Business data processing methods, devices and electronic equipment

Abstract

This application discloses a method, apparatus, and electronic device for processing business data. The method is applicable to the fields of big data technology, fintech, or other technical fields. The method includes: determining tag information for business data within a financial institution based on business scenarios and business needs within those scenarios; processing the business data based on the tag information to obtain a target tag table; determining the business systems associated with the target tag table based on business needs to obtain target business systems; and responding to data processing instructions sent by the target business systems based on the target tag table. This application solves the problem in related technologies where responding to data processing instructions from different business systems results in low data processing efficiency due to the high degree of repetition among numerous data processing instructions, requiring significant cluster resources to process these highly repetitive instructions.

Description

Technical Field

[0001] This application relates to the fields of big data technology, fintech, or other technical fields. Specifically, it relates to a method, apparatus, and electronic device for processing business data. Background Technology

[0002] With the development of big data technology, the scale and complexity of data are constantly increasing. Traditional data organization and processing methods are no longer sufficient to meet the needs of enterprises, necessitating a more flexible and efficient way to manage and utilize data. The establishment and use of a tagging system is of significant practical importance for data asset construction in the context of big data.

[0003] Tags are data assets derived from processed raw data. By combining business needs and rules, key information is extracted from the raw data, allowing for finer-grained segmentation and enabling low-cost data usage in business scenarios. The construction of a tagging system is often closely related to a data platform. A data platform typically manages data through business data and business needs. This system also uses business scenario-driven tags to manage data and provide support for front-end business processes.

[0004] However, as data jobs accumulate within the data platform, a large number of these jobs exhibit high repetition. Furthermore, these data jobs are scattered across different business scenarios, making integration and reuse difficult. When highly repetitive data jobs are executed repeatedly, a significant amount of computing resources are wasted on repetitive tasks, leading to a waste of computing resources and reducing enterprise efficiency.

[0005] Currently, there is no effective solution to the problem of low data processing efficiency when responding to data processing instructions from different business systems, due to the high degree of repetition among a large number of data processing instructions, which requires a large amount of cluster resources to process the highly repetitive data processing instructions. Summary of the Invention

[0006] The main objective of this application is to provide a method, apparatus, and electronic device for processing business data, in order to solve the problem in the related art where, when responding to data processing instructions from different business systems, a large number of data processing instructions are highly repetitive, requiring a large amount of cluster resources to process these highly repetitive instructions, resulting in low data processing efficiency.

[0007] To achieve the above objectives, according to one aspect of this application, a method for processing business data is provided. The method includes: determining tag information for business data in a financial institution based on a business scenario and business requirements within the business scenario, wherein the tag information describes the theme and attributes of the business data; processing the business data based on the tag information and writing the processed tag information into a data table to obtain a target tag table; determining a business system related to the target tag table based on the business requirements to obtain a target business system; and upon receiving a data processing instruction from the target business system, obtaining the data requested by the data processing instruction based on the target tag table to obtain target data, and responding to the data processing instruction based on the target data.

[0008] Furthermore, determining the tag information of the business data in the financial institution based on the business scenarios and business requirements in the business scenarios includes: determining the key fields of the business data based on the business scenarios to obtain the tag subject, wherein the key fields refer to fields in the business data that are related to the business scenarios; determining the attributes of the tag subject in the business data based on the business requirements to obtain tag attributes; and determining the tag information based on the tag subject and the tag attributes.

[0009] Further, processing the business data based on the tag information and writing the processed tag information into a data table to obtain a target tag table includes: collecting indicator data from the source database of the financial institution based on the tag information to obtain a target indicator table; determining the tag paradigm corresponding to each indicator data in the target indicator table based on the business requirements and the tag information, wherein the tag paradigm is used to indicate the data content required for the target tag table to be generated; processing the indicator data in the target indicator table based on the tag paradigm to obtain a target tag set corresponding to the target indicator table; aggregating the tag data in the target tag set and writing the aggregated tag data into a data table to obtain the target tag table.

[0010] Further, the process of collecting indicator data based on the tag information to obtain the target indicator table includes: collecting indicator data related to the tag information from the source database to obtain an indicator data set; determining the business scenario to which each indicator data belongs in the indicator data set to obtain the business scenario corresponding to each indicator data; aggregating the indicator data in the indicator data set according to the business scenario corresponding to each indicator data, and writing the aggregated indicator data into a data table to obtain the target indicator table.

[0011] Further, determining the tag paradigm corresponding to each indicator data in the target indicator table based on the business requirements and the tag information includes: determining the tag subject of each indicator data in the target indicator table based on the tag information; determining the tag attribute of each indicator data based on the business requirements and the tag information; determining the statistical frequency of the tag attribute of each indicator data based on the business requirements, thereby obtaining the tag frequency of the tag attribute of each indicator data; and determining the tag paradigm corresponding to each indicator data in the target indicator table based on the tag subject of each indicator data, the tag attribute of each indicator data, and the tag frequency of the tag attribute of each indicator data.

