of the method for determining a target template according to an embodiment of the present disclosure is schematically shown.

[0159] like Figure 4 As shown, the method 400 for determining a target template of this embodiment includes a standard data table 401 , first standard data 402 , second standard data 403 , a target processing model 404 , a processing template 405 , and a target template 406 .

[0160] According to an embodiment of the present disclosure, after the standard data table 401 is generated according to the target data, the first standard data 402 and the second standard data 403 are acquired from the standard data table 401 .

[0161] According to an embodiment of the present disclosure, after acquiring the first standard data 402 , the target processing model 404 is determined according to the fields 402 in the first standard data.

[0162] According to an embodiment of the present disclosure, a plurality of processing templates 405 having at least one identical attribute information field with the target processing model 404 are selected from a plurality of processing templates stored in the computing platform.

[0163] According to an embodiment of the present disclosure, after determining multiple processing templates 405 , a one-to-one matching operation is performed between the fields corresponding to the acquired second standard data 403 and the multiple processing templates 405 , and the processing template that successfully matches the target processing model can be used as the target template 406 .

[0164] The embodiments of the present disclosure utilize the first standard data and the second standard data in the standard data table to perform double-layer matching on the target processing model and the target template respectively, which can more accurately determine the target template corresponding to the target data to improve the processing efficiency of the computing platform for resource calculation.

[0165] Figure 5 The flowchart of the method for obtaining the first verification result according to the embodiment of the present disclosure is schematically shown.

[0166] like Figure 5 As shown, the method 500 includes operations S510 to S540.

[0167] In operation S510, a data verification request is periodically sent to a target data source.

[0168] In operation S520, verification data returned by the target data source is received.

[0169] In operation S530 , the verification data and the target data are compared to obtain a first verification result.

[0170] In operation S540, in response to the first verification result indicating an abnormality, the first verification result is pushed to the user through a preset channel.

[0171] According to an embodiment of the present disclosure, the period for sending a data verification request may be set according to the attributes of the target data.

[0172] According to an embodiment of the present disclosure, verification data is used to verify the integrity and accuracy of target data. The verification data may include all basic attribute information associated with the target object, such as target object type, data processing rules, deadline, issuing entity, location of business unit, transaction channel and other information.

[0173] According to an embodiment of the present disclosure, the first verification result is used to characterize whether the fields of the verification data and the target data match, and the verification result includes a correct match or an abnormal match.

[0174] According to an embodiment of the present disclosure, a preset channel is used to push the first verification result to the user. The preset channel may be manually selected and set in advance, and the push channel includes an interactive interface, an email, a text message, etc.

[0175] According to an embodiment of the present disclosure, according to the time period set by the user, i.e., the information administrator, the computing platform periodically sends data verification request messages to the target data source. After receiving the verification data returned by the target data source, i.e., the database, the computing platform compares and matches the target data with the fields of the verification data to obtain a first verification result to confirm whether the target data is complete and accurate.

[0176] According to an embodiment of the present disclosure, if the first verification result indicates data anomaly, the target data is missing or incorrect, and the verification result will be sent to the information administrator in a form such as an email to prompt the user or information administrator of data access anomaly.

[0177] According to an embodiment of the present disclosure, the pushed first verification result content may include abnormal information prompt, target object name, domain name, domain content, etc. Among them, the domain name can be used to identify the location of abnormal data.

[0178] For example, in the financial field scenario, the computing platform can verify the integrity of financial data online with a third-party database at the end of each day. The verification scope is bonds with trading positions or pledge positions within one year. If the basic information of the financial data is missing or incorrect, an error message will be sent to the information administrator and the user group of the business management office via email. The content of the email can be: "Basic information of financial data is incorrect: ISINxxx, CUSIPxxx, financial data name xxx, domain name xxx, domain content xxx". The verification rules can be set as follows: the fields to be verified in the calculation platform may include CPN_TYP interest calculation type, MARKET_ISSUE issuance market, INDUSTRY_GROUP issuing entity, expiration date, option type, reset index, Callable, and Putable. For these 8 fields, all fields in the database corresponding to these 8 fields will be automatically obtained from the third-party database at the end of each day, including CPN_TYP (full), MARKET_ISSUE (MARKET_SECTOR_DES <> Mtge), INDUSTRY_GROUP (full), MTY_TYP (MARKET_SECTOR_DES <> Mtge), RESET_INDEX (CPN_TYP = FLOATING or VARIABLE), Callable, and Putable. The fields to be verified in the calculation platform are compared one by one with the verification fields obtained from the third-party database to determine whether the basic information of the financial data in the calculation platform is missing or incorrect.

[0179] In the embodiment of the present disclosure, the computing platform periodically sends data verification requests to the data source, compares the target data with the verification data, and promptly pushes error information to the user when abnormal data occurs, so as to ensure the security and accuracy of the target data, thereby improving the security and accuracy of the computing platform.

[0180] According to an embodiment of the present disclosure, when the first verification result indicates that M first fields are abnormal, the M first fields are displayed through a third interactive interface, where M≥2. In response to a selection operation by a user on the third interactive interface, N second fields are determined from the M first fields, where M≥N≥1. The N second fields are added to the whitelist of the computing platform so that the N second fields are not verified during the next data verification process.

[0181] According to an embodiment of the present disclosure, the M first fields are used to represent multiple target data fields to be compared with the verification data.

[0182] According to an embodiment of the present disclosure, the third interactive interface is used to display multiple first fields, and can also provide users with an operation box for performing operations such as selection, ignoring, restoring, and querying, as well as a whitelist display box.

[0183] According to an embodiment of the present disclosure, the third interactive interface may also provide "update organization" and "verification field" filtering items, wherein "update organization" can filter any unit, while other units can only filter the content of the unit.

[0184] For example, in the verification abnormality information query result display interface, that is, the third interactive interface, the "affiliated institution" field can be renamed "updated institution", and the "updated teller" field can be kept consistent with the value of the field of the same name in the financial data basic information maintenance interface. The original "updated institution" field on the interface is renamed "verification institution", and a new "verification teller" field can be added. Therefore, a total of four fields "affiliated institution", "affiliated teller", "processing institution", and "processing teller" are displayed on the third interactive interface. "Affiliated institution" and "affiliated teller" can be obtained from the "updated user" and "updated institution" of the basic information of financial data. "Processing institution" and "processing teller" are used to record the users and institutions that operate the "third-party data overwrite", and the third interactive interface will no longer synchronously update the "updated user" and "updated institution" in the basic information of financial data after operating the "third-party data overwrite".

[0185] According to an embodiment of the present disclosure, the N second fields are used to characterize one or more fields that are inconsistent with the verification data but have no effect on the data calculation of the computing platform.

[0186] According to an embodiment of the present disclosure, the whitelist is used to record one or more second fields, that is, fields that have verification anomalies but have no impact on the computing platform. The data information corresponding to the field is included in the whitelist. This data information will be ignored in subsequent verifications of the computing platform, that is, the process of verifying and comparing the fields corresponding to the data information will be skipped.

[0187] According to an embodiment of the present disclosure, after obtaining the first verification result, the computing platform will determine whether the first verification result represents an abnormality in multiple first fields. If an abnormality exists, the abnormal multiple first fields will be displayed on the third interactive interface to prompt the user to view.

[0188] According to an embodiment of the present disclosure, after reading multiple first fields on the third interactive interface, the user can select at least one field that has no effect on the computing process of the computing platform from the multiple abnormal first fields displayed on the third interactive interface, and use it as the second field. The second field can be moved into the whitelist display box through the third interactive interface, or the second field can be ignored through the ignore option on the third interactive interface. The computing platform will automatically move the ignored second field into the whitelist by default.

[0189] For example, in the financial field scenario, the computing platform obtains the verification data of financial data A from a third-party database, and after comparing it with the target data of financial data A, it is found that there are abnormalities in the display of fields A and B after verification, but the modification of these two fields has no effect on the calculation process of the computing platform. Therefore, by moving fields A and B into the whitelist display box of the third interactive interface, the computing platform can ignore the verification abnormal data corresponding to these two fields, and the comparison process of fields A and B of financial data A will be skipped during the subsequent automatic verification at the end of each day. Among them, if financial data A is a bond, fields A and B can be the issuing entity (INDUSTRY_GROUP) field and the security key (SECURITY_KEY) field.

[0190] According to an embodiment of the present disclosure, the user can view the data information that has been moved into the whitelist through the query option on the third interactive interface, and can also remove the records that have been included in the whitelist through the restore option. The data information after being removed will restore the automatic verification function of the data field in the subsequent verification.

[0191] Figure 6 The flowchart of the method for determining the second field according to an embodiment of the present disclosure is schematically shown.

[0192] like Figure 6 As shown, the method 600 for determining the second field of this embodiment includes operations S601 to S607.

[0193] In operation S601, a first verification result is obtained.

[0194] In operation S602 , it is determined whether the first verification result indicates that the M first fields are abnormal.

[0195] In operation S603, M first fields are displayed on the third interactive interface.

[0196] In operation S604, the process is ended in response.

[0197] In operation S605, the user performs a selection operation on the third interactive interface.

[0198] In operation S606, N second fields are determined from the M first fields.

[0199] In operation S607 , the N second fields are moved into a white list.

[0200] According to an embodiment of the present disclosure, after obtaining the first verification result by executing operation S601, operation S602 is used to determine whether the first verification result represents that M first fields are abnormal. If so, it indicates that there is an abnormality, and operation S603 is executed to display the abnormal multiple first fields on the third interactive interface to prompt the user to view them. If not, operation S604 is executed to end the process.

[0201] According to an embodiment of the present disclosure, after the user reads the M first fields on the third interactive interface, by executing operation S605, the user can select from multiple abnormal first fields displayed on the third interactive interface, and by executing S606, select at least one field that has no effect on the computing process of the computing platform and use it as the second field. After determining the second field, execute operation S607, and the user can move the second field into the whitelist through the third interactive interface.

[0202] In the embodiment of the present disclosure, the user can flexibly select fields that do not affect the calculation and move them into the whitelist for ignore processing through interactive operations of the third interactive interface, so that the fields in the whitelist will not be repeatedly checked in subsequent verifications, which can effectively reduce the amount of data verification and improve data verification efficiency.

[0203] According to an embodiment of the present disclosure, after the first verification result is pushed to the user through a preset channel, it includes: in response to receiving an operation request for processing the first verification result, determining the request type and the user who sends the operation request; when it is determined that the request type is a query type and the user belongs to the first user or the second user, displaying the query result on a fourth interactive interface, wherein the first user only has the authority to view the first verification result, and the second user has the authority to view and process the first verification result; when it is determined that the request type is an exception handling type and the user is the second user, displaying an operation box on the fifth interactive interface so that the user can input an exception handling strategy through the operation box.

[0204] According to an embodiment of the present disclosure, the request type can be used to characterize the type of operation request sent by the user. The request type can include a query request and an exception handling request. Among them, the exception handling request can be a new request, a modification request, a deletion request, a reset request, an export request, etc.