[0012] Further, aggregating the tag data in the target tag set and writing the aggregated tag data into a data table to obtain the target tag table includes: aggregating the target tags in the target tag set according to the tag paradigm of each target tag in the target tag set, and writing the aggregated tag data into a data table to obtain a first tag table; determining the association relationship between the tag subjects of each target tag in the first tag table; aggregating the tag data in the first tag table according to the association relationship between the paradigm subjects of each target tag, and writing the aggregated tag information into a data table to obtain the target tag table.

[0013] Further, obtaining the target data based on the target tag table and the data requested by the data processing instruction includes: determining the tag information required by the data processing instruction to obtain the target tag body and target tag attributes; determining the logical relationship between the target tag bodies based on the data processing instruction; generating a query statement based on the target tag attributes and the logical relationship to obtain the target query statement; and performing a data query in the target tag table based on the target query statement to obtain the target data.

[0014] Furthermore, after receiving the data processing instruction sent by the target business system, the method further includes: establishing a connection between the target tag table and the target business system to obtain a target connection; and sending the updated target tag table to the target business system through the target connection.

[0015] To achieve the above objectives, according to another aspect of this application, a business data processing apparatus is provided, comprising: a first determining unit, configured to determine tag information of business data in a financial institution based on a business scenario and business requirements in the business scenario, wherein the tag information is used to describe the theme and attributes of the business data; a processing unit, configured to process the business data based on the tag information and write the processed tag information into a data table to obtain a target tag table; a second determining unit, configured to determine a business system related to the target tag table based on the business requirements to obtain a target business system; and an obtaining unit, configured to, upon receiving a data processing instruction sent by the target business system, obtain the data requested by the data processing instruction based on the target tag table to obtain target data, and respond to the data processing instruction based on the target data.

[0016] Further, the first determining unit includes: a first determining subunit, used to determine the key fields of the business data based on the business scenario to obtain the tag body, wherein the key fields refer to fields in the business data that are related to the business scenario; a second determining subunit, used to determine the attributes of the tag body in the business data based on the business requirements to obtain tag attributes; and a third determining subunit, used to determine the tag information based on the tag body and the tag attributes.

[0017] Further, the processing unit includes: a collection subunit, used to collect indicator data from the source database of the financial institution based on the tag information to obtain a target indicator table; a fourth determination subunit, used to determine the tag paradigm corresponding to each indicator data in the target indicator table based on the business requirements and the tag information, wherein the tag paradigm is used to indicate the data content required for the target tag table to be generated; a processing subunit, used to process the indicator data in the target indicator table according to the tag paradigm to obtain a target tag set corresponding to the target indicator table; and an aggregation subunit, used to aggregate the tag data in the target tag set and write the aggregated tag data into a data table to obtain the target tag table.

[0018] Further, the acquisition subunit includes: an acquisition module, used to acquire indicator data related to the tag information from the source database to obtain an indicator data set; a first determination module, used to determine the business scenario to which each indicator data belongs in the indicator data set to obtain the business scenario corresponding to each indicator data; and a first aggregation module, used to aggregate the indicator data in the indicator data set according to the business scenario corresponding to each indicator data, and write the aggregated indicator data into a data table to obtain the target indicator table.

[0019] Further, the fourth determining subunit includes: a second determining module, used to determine the label subject of each indicator data in the target indicator table based on the label information; a third determining module, used to determine the label attribute of each indicator data based on the business requirements and the label information; a fourth determining module, used to determine the statistical frequency of the label attribute of each indicator data based on the business requirements, thereby obtaining the label frequency of the label attribute of each indicator data; and a fifth determining module, used to determine the label paradigm corresponding to each indicator data in the target indicator table based on the label subject of each indicator data, the label attribute of each indicator data, and the label frequency of the label attribute of each indicator data.

[0020] Further, the aggregation subunit includes: a second aggregation module, used to aggregate the target tags in the target tag set according to the tag paradigm of each target tag in the target tag set, and write the aggregated tag data into a data table to obtain a first tag table; a sixth determination module, used to determine the association relationship between the tag subjects of each target tag in the first tag table; and a third aggregation module, used to aggregate the tag data in the first tag table according to the association relationship between the paradigm subjects of each target tag, and write the aggregated tag information into a data table to obtain the target tag table.

[0021] Further, the acquisition unit includes: a fifth determining subunit, used to determine the tag information required by the data processing instruction, and obtain the target tag body and the target tag attribute; a sixth determining subunit, used to determine the logical relationship between the target tag bodies according to the data processing instruction; a generating subunit, used to generate a query statement according to the target tag attribute and the logical relationship, and obtain the target query statement; and a query subunit, used to perform a data query in the target tag table according to the target query statement, and obtain the target data.