[0205] According to an embodiment of the present disclosure, the first user and the second user have different operation permissions. The first user only has the operation permission to view the first verification result, that is, the first user can only perform query operations, and the second user has the permission to view and process the first verification result, that is, the second user can perform exception handling operations such as query, add, modify, delete, reset, and export.

[0206] According to an embodiment of the present disclosure, the fourth interactive interface may be used to display the first verification result queried by the user.

[0207] According to an embodiment of the present disclosure, the fifth interactive interface is used to provide the user with an exception handling operation box for processing the first verification result, and the exception handling operation box may include operation options such as adding, modifying, deleting, and resetting.

[0208] According to an embodiment of the present disclosure, the exception handling strategy may be a solution adopted by a user with processing authority to handle the exception information represented by the first verification result, for example, modifying, adding, deleting, and other operations on the exception information to correct and improve missing or erroneous information.

[0209] According to an embodiment of the present disclosure, after the first verification result is pushed to the user through a preset channel such as email, the user sends an operation request such as query and exception handling to the computing platform for the first verification result. After receiving the above operation request, the computing platform determines the specific type of the operation request and whether the user sending the operation request belongs to the first or second user.

[0210] According to an embodiment of the present disclosure, if it is determined that the request type is a query request and the user belongs to the first user or the second user, a fourth interactive interface may pop up in the computing platform to display the query result of the query exception information to the user.

[0211] According to an embodiment of the present disclosure, if it is determined through judgment that the request type is an exception handling type, and the user is a second user with processing operation authority, a fifth interactive interface may pop up in the computing platform and an operation box may be displayed to the second user, so that the second user can modify, add, delete, export, and perform other operations on the exception information by selecting an operation option in the operation box, and correct and improve any missing or erroneous information.

[0212] For example, in the basic bond information management scenario in the financial field, users can be divided into financial data information managers and financial data comparison information managers. The financial data information manager is the first user and can only query the abnormal verification results. The financial data comparison information manager is the second user and can not only query the abnormal verification results, but also modify, add, export and other processing operations on the abnormal verification results.

[0213] The embodiments of the present disclosure distinguish users with different operation permissions by judging the operation request type and user type sent by the user, and provide different operation interfaces for users with different permissions in a targeted manner, so as to improve the security of data processing on the user side.

[0214] According to an embodiment of the present disclosure, a method for obtaining a third verification result includes: batch acquiring P processing models and / or processing templates stored in a computing platform at a preset time, where P≥2; verifying the P processing models and / or processing templates based on a model mapping relationship or a template mapping relationship stored in the computing platform to obtain a second verification result; in response to the second verification result indicating that the model mapping relationship is normal, obtaining verification resource information at the current moment from a target data source; and comparing the verification resource information with the resource data obtained using the P processing models and / or processing templates to obtain a third verification result.

[0215] According to an embodiment of the present disclosure, the preset time is set by a user in a computing platform, and the preset time may be the end of each day, the end of each month, the end of each week, and the like.

[0216] According to an embodiment of the present disclosure, the second verification result may be used to represent a verification result of verifying a matching result between a target object and a processing model and / or a processing template by utilizing a mapping relationship of a model or a template.

[0217] According to an embodiment of the present disclosure, the verification resource information may be public verification resource data accessed from a database, and the verification resource data is calculated by a third-party system using public target data.

[0218] According to an embodiment of the present disclosure, the third verification result can be used to characterize the verification result obtained by comparing the public verification resource data accessed from the third-party database with the target resource data calculated by the processing model or processing template stored in the computing platform.

[0219] According to an embodiment of the present disclosure, after obtaining the second verification result and the third verification result, if the verification result indicates an abnormality, the computing platform can automatically send a reminder email at the end of each day. For example, the email subject can be "XXXX processing model and / or processing template matching abnormality reminder (XXXX year X month XX day)", and the email body can be a hyperlink. After clicking the hyperlink, you can jump to the corresponding query result page to view and export the processing model and / or processing template matching abnormality data information. The email sending range can be flexibly set by the administrator on the email reminder parameter page.

[0220] According to an embodiment of the present disclosure, at a preset time, such as the end of each day, multiple processing models and / or processing templates stored in the computing platform are obtained in batches, and the matching results between the target object and the processing model and / or processing template are re-verified based on the one-to-one correspondence between the processing model and / or processing template to obtain a second verification result.

[0221] According to an embodiment of the present disclosure, if the second verification result is normal, the verification resource data currently disclosed in the third-party system can be obtained from the target data source, ie, the third-party database.

[0222] According to an embodiment of the present disclosure, the computing platform calculates resource data based on the re-calibrated processing model and / or processing template, compares the resource data with the publicly available verification resource data, and the comparison result is the third verification result.

[0223] For example, in the scenario of verifying the calculation model of financial data, the calculation platform at the end of each day will re-verify the matching results of the financial data and the calculation model according to the mapping rules of the financial data calculation model, and take corresponding treatment measures according to the verification results. The calculation platform will also access the market yield data in the third-party database based on the matched financial data calculation model after re-verification, calculate the accrued interest and net price calculation results of the financial data, and compare them with the accrued interest and net price public data directly obtained from the third-party database to obtain the accuracy verification results of the financial data calculation model.