[0022] Furthermore, the apparatus further includes: an establishment unit, configured to establish a connection between the target tag table and the target business system after determining the business system related to the target tag table based on the business requirements and obtaining the target business system, thereby obtaining a target connection; and a sending unit, configured to send the updated target tag table to the target business system through the target connection.

[0023] To achieve the above objectives, according to one aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the processing method for business data described in any of the above-mentioned methods.

[0024] To achieve the above objectives, according to one aspect of this application, an electronic device is provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the business data processing method described in any one of the above.

[0025] This application employs the following steps: determining tag information for business data within a financial institution based on its business scenarios and requirements, wherein the tag information describes the subject and attributes of the business data; processing the business data based on the tag information and writing the processed tag information into a data table to obtain a target tag table; determining the business systems associated with the target tag table based on the business requirements to obtain target business systems; and upon receiving a data processing instruction from the target business system, retrieving the data requested by the data processing instruction based on the target tag table to obtain target data, and responding to the data processing instruction based on the target data. This solves the problem in related technologies where, when responding to data processing instructions from different business systems, the high degree of repetition among numerous data processing instructions necessitates the expenditure of significant cluster resources to process these highly repetitive instructions, resulting in low data processing efficiency. By determining tag information based on business scenarios and needs, and processing business data in financial institutions based on this tag information, a target tag table is obtained. This aggregates fragmented business data, allowing direct queries on the target tag table upon receiving data processing instructions. This improves the response efficiency of data processing instructions and avoids the problem of low response efficiency caused by expending significant computing resources to process highly repetitive data processing instructions. It also enhances the reusability of tag data in the target tag table, achieving the effect of effectively and flexibly using tag data, and further improving the work efficiency of financial institutions. Attached Figure Description

[0026] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0027] Figure 1 This is a flowchart of a business data processing method provided in Embodiment 1 of this application;

[0028] Figure 2 This is a schematic diagram of an optional business data processing method provided in Embodiment 1 of this application. Figure 1 ;

[0029] Figure 3This is a schematic diagram of an optional business data processing method provided in Embodiment 1 of this application. Figure 2 ;

[0030] Figure 4 This is a schematic diagram of a business data processing apparatus according to Embodiment 2 of this application;

[0031] Figure 5 This is a schematic diagram of an electronic device for processing business data according to Embodiment 5 of this application. Detailed Implementation

[0032] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0033] It should be noted that the processing methods, apparatus, processors, and electronic devices specified in this application can be used in the financial technology field to process data processing requests, thereby improving the response efficiency of data processing requests. They can also be used in any field other than the financial technology field. The application fields of the processing methods, apparatus, processors, and electronic devices specified in this application are not limited.

[0034] It should be noted that the user information (including but not limited to user device information, user personal information, user information stored in financial institutions, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, data stored in financial institutions, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0035] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0036] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0037] Example 1

[0038] The present invention will now be described in conjunction with preferred implementation steps. Figure 1 This is a flowchart of a business data processing method according to Embodiment 1 of this application, such as... Figure 1 As shown, the method includes the following steps:

[0039] Step S101: Determine the tag information of the business data in the financial institution based on the business scenarios and business needs in the business scenarios. The tag information is used to describe the theme and attributes of the business data.

[0040] In this first embodiment, a business scenario refers to a series of events or situations designed based on the services provided by the financial institution or specific business processes. A business scenario can include information such as the various stages of business activities, participants, interaction methods, data flow, and required resources and technical support. Business data refers to business-related data stored within the financial institution. Tag information refers to key information within the business data, such as key fields like "customer account number" and "balance" in the business data table "account balance table".

[0041] Step S102: Process the business data based on the tag information and write the processed tag information into the data table to obtain the target tag table.

[0042] In this first embodiment, the business data needs to be extracted, processed, and calculated based on the determined tag information to obtain a target tag table composed of tag data.

[0043] Step S103: Determine the business system related to the target tag table based on business requirements to obtain the target business system.

[0044] After obtaining the target tag table in this first embodiment, the financial institution's business system or application needs to subscribe to the target tag table it requires to provide tag data or business data to the corresponding business system. It should be noted that the operation of a business system or application subscribing to the target tag table can also be seen as providing a data interface to the business system or application, through which tag data related to the target business system can be sent to the target business system.

[0045] Step S104: Upon receiving a data processing instruction from the target business system, obtain the data requested by the data processing instruction based on the target tag table, obtain the target data, and respond to the data processing instruction based on the target data.

[0046] In this first embodiment, the data processing instruction can be an instruction to query business data in the target business system, an instruction to process business data in the target business system, or other instructions to process data.

[0047] When a data processing instruction is received from the target business system, the system returns the data required by the instruction to the target business system based on the target tag table that the target business system has subscribed to. Specifically, a query statement can be generated based on the data processing instruction and the query can be performed in the target tag table, thus eliminating the need to process the data in the source database.

[0048] Optionally, in this first embodiment, Figure 2 This is a schematic diagram of an optional business data processing method provided in Embodiment 1 of this application. Figure 1 .like Figure 2 As shown, business data in different business scenarios is analyzed to determine the key fields (i.e., tag subjects) of the data tables containing the business data in each scenario, and at least one attribute (i.e., tag attribute) of the key fields is determined based on the specific business requirements of each scenario. Then, the determined tag information is further designed according to expert rules or business requirements to determine the statistical frequency of the tag attributes of each tag subject. Each tag subject is then used as a paradigm subject, and the tag attributes of each tag subject are used as the paradigm attributes of each paradigm subject. The tag paradigm is determined based on the statistical frequency of each paradigm subject, its paradigm attributes, and the paradigm attributes of each paradigm subject. Next, indicator data is collected from the business data of different business systems of the financial institution, and the indicator data is processed according to the tag paradigm to obtain a tag set. Next, the tag data in the tag set is aggregated, and the aggregation rules can be business scenarios, business requirements, data dimensions, etc., to obtain a target tag table. Finally, the target tag table is subscribed to in the application side or external business systems of the financial institution to process data processing requests based on the target tag table.

[0049] In summary, the business data processing method provided in Embodiment 1 of this application determines the tag information of business data in financial institutions based on business scenarios and business needs within those scenarios. The tag information describes the theme and attributes of the business data. The business data is processed based on the tag information, and the processed tag information is written into a data table to obtain a target tag table. The business systems associated with the target tag table are determined based on business needs to obtain target business systems. Upon receiving a data processing instruction from the target business system, the data requested by the data processing instruction is obtained based on the target tag table to obtain target data. The data processing instruction is then responded to based on the target data. This method solves the problem in related technologies where responding to data processing instructions from different business systems is inefficient due to the high degree of repetition among numerous data processing instructions, requiring significant cluster resources to process these highly repetitive instructions. By determining tag information based on business scenarios and needs, and processing business data in financial institutions based on this tag information, a target tag table is obtained. This aggregates fragmented business data, allowing direct queries on the target tag table upon receiving data processing instructions. This improves the response efficiency of data processing instructions and avoids the problem of low response efficiency caused by expending significant computing resources to process highly repetitive data processing instructions. It also enhances the reusability of tag data in the target tag table, achieving the effect of effectively and flexibly using tag data, and further improving the work efficiency of financial institutions.

[0050] Optionally, in the business data processing method provided in Embodiment 1 of this application, determining the tag information of the business data in the financial institution based on the business scenario and the business requirements in the business scenario includes: determining the key fields of the business data based on the business scenario to obtain the tag subject, wherein the key fields refer to the fields in the business data that are related to the business scenario; determining the attributes of the tag subject in the business data based on the business requirements to obtain the tag attributes; and determining the tag information based on the tag subject and the tag attributes.

[0051] In this first embodiment, in order to improve the processing efficiency of data processing instructions in financial institutions, different business scenarios in financial institutions can be analyzed, and the key fields of business data in the business scenarios can be analyzed. For example, in the business scenario of processing customer assets, the customer number or customer account can be used as the tag subject in this business scenario.

[0052] It is important to note that when determining the subject of a tag, there are often multiple data fields that can be identified as the subject of a tag. In this case, the subject of the tag can be determined based on a more specific business scenario. For example, if either the customer ID or the customer account can be used as the subject of a tag, the business scenario can be divided into more specific sub-scenarios based on the customer ID and the customer account. The customer ID and the customer account can then be used as the subject of the tag in each sub-scenarios. This will result in multiple dimensions of tag information (i.e., tag information with the customer ID as the first dimension and tag information with the customer account as the second dimension) in the business scenario of handling customer assets.

[0053] Furthermore, the tag body can be flexibly adjusted based on specific scenarios such as whether the business scenario involves streaming data and whether it supports relevant data sources. For example, if business scenario A1 supports data source B1, the tag body under business scenario A1 can be added based on data source B1.

[0054] After determining the tag subject, at least one attribute of the tag subject can be determined based on the business requirements of the business scenario. For example, the tag attributes corresponding to the tag subject can be determined based on the purpose, data content, data format, and data scope of the tag subject.