[0224] According to the above specific embodiments of the present disclosure, the accuracy check can be performed by calculating the error of the number of days of accrued interest of the financial data obtained on the computing platform. If the error of the calculated number of days is within the feasible range, it can be judged that the check result is accepted. The number of days error corresponding to the calculation result is shown in Table 2:

[0225] Calculation results Error in the number of days for calculating accrued interest -1.999 to -2.001 -2 days 0.999 to -1.001 -1 day -0.001 to 0.001 Day 0 0.999 to 1.001 1 day 1.999 to 2.001 2 days

[0226] Table 2 The day error corresponding to the calculation results

[0227] The specific verification method can be implemented by the following calculation formula: accrued interest calculation days error = (accrued interest calculated by the calculation platform - accrued interest of the target database) / daily accrued interest calculated by the calculation platform. If the calculation result is within the calculation result range of Table 2, it can be considered that the calculation days error is within [-2, 2], and the verification result can be judged as accepted, and the accrued interest calculation days error can be output through the output interface of the calculation platform, as well as the verification information, to ask the user whether to accept the judgment result.

[0228] According to another specific embodiment of the present disclosure, in the scenario of verifying the yield curve template of financial data, at the end of each day, based on the fact that the computing platform has realized automatic re-matching of the unmatched financial data yield curve template, the computing platform will further verify the yield curve template matched by all financial data, and compare it with the financial data yield curve mapping rules to determine whether they are consistent, and take corresponding processing measures based on the verification results.

[0229] Figure 7 The flowchart of the method for obtaining the third verification result according to the embodiment of the present disclosure is schematically shown.

[0230] like Figure 7 As shown, the method 700 for obtaining the third verification result of this embodiment includes S701 to S707.

[0231] In operation S701, a plurality of process models and / or process templates are obtained from a computing platform.

[0232] In operation S702, a second verification result is obtained.

[0233] In operation S703 , it is determined whether the second verification result indicates that the result is normal.

[0234] In operation S704, resource data is acquired.

[0235] In operation S705, verification resource information is acquired from the target data source.

[0236] In operation S706, a third verification result is obtained.

[0237] In operation S707, the process is ended in response.

[0238] According to an embodiment of the present disclosure, operation S701 is performed at a preset time to obtain multiple processing models and / or processing templates stored in the computing platform, and the matching results between the target object and the processing model and / or processing template are re-checked according to the mapping relationship between the processing model and / or processing template to obtain a second verification result.

[0239] According to an embodiment of the present disclosure, after executing operation S702, that is, after obtaining the second verification result, a judgment operation S703 is performed to determine whether the second verification result is normal. If so, operation S705 can be performed to obtain the verification resource information at the current moment from the target data source. If not, operation S707 will be performed to end the process.

[0240] According to an embodiment of the present disclosure, in operation S704, the computing platform obtains resource data based on the re-verified processing model and / or processing template, compares the resource data with the verification resource information, and obtains a third verification result through operation S706.

[0241] The embodiments of the present disclosure verify the processing model and / or processing template stored in the computing platform to ensure the accuracy of the model, calculate the resource data based on the verification result, and then compare it with the verification resource information accessed from the third-party database. The accuracy of the resource calculation performed by the processing model and / or processing template can be verified based on the obtained verification result, thereby improving the calculation accuracy of the computing platform.

[0242] Figure 8 The flowchart of the method for acquiring resource data according to an embodiment of the present disclosure is schematically shown.

[0243] like Figure 8 As shown, the method 800 for acquiring resource data in this embodiment includes S801 to S814.

[0244] According to an embodiment of the present disclosure, in operation S801, a data acquisition request is sent to the target data source, and operation S802 is performed to determine whether the computing platform successfully receives the target data associated with the target object from the target data source. If so, operation S803 is performed to receive the target data; if not, operation S804 is performed to display abnormal reception information on the second interactive interface. After the user performs an import operation, operation S805 is performed to obtain and parse the import file imported by the user to obtain the target data.

[0245] According to an embodiment of the present disclosure, the target data received in S803 and the target data imported in S805 can be displayed in the first interactive interface through operation S806. The displayed target data can generate a standard data table corresponding to the target object by executing operation S809.

[0246] According to an embodiment of the present disclosure, by executing operation S807, the fields to be input corresponding to the target data can also be displayed in the first interactive interface. The user can enter the fields to be input in the input box in the first interactive interface, and after obtaining the field value of the field to be input by executing S808, the target data and the field value to be input displayed on the first interactive interface are parsed and extracted. By executing operation S809, a standard data table corresponding to the target object can also be generated.

[0247] According to an embodiment of the present disclosure, the fields to be input may be, for example, when obtaining basic information of foreign currency data, i.e., target data, in a financial scenario. The fields displayed on the first interactive page may include eight fields, namely, MAEKET_ISSUE (circulation market), MARKET_SECTOR_DES (security key), RESET_INDEX (floating interest rate index), CPN_TYP (interest calculation type), MTY_TYP (option type), ULT_PARENT_CNTRY_OF_RISK (risk home country), Callable, and Putable. Among them, the ULT_PARENT_CNTRY_OF_RISK (risk home country) field is a mandatory item among the eight fields. This field is the field to be input. This field needs to be entered by a financial data information administrator instead of being imported from the target data source, i.e., a third-party database. The remaining seven fields are non-mandatory items and can be directly obtained from the third-party database.

[0248] According to an embodiment of the present disclosure, after generating a standard data table, operation S810 is performed to obtain first standard data and second standard data in the standard data table, and the first standard data is used for matching and operation S811 is performed to determine a target processing model. After determining the target processing model, multiple processing templates related to the target processing model are determined.

[0249] According to an embodiment of the present disclosure, according to the acquired second standard data, a processing template matching the second standard data is selected from a plurality of processing templates, and operation S812 is performed to determine the matching processing template as a target template.

[0250] According to an embodiment of the present disclosure, after determining the target template, operation S813 is performed, by matching the data information in the standard data table with the data information of the processing template, and then performing mathematical operations, logical reasoning and the like on the matched target data to obtain resource data.

[0251] According to an embodiment of the present disclosure, after obtaining the resource data, operation S814 is executed to call the output interface of the computing platform to output the resource data in a target form, thereby terminating the data processing flow based on the computing platform.

[0252] For example, in the scenario of calculating the yield to maturity in the financial field, if the target object is a bond, the calculation platform can access the China Bond daily end yield curve data, where the yield curve data includes the yield curve number, yield curve name, term structure, and yield rate information.

[0253] According to a specific embodiment of the present disclosure, the bond yield is analyzed based on the matching comparison or customized matching comparison relationship between the bond and the yield curve, and the analysis content includes the valuation yield, interest value-added tax, interest income tax, and pre-tax yield.

[0254] According to a specific embodiment of the present disclosure, based on the real-time bond valuation information in the third-party database imported by the user, a processing model such as a third-order linear interpolation method can be used to generate a matching target processing template such as a yield curve template according to a predetermined input and output term structure. If the data cannot be automatically accessed for various specific reasons, the system can support the user's manual import based on a worksheet format file at a certain frequency.

[0255] According to a specific embodiment of the present disclosure, based on the single bond yield market data imported by the user and the information on whether to participate in the construction of the yield curve field, the basic information of the bonds stored in the calculation platform is queried to obtain the remaining term, thereby establishing a curve template. After obtaining the yield curve, the calculation platform can manually modify the yield curve data and spread data based on the expectations of future interest rates and future spreads, and calculate the various indicators of single bonds and combinations at a certain time based on the interest rate scenario. Based on the existing portfolio and new investments, the exposure and income at different points in time are calculated to derive the yield to maturity of individual bonds.

[0256] According to a specific embodiment of the present disclosure, the real-time spread of yield can be defined as the difference between the yield of a single bond and the yield of the remaining term. The calculation method used when calculating the real-time spread has a priority order, such as the first priority real-time spread can be the difference between the real-time single bond yield and the real-time yield curve; the second priority real-time spread can be the difference between the real-time single bond yield and the China Bond Day-End Yield Curve; the third priority real-time spread can be the difference between the China Bond Day-End Valuation Single Bond Yield and the China Bond Day-End Yield Curve.

[0257] According to a specific embodiment of the present disclosure, if both the real-time single bond yield and the real-time yield curve of bond A exist, the first priority calculation is used. For example, if the real-time single bond yield of bond A exists but the real-time yield curve does not exist, the second priority calculation can be used. If neither the real-time single bond yield nor the real-time yield curve of bond A exists, the third priority calculation can be used.

[0258] According to a specific embodiment of the present disclosure, when importing data from a third-party database, the user needs to be prompted to import data that contains at least an 8-point term structure for constructing a real-time yield curve.

[0259] According to an embodiment of the present disclosure, in the case where a third-party database does not provide data on holidays, the computing platform may use the previous day's end-of-day data to perform a base processing on today's data.

[0260] According to the embodiments of the present disclosure, for the situation where a one-to-one correspondence cannot be established with the target template according to the matching rules in the computing platform, the computing platform can provide a foreground mapping function. In addition, for the situation where the computing platform has established a mapping relationship for the financial data and the user wishes to modify it manually, the user can modify it manually, and after the manual modification, the original system automatic mapping becomes invalid.

[0261] Fig. 9 The flowchart of the first verification result verification method according to the embodiment of the present disclosure is schematically shown.

[0262] According to an embodiment of the present disclosure, operation S901 is performed after acquiring the target data, and a data verification request is periodically sent to the target data source. After the target data source returns the verification data, the computing platform executes operation S902 to receive the returned verification data, and compares it with the target data acquired in S903, and obtains the first verification result after the comparison through operation S904.

[0263] According to an embodiment of the present disclosure, after obtaining the first verification result, a judgment operation S905 is performed to determine whether the first verification result is abnormal. If so, operation S906 is performed and the first verification result can be pushed to the user via email. If not, it means that the first verification result is normal and the target data is correct, so S916 can be executed to end the process.

[0264] According to an embodiment of the present disclosure, after the first verification result is pushed to the user, a judgment operation S908 can be performed to determine whether the M first fields in the first verification result are abnormal. If so, operation S909 can be performed to display the M first fields on the third interactive interface. The user can perform operation S910 to select an ignorable field that does not affect the calculation as the second field from the M first fields displayed on the third interactive interface, and can perform operation S911 to move the second field into the whitelist. The fields in the whitelist can be skipped in subsequent verifications. If not, perform S917 to end the process.

[0265] According to the embodiment of the present disclosure, after the first verification result is pushed to the user, operation S907 can also be performed. After the computing platform receives the user's operation request to process the first verification result, it determines the request type and the user who sent the operation request, and performs judgment operation S912 to determine whether the request type is a query type and the user belongs to the first user or the second user. If yes, operation S913 can be performed to display the query result on the fourth interactive interface. If not, judgment operation S914 can be performed to determine whether the request type is an exception handling type and the user is the second user. If yes, S915 can be performed to display the operation box on the fifth interactive interface to provide the user with operation options such as modification, deletion, and addition. If no, S918 can be performed to end the process.