[0055] By conducting a detailed analysis of business scenarios and requirements, the tag construction process can be standardized, thereby determining the focus of data processing instructions in the business scenario, extracting the data required by the data processing instructions, avoiding the problem of performing repetitive work in order to respond to data processing instructions, and achieving the effect of improving the work efficiency of financial institutions.

[0056] Optionally, in the business data processing method provided in Embodiment 1 of this application, processing the business data based on tag information and writing the processed tag information into a data table to obtain a target tag table includes: collecting indicator data based on tag information in the source database of a financial institution to obtain a target indicator table; determining the tag paradigm corresponding to each indicator data in the target indicator table based on business needs and tag information, wherein the tag paradigm is used to indicate the data content required for the target tag table to be generated; processing the indicator data in the target indicator table based on the tag paradigm to obtain a target tag set corresponding to the target indicator table; aggregating the tag data in the target tag set and writing the aggregated tag data into a data table to obtain the target tag table.

[0057] In this first embodiment, to avoid the repeated execution of highly similar data processing requests in the business system, which would lead to a waste of computing resources and reduce the work efficiency of financial institutions, the business data in the financial institution can be processed based on the tag information analyzed based on the business scenario and business requirements. The data required for the data processing instructions can be extracted to obtain the target tag table, and then the data processing instructions can be responded to based on the tag data in the target tag table.

[0058] Specifically, indicator data related to tag information can be collected from the source database of financial institutions to obtain the target indicator table. The source database can be a database under different business systems in the financial institution, a database included in the data management center, or other databases that store data.

[0059] Then, a tag paradigm is determined based on business requirements and tag information. The tag paradigm specifies the data contained in the target tag table and the data format of the target tag table. For example, in one optional embodiment, the tag paradigm can be determined directly based on business requirements and tag information; alternatively, in another optional embodiment, the tag paradigm can be determined based on business requirements, tag information, and indicator data in the target indicator table.

[0060] Secondly, the indicator data in the target indicator table is extracted, calculated, and processed according to the predefined label paradigm to obtain a target label set containing label data. It is important to note that in this solution, when processing the indicator data in the target indicator table according to the label paradigm, in addition to extracting the data required by the label paradigm to obtain the label data corresponding to that paradigm, at least one indicator data can also be aggregated and / or calculated according to the label paradigm to obtain the label data corresponding to that label paradigm.

[0061] Finally, the tag data in the target tag set is aggregated, and the aggregated tag data is written into a data table to obtain the target tag table.

[0062] Optionally, in the business data processing method provided in Embodiment 1 of this application, collecting indicator data based on tag information to obtain a target indicator table includes: collecting indicator data related to tag information in a source database to obtain an indicator data set; determining the business scenario to which each indicator data belongs in the indicator data set to obtain the business scenario corresponding to each indicator data; aggregating the indicator data in the indicator data set according to the business scenario corresponding to each indicator data, and writing the aggregated indicator data into a data table to obtain the target indicator table.

[0063] In this first embodiment, in order to obtain indicator data from the source database and transform the indicator data into a target label table, indicator data related to the label information can be collected from source databases of different business scenarios, different granularities, different data dimensions, different data sources, and different servers in the financial institution, based on the label information, to obtain an indicator data set. Then, the indicator data in the indicator data set is aggregated according to the business scenario, different granularities, different data dimensions, different data sources, and different servers to which each indicator data belongs, and the aggregated indicator data is written into a data table to obtain the target indicator table.

[0064] In one optional embodiment, asset information of all customers in a financial institution's source database can be collected to obtain an indicator data set. Then, the indicator data in the indicator data set can be aggregated according to the business scenario. For example, the business scenario of processing customer assets can be regarded as business scenario A1. Then, the asset information of all customers in the indicator data set can be written into data table C1, and finally, data table C1 can be used as the target indicator table. Alternatively, the indicator information related to customer number B0001 can be written into data table C2, and the indicator information related to customer number B0002 can be written into data table C3. Finally, data tables C2 and C3 can be used as the target indicator table. Or, the indicator information of different customers can be aggregated again to obtain data table C4, and data table C4 can be used as the target indicator table.

[0065] By collecting indicator data from financial institutions' databases and aggregating the data into target indicator tables according to business scenarios or other rules, it is possible to integrate scattered data from the databases into comprehensive indicator tables. This facilitates the response to data processing instructions through the target indicator tables, thereby improving the efficiency of financial institutions.

[0066] Optionally, in the business data processing method provided in Embodiment 1 of this application, determining the label paradigm corresponding to each indicator data in the target indicator table based on business requirements and label information includes: determining the label subject of each indicator data in the target indicator table based on label information; determining the label attribute of each indicator data based on business requirements and label information; determining the statistical frequency of the label attribute of each indicator data based on business requirements, thereby obtaining the label frequency of the label attribute of each indicator data; and determining the label paradigm corresponding to each indicator data in the target indicator table based on the label subject of each indicator data, the label attribute of each indicator data, and the label frequency of the label attribute of each indicator data.