[0266] Fig.10 The structural block diagram of a data processing device based on a computing platform according to an embodiment of the present disclosure is schematically shown.

[0267] like Fig.10 As shown, the data processing device 1000 based on the computing platform of this embodiment includes a sending module 1010 , a receiving module 1020 , a generating module 1030 , a matching module 1040 , a processing module 1050 and an output module 1060 .

[0268] The sending module 1010 is used to send a data acquisition request to a target data source, where the data acquisition request is used to request to acquire target data associated with a target object. In one embodiment, the sending module 1010 can be used to perform the operation S210 described above, which will not be described in detail here.

[0269] The receiving module 1020 is used to receive target data associated with the target object from the target data source. In one embodiment, the receiving module 1020 can be used to perform the operation S220 described above, which will not be described in detail here.

[0270] The generating module 1030 is used to process the target data and generate a standard data table corresponding to the target object. In one embodiment, the generating module 1030 can be used to perform the operation S230 described above, which will not be described in detail here.

[0271] The matching module 1040 is used to determine a target template that matches the standard data table from a plurality of processing templates stored in the computing platform, wherein the processing template is used to process the standard data table according to a preset business logic. In one embodiment, the matching module 1040 can be used to perform the operation S240 described above, which will not be described in detail here.

[0272] The processing module 1050 is used to process the standard data table using the target template to obtain processed resource data. In one embodiment, the processing module 1050 can be used to perform the operation S250 described above, which will not be described in detail here.

[0273] The output module 1060 is used to call the output interface to output the processed resource data in the target form. In one embodiment, the output module 1060 can be used to perform the operation S260 described above, which will not be described in detail here.

[0274] According to an embodiment of the present disclosure, the data processing device 1000 based on a computing platform of this embodiment further includes a first display module and a first acquisition module.

[0275] The first display module is used to display the target data in the first interactive interface, wherein the first interactive interface also includes fields to be input corresponding to the target data. In one embodiment, the first display module can also provide viewing and operation options to the user, and the first interactive interface includes fields to be input corresponding to the target data and data source import fields, wherein the fields to be input need to be entered by user input instead of being imported from the target data source.

[0276] The first acquisition module is used to obtain the field value of the field to be input in response to the user's input operation. In one embodiment, after the user performs an input operation on the field to be input in the first display module, the field value corresponding to the field can be obtained.

[0277] According to an embodiment of the present disclosure, the data processing device 1000 based on a computing platform of this embodiment further includes a second display module and a second acquisition module.

[0278] The second display module is used to display abnormal reception information on the second interactive interface in response to the failure to successfully receive the target data associated with the target object from the target data source. In one embodiment, after sending a data acquisition request to the target data source, it is determined whether the target data associated with the target object from the target data source, i.e., the database, is successfully received. If it is not successfully received, a message prompt box of abnormal reception information will pop up on the second interactive interface to remind the user that the database information access failed.

[0279] The second acquisition module is used to respond to the user's import operation on the second interactive interface, acquire and parse the import file, and obtain the target data. In one embodiment, after receiving the abnormal reception information, the user can upload the file required to be associated with the target object to the file upload column of the second interactive interface through a manual import operation. The computing platform obtains the import file uploaded by the user, parses and identifies the import file, and extracts the basic information associated with the target object as the target data.

[0280] According to an embodiment of the present disclosure, the generating module 1030 includes a first generating unit.

[0281] The first generating unit is used to process the target data and the field values ​​of the fields to be input, and generate a standard data table corresponding to the target object. In one embodiment, after obtaining the target data and the field values ​​of the fields to be input, the field values ​​in the target data and the field values ​​of the fields to be input are extracted, and the extracted field values ​​are imported into the table to automatically generate a standard data table corresponding to the target object.

[0282] According to an embodiment of the present disclosure, the matching module 1040 includes a first determination unit, a second determination unit, and a third determination unit.

[0283] The first determination unit is used to determine the target processing model according to the first standard data in the standard data table, wherein the first standard data is used to characterize the attributes of the target data. In one embodiment, after the target data is used to generate the standard data table, the first standard data in the standard data table, i.e., the type of target object, calculation type, calculation cycle, calculation rule and other data information fields are used to distinguish and map to the corresponding calculation model, and the calculation model matching these fields is selected as the target processing model.

[0284] The second determining unit is used to determine a plurality of processing templates related to the target processing model. In one embodiment, a plurality of processing templates having at least one identical attribute information field with the target processing model are selected from a plurality of processing templates stored in the computing platform.

[0285] The third determination unit is used to determine the target template from the plurality of processing templates according to the second standard data in the standard data table, wherein the second standard data is used to characterize the information of the entity that publishes the target object. In one embodiment, after the plurality of processing templates are determined, the second standard data in the standard data table, i.e., the fields of data information such as the business unit or organization, transaction channel, and location of the business unit of the target object, are matched one-to-one with the plurality of processing templates, and the matched processing template can be used as the target template.

[0286] According to an embodiment of the present disclosure, the data processing device 1000 based on the computing platform further includes a first verification module.

[0287] According to an embodiment of the present disclosure, the first verification module includes a first sending unit, a first receiving unit, a first comparing unit and a first pushing unit.

[0288] The first sending unit is used to periodically send a data verification request to the target data source. In one embodiment, the first sending unit can be used to perform the operation S510 described above, which will not be repeated here.

[0289] The first receiving unit is used to receive the verification data returned by the target data source. In one embodiment, the first receiving unit can be used to perform the operation S520 described above, which will not be described in detail here.