[0067] In this first embodiment, in order to obtain the data required for data processing instructions based on actual production conditions, a label paradigm can be determined based on business needs, the determined label information, and the indicator data in the target indicator table. Then, the target indicator table is processed according to the label paradigm to obtain the data required for data processing instructions.

[0068] Specifically, the label subject of each indicator data in the target indicator table can be determined based on the label subject under different business scenarios. Then, the label attribute of the label subject of each indicator data can be determined based on the label information corresponding to the label subject. It should be noted that the label attribute corresponding to the label subject of each indicator data can also be determined based on business needs, expert rules, or the business logic itself. For example, the label attribute of the label subject customer account includes daily asset income, but since it is necessary to calculate the customer's monthly average daily assets in the business scenario of processing customer asset information, the monthly average daily assets attribute label can be added to the label subject customer account. Second, the statistical frequency of each label attribute can be determined based on business needs, expert rules, or the business logic itself, thus obtaining the label frequency of each label attribute. For example, the statistical frequency of the label attribute daily assets of the label subject customer account is daily, and the statistical frequency of the label attribute monthly average daily assets of the label subject customer account is monthly. Finally, the label paradigm corresponding to each indicator data can be determined based on the label subject of each indicator data, the label attribute of each indicator data, and the label frequency of the label attribute of each indicator data.

[0069] In addition, the tag information can be adjusted according to new business scenarios or business needs, that is, the tag subject, tag attributes and tag frequency can be flexibly adjusted.

[0070] Determining the label paradigm corresponding to each indicator data by using label information and business requirements is beneficial for processing the indicator data in the target indicator table according to the label paradigm, thereby obtaining the data requested by the data processing instructions, avoiding repetitive calculation work, and improving the work efficiency of data processing instructions.

[0071] Optionally, in the business data processing method provided in Embodiment 1 of this application, aggregating the tag data in the target tag set and writing the aggregated tag data into a data table to obtain a target tag table includes: aggregating the target tags in the target tag set according to the tag paradigm of each target tag in the target tag set, and writing the aggregated tag data into a data table to obtain a first tag table; determining the association relationship between the tag subjects of each target tag in the first tag table; aggregating the tag data in the first tag table according to the association relationship between the paradigm subjects of each target tag, and writing the aggregated tag information into a data table to obtain a target tag table.

[0072] In this first embodiment, in order to facilitate different business systems in a financial institution to obtain tag data related to that business system, the tag data can be aggregated. That is, the tag data in the target tag set can be aggregated according to certain rules to obtain the target tag table, so that the business systems or applications in the financial institution can use it.

[0073] Specifically, each target tag in the target tag set can be aggregated for the first time based on its tag subject, tag attributes, tag frequency, or the business scenario to which the tag belongs. The aggregated tag data is then written into a data table to obtain the first tag table. For example, personal asset information of customers can be aggregated into data table A1, corporate asset information of customers can be aggregated into data table A2, and credit card information in the credit card business scenario can be aggregated into data table A3. Then, the relationships between each tag subject in the first tag table are determined. Finally, the tag subjects with relationships in the first tag table are aggregated for the second time, and the results of the second aggregation are stored in a data table to obtain the target tag table.

[0074] By aggregating the tag data in the target tag set, tag data that are related in business can be grouped together, achieving the effect of aggregating scattered data. This makes it easier for business systems to retrieve data from the aggregated tag table and improves the processing efficiency of data processing instructions.

[0075] Optionally, in the business data processing method provided in Embodiment 1 of this application, obtaining the data requested by the data processing instruction based on the target tag table to obtain the target data includes: determining the tag information required by the data processing instruction to obtain the target tag body and target tag attributes; determining the logical relationship between the target tag bodies based on the data processing instruction; generating a query statement based on the target tag attributes and logical relationship to obtain the target query statement; and performing a data query in the target tag table based on the target query statement to obtain the target data.

[0076] In this first embodiment, in order to respond to the data processing instruction and obtain the target data, a query statement can be automatically generated according to the data processing instruction, and the target data can be obtained through the query statement.

[0077] Specifically, the target tag subject and target tag attribute in the data processing instruction can be determined. For example, if the data processing instruction requires obtaining the average daily assets of customer A1 in August, then the target tag subject of the tag information required by the data processing instruction can be determined as customer A1's customer account, and the target tag attribute of the tag information required by the data processing instruction can be determined as the average daily assets of the customer account.

[0078] Then, since the data required by the data processing instruction may include multiple tag subjects instead of just a single tag subject, in order to generate a query statement, it is necessary to determine the logical relationship between multiple tag subjects when the data processing instruction requires multiple tag subjects. For example, the data processing instruction may need to obtain the average monthly assets of customer A1 and customer A2 at the same time.