[0290] The first comparison unit is used to compare the verification data and the target data to obtain a first verification result. In one embodiment, the first comparison unit can be used to perform the operation S530 described above, which will not be described in detail here.

[0291] The first push unit is used to push the first verification result to the user through a preset channel in response to the first verification result indicating an abnormality. In one embodiment, the first push unit can be used to perform the operation S540 described above, which will not be described in detail here.

[0292] According to an embodiment of the present disclosure, the data processing device 1000 based on the computing platform further includes a second verification module.

[0293] According to an embodiment of the present disclosure, the second verification module includes a first display unit, a fourth determination unit, and a first operation unit.

[0294] The first display unit is used to display the M first fields through the third interactive interface when the first verification result indicates that the M first fields are abnormal, where M≥2. In one embodiment, after obtaining the first verification result, it is determined whether the first verification result indicates that the M first fields are abnormal. If there is an abnormality, the abnormal multiple first fields are displayed on the third interactive interface to prompt the user to view.

[0295] The fourth determination unit is used to determine N second fields from M first fields in response to a selection operation of the user on the third interactive interface, where M≥N≥1. In one embodiment, the user can select at least one field that has no effect on the computing process of the computing platform from among the multiple abnormal first fields displayed on the third interactive interface, and use it as the second field.

[0296] The first operation unit is used to add the N second fields to the whitelist of the computing platform so that the N second fields are not verified during the next data verification process. In one embodiment, the user can move the data information corresponding to the second field into the whitelist 6 through the ignore option on the third interactive interface, and the second field included in the whitelist can be ignored in subsequent verification, that is, the process of verifying and comparing the second field will be skipped.

[0297] According to an embodiment of the present disclosure, the data processing device 1000 based on the computing platform further includes a third verification module.

[0298] According to an embodiment of the present disclosure, the third verification module further includes a fifth determination unit, a second display unit, and a third display unit.

[0299] The fifth determination unit is used to determine the request type and the user who sent the operation request in response to receiving the operation request for processing the first verification result. In one embodiment, after the first verification result is pushed to the user through a preset channel such as an email, the user sends an operation request such as a query or exception handling to the computing platform for the first verification result. After receiving the above operation request, the computing platform determines the specific type of the operation request and whether the user who sent the operation request is the first user or the second user.

[0300] The second display unit is used to display the query result on the fourth interactive interface when it is determined that the request type is a query type and the user belongs to the first user or the second user, wherein the first user only has the authority to view the first verification result and the second user has the authority to view and process the first verification result. In one embodiment, if it is determined that the request type is a query request and the user belongs to the first user or the second user, the fourth interactive interface can be popped up in the computing platform to display the query result of the query exception information to the user.

[0301] The third display unit is used to display an operation box on the fifth interactive interface when it is determined that the request type is an exception handling type and the user is a second user, so that the user can input an exception handling strategy through the operation box. In one embodiment, if it is determined that the request type is an exception handling type and the user is a second user with processing operation authority, the fifth interactive interface can be popped up in the computing platform and the operation box can be displayed to the second user, so that the second user can modify, add, delete, etc. the exception information by selecting the operation option in the operation box, and correct and improve the missing or incorrect information.

[0302] According to an embodiment of the present disclosure, the data processing device 1000 based on the computing platform further includes a fourth verification module.

[0303] According to an embodiment of the present disclosure, the fourth verification module further includes a third acquisition unit, a fourth acquisition unit, a fifth acquisition unit and a second comparison unit.

[0304] The third acquisition unit is used to batch acquire P processing models and / or processing templates stored in the computing platform at a preset time, where P≥2. In one embodiment, at the end of each day, a plurality of processing models and / or processing templates stored in the computing platform are batch acquired.

[0305] The fourth acquisition unit is used to verify the P processing models and / or processing templates based on the model mapping relationship or template mapping relationship stored in the computing platform to obtain a second verification result. In one embodiment, the matching result between the target object and the processing model and / or processing template is rechecked according to the mapping relationship between the processing model and / or processing template to obtain the second verification result.

[0306] The fifth acquisition unit is used to obtain the verification resource information at the current moment from the target data source in response to the second verification result indicating that the second verification result is normal. In one embodiment, after obtaining the second verification result, it is determined whether the second verification result indicates that the second verification result is normal. If yes, the verification resource information calculated and disclosed on the third-party platform at the current moment can be obtained from the target data source, i.e., the database.

[0307] The second comparison unit is used to compare the verification resource information with the resource data obtained by using the P processing models and / or the processing templates to obtain a third verification result. In one embodiment, at the end of each day, the computing platform calculates the resource data based on the re-calibrated processing model and / or processing template, compares the resource data with the verification resource information, and the comparison result is the third verification result.

[0308] According to an embodiment of the present disclosure, any multiple modules among the sending module 1010, the receiving module 1020, the generating module 1030, the matching module 1040, the processing module 1050 and the output module 1060 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module.

[0309] According to an embodiment of the present disclosure, at least one of the sending module 1010, the receiving module 1020, the generating module 1030, the matching module 1040, the processing module 1050 and the output module 1060 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or by any one of the three implementation methods of software, hardware and firmware or by an appropriate combination of any of them. Alternatively, at least one of the sending module 1010, the receiving module 1020, the generating module 1030, the matching module 1040, the processing module 1050 and the output module 1060 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be performed.

[0310] Fig.11 A block diagram of an electronic device according to a data processing method based on a computing platform according to an embodiment of the present disclosure is schematically shown.