[0079] Secondly, a query statement is generated based on the logical relationship between each target tag attribute and the target tag body. It should be noted that the query statement generated in this first embodiment can be an SQL statement used to query a database, or other query statements can be generated for further querying.

[0080] Finally, the generated query statement is used to query the target label table to obtain the target data required by the data processing instructions.

[0081] By determining the tag body of the data required by the data processing instruction, the logical relationship between the tag bodies, and the tag attributes of the tag bodies, query statements can be automatically generated. This avoids the problem of low processing efficiency of data processing instructions caused by manual editing of query statements, thereby improving the processing efficiency of data processing instructions and achieving the effect of improving the work efficiency of financial institutions.

[0082] Optionally, in the business data processing method provided in Embodiment 1 of this application, after receiving the data processing instruction sent by the target business system, the method further includes: establishing a connection between the target tag table and the target business system to obtain a target connection; and sending the updated target tag table to the target business system through the target connection.

[0083] In this first embodiment, in order for business systems or applications in financial institutions to conveniently and quickly obtain tag data from the target tag table, the business systems or applications can subscribe to the required target tag table in the data platform of the financial institution. The data platform is configured with a data interface to transmit data to the business systems or applications, and the tag data is transmitted to the business systems or applications through the data interface (that is, the above-mentioned connection is established between the target tag table and the target business system to obtain the target connection).

[0084] Furthermore, the tag information subscribed to by the business system can be flexibly adjusted when business scenarios or business needs change.

[0085] By subscribing to target tag tables through business systems or applications, it is beneficial to respond to data processing instructions in a timely manner through the subscribed tag data. This achieves the effect of obtaining the data required by the data processing instructions, avoids the problem of repeated calculations by different business systems in order to respond to data processing instructions, which leads to the waste of computing resources, improves the response speed of data processing instructions, and at the same time, it is beneficial for business systems to conveniently and timely obtain the tag data they need, thereby improving the work efficiency of business systems.

[0086] Optionally, in this first embodiment, Figure 3 This is a schematic diagram of an optional business data processing method provided in Embodiment 1 of this application. Figure 2 .

[0087] like Figure 3 As shown, firstly, different business scenarios in financial institutions (such as...) Figure 3 The analysis is performed on business scenarios 1, 2, and N, and / or business requirements, to obtain tag information. Then, based on the tag information, key information or frequently accessed data from the financial institution's business data is extracted to obtain tag sets corresponding to different business scenarios (e.g., ...). Figure 3 (The tag set 1, tag set 2, and tag set N in the text).

[0088] Then, aggregation operations can be performed on at least one tag set according to rules such as business scenarios and data dimensions to obtain an aggregated tag set. The aggregated tag set is as follows: Figure 3 The system includes corporate tag sets, personal tag sets, and credit card tag sets. The corporate tag set includes corporate tag sets based on customer ID and corporate tag sets based on customer account. The personal tag set includes personal tag sets based on customer ID and personal tag sets based on customer account. The credit card tag set includes credit card tag sets based on credit card number.

[0089] Finally, the external business systems within the financial institution subscribe to the aggregated tag set in order to respond to data request instructions based on the aggregated tag set and push the tag set related to the data request instruction to the external business systems. The subscription relationship is as follows: Figure 3 The risk management platform subscribes to a corporate tag set with customer ID as the main tag, the customer operation platform subscribes to a personal tag set with customer ID as the main tag, the information center subscribes to a personal tag set with customer account as the main tag, and other business systems subscribe to a credit card tag set.

[0090] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0091] Example 2

[0092] This application also provides a business data processing apparatus in Embodiment 2. It should be noted that the business data processing apparatus in Embodiment 2 can be used to execute the business data processing method provided in Embodiment 1 of this application. The business data processing apparatus provided in Embodiment 2 is described below.

[0093] Figure 4 This is a schematic diagram of a business data processing apparatus according to Embodiment 2 of this application. Figure 4 As shown, the device includes: a first determining unit 401, a processing unit 402, a second determining unit 403, and an acquisition unit 404.

[0094] Specifically, the first determining unit 401 is used to determine the tag information of the business data in the financial institution based on the business scenario and the business needs in the business scenario, wherein the tag information is used to describe the theme and attributes of the business data.

[0095] The processing unit 402 is used to process business data based on tag information and write the processed tag information into a data table to obtain a target tag table.

[0096] The second determining unit 403 is used to determine the business system related to the target label table based on business needs, and thus obtain the target business system.

[0097] The acquisition unit 404 is used to, upon receiving a data processing instruction sent by the target business system, acquire the data requested by the data processing instruction based on the target tag table, obtain the target data, and respond to the data processing instruction based on the target data.