[0311] like Fig.11As shown, the electronic device 1100 according to an embodiment of the present disclosure includes a processor 1101, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1102 or a program loaded from a storage part 1108 to a random access memory (RAM) 1103. The processor 1101 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1101 may also include an onboard memory for caching purposes. The processor 1101 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0312] In RAM1103, various programs and data required for the operation of electronic device 1100 are stored. Processor 1101, ROM1102 and RAM 1103 are connected to each other through bus 1104. Processor 1101 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 1102 and / or RAM 1103. It should be noted that the program can also be stored in one or more memories other than ROM 1102 and RAM 1103. Processor 1101 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0313] According to an embodiment of the present disclosure, the electronic device 1100 may further include an input / output (I / O) interface 1105, which is also connected to the bus 1104. The electronic device 1100 may further include one or more of the following components connected to the input / output I / O interface 1105: an input portion 1106 including a keyboard, a mouse, etc.; an output portion 1107 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 1108 including a hard disk, etc.; and a communication portion 1109 including a network interface card such as a LAN card, a modem, etc. The communication portion 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the I / O interface 1105 as needed. A removable medium 1111, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1110 as needed, so that a computer program read therefrom is installed into the storage portion 1108 as needed.

[0314] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0315] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus, or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 1102 and / or RAM 1103 described above and / or one or more memories other than ROM 1102 and RAM 1103.

[0316] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the above method provided by the embodiment of the present disclosure.

[0317] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 1101. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0318] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 1109, and / or installed from a removable medium 1111. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0319] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1109, and / or installed from the removable medium 1111. When the computer program is executed by the processor 1101, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0320] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0321] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0322] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0323] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present disclosure. It should be understood that the above description is only a specific embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A data processing method based on a computing platform, comprising: Sending a data acquisition request to a target data source, wherein the data acquisition request is used to request to acquire target data associated with a target object; receiving the target data associated with the target object from the target data source; Processing the target data to generate a standard data table corresponding to the target object; Determining a target template that matches the standard data table from a plurality of processing templates stored in the computing platform, wherein the processing template is used to process the standard data table according to a preset business logic; Processing the standard data table using the target template to obtain processed resource data; The output interface is called to output the processed resource data in a target form.

2. The method according to claim 1, wherein: After receiving the target data associated with the target object from the target data source, the method further includes: Displaying the target data in a first interactive interface, wherein the first interactive interface further includes a field to be input corresponding to the target data; In response to the user's input operation, obtaining the field value of the field to be input; The processing of the target data to generate a standard data table corresponding to the target object further includes: The target data and the field values ​​of the fields to be input are processed to generate a standard data table corresponding to the target object.

3. The method according to claim 1 or 2, further comprising: In response to unsuccessful reception of the target data associated with the target object from the target data source, displaying abnormal reception information on the second interaction interface; as well as In response to the user's import operation on the second interactive interface, the import file is acquired and parsed to obtain the target data.

4. The method according to claim 1 or 2, wherein: The step of determining a target template matching the standard data table from a plurality of processing templates stored in the computing platform comprises: Determining a target processing model according to first standard data in the standard data table, wherein the first standard data is used to characterize the attributes of the target data; determining a plurality of process templates associated with the target process model; and The target template is determined from the plurality of processing templates according to second standard data in the standard data table, wherein the second standard data is used to characterize information of an entity that publishes the target object.

5. The method according to claim 1 or 2, further comprising: Periodically sending a data verification request to the target data source; Receiving verification data returned by the target data source; Comparing the verification data with the target data to obtain a first verification result; as well as In response to the first verification result indicating an abnormality, the first verification result is pushed to the user through a preset channel.

6. The method according to claim 5, further comprising: When the first verification result indicates that M first fields are abnormal, displaying the M first fields through a third interactive interface, M≥2; In response to a selection operation of the user on the third interactive interface, determining N second fields from the M first fields, M≥N≥1; The N second fields are added to the whitelist of the computing platform so that the N second fields are not verified during the next data verification process.

7. The method according to claim 5, wherein: After the first verification result is pushed to the user through the preset channel, the method further includes: In response to receiving an operation request for processing the first verification result, determining a request type and a user sending the operation request; When it is determined that the request type is a query type and the user is a first user or a second user, displaying the query result on a fourth interactive interface, wherein the first user only has the authority to view the first verification result, and the second user has the authority to view and process the first verification result; When it is determined that the request type is an exception handling type and the user is a second user, an operation box is displayed on the fifth interaction interface so that the user can input an exception handling strategy through the operation box.

8. The method according to claim 1 or 2, further comprising: Batch acquire P processing models and / or processing templates stored in the computing platform at a preset time, where P≥2; Based on the model mapping relationship or the template mapping relationship stored in the computing platform, verify the P processing models and / or the processing templates to obtain a second verification result; In response to the second verification result indicating that the verification result is normal, obtaining verification resource information at the current moment from the target data source; as well as The verification resource information is compared with the resource data obtained by using the P processing models and / or the processing templates to obtain a third verification result.

9. A data processing device based on a computing platform, comprising: A sending module, used for sending a data acquisition request to a target data source, wherein the data acquisition request is used for requesting to acquire target data associated with a target object; A receiving module, configured to receive the target data associated with the target object from the target data source; A generating module, used for processing the target data to generate a standard data table corresponding to the target object; A matching module, used to determine a target template that matches the standard data table from a plurality of processing templates stored in the computing platform, wherein the processing template is used to process the standard data table according to a preset business logic; A processing module, used for processing the standard data table using the target template to obtain processed resource data; The output module is used to call the output interface to output the processed resource data in a target form.

10. An electronic device comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to execute the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 8.

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