[0098] The business data processing apparatus provided in Embodiment 2 of this application determines the tag information of business data in a financial institution based on the business scenario and business requirements in the financial institution by a first determining unit 401. The tag information is used to describe the theme and attributes of the business data. The processing unit 402 processes the business data based on the tag information and writes the processed tag information into a data table to obtain a target tag table. The second determining unit 403 determines the business system related to the target tag table based on the business requirements to obtain a target business system. When the acquisition unit 404 receives a data processing instruction sent by the target business system, it acquires the data requested by the data processing instruction based on the target tag table to obtain the target data, and responds to the data processing instruction based on the target data. This solves the problem in related technologies where, when responding to data processing instructions from different business systems, the high degree of repetition among a large number of data processing instructions requires a large amount of cluster resources to process the highly repetitive data processing instructions, resulting in low data processing efficiency. By determining tag information based on business scenarios and needs, and processing business data in financial institutions based on this tag information, a target tag table is obtained. This aggregates fragmented business data, allowing direct queries on the target tag table upon receiving data processing instructions. This improves the response efficiency of data processing instructions and avoids the problem of low response efficiency caused by expending significant computing resources to process highly repetitive data processing instructions. It also enhances the reusability of tag data in the target tag table, achieving the effect of effectively and flexibly using tag data, and further improving the work efficiency of financial institutions.

[0099] Optionally, in the business data processing apparatus provided in Embodiment 2 of this application, the first determining unit 401 mentioned above includes: a first determining subunit, used to determine key fields of business data based on business scenarios to obtain tag subjects, wherein key fields refer to fields in business data that are related to business scenarios; a second determining subunit, used to determine the attributes of tag subjects in business data based on business requirements to obtain tag attributes; and a third determining subunit, used to determine tag information based on tag subjects and tag attributes.

[0100] Optionally, in the business data processing apparatus provided in Embodiment 2 of this application, the aforementioned processing unit 402 includes: a collection subunit, used to collect indicator data from the source database of a financial institution based on tag information to obtain a target indicator table; a fourth determination subunit, used to determine the tag paradigm corresponding to each indicator data in the target indicator table based on business needs and tag information, wherein the tag paradigm is used to indicate the data content required for the target tag table to be generated; a processing subunit, used to process the indicator data in the target indicator table according to the tag paradigm to obtain a target tag set corresponding to the target indicator table; and an aggregation subunit, used to aggregate the tag data in the target tag set and write the aggregated tag data into a data table to obtain the target tag table.

[0101] Optionally, in the business data processing apparatus provided in Embodiment 2 of this application, the above-mentioned acquisition subunit includes: an acquisition module, used to acquire indicator data related to tag information in the source database to obtain an indicator data set; a first determination module, used to determine the business scenario to which each indicator data belongs in the indicator data set to obtain the business scenario corresponding to each indicator data; and a first aggregation module, used to aggregate the indicator data in the indicator data set according to the business scenario corresponding to each indicator data, and write the aggregated indicator data into a data table to obtain a target indicator table.

[0102] Optionally, in the business data processing apparatus provided in Embodiment 2 of this application, the aforementioned fourth determining subunit includes: a second determining module, used to determine the label body of each indicator data in the target indicator table based on the label information; a third determining module, used to determine the label attribute of each indicator data based on business requirements and label information; a fourth determining module, used to determine the statistical frequency of the label attribute of each indicator data based on business requirements, thereby obtaining the label frequency of the label attribute of each indicator data; and a fifth determining module, used to determine the label paradigm corresponding to each indicator data in the target indicator table based on the label body of each indicator data, the label attribute of each indicator data, and the label frequency of the label attribute of each indicator data.

[0103] Optionally, in the business data processing apparatus provided in Embodiment 2 of this application, the above-mentioned aggregation subunit includes: a second aggregation module, used to aggregate the target tags in the target tag set according to the tag paradigm of each target tag in the target tag set, and write the aggregated tag data into a data table to obtain a first tag table; a sixth determining module, used to determine the association relationship between the tag subjects of each target tag in the first tag table; and a third aggregation module, used to aggregate the tag data in the first tag table according to the association relationship between the paradigm subjects of each target tag, and write the aggregated tag information into a data table to obtain a target tag table.

[0104] Optionally, in the business data processing apparatus provided in Embodiment 2 of this application, the aforementioned acquisition unit 404 includes: a fifth determining subunit, used to determine the tag information required by the data processing instruction, and obtain the target tag body and the target tag attribute; a sixth determining subunit, used to determine the logical relationship between the target tag bodies according to the data processing instruction; a generating subunit, used to generate a query statement according to the target tag attribute and the logical relationship, and obtain the target query statement; and a query subunit, used to perform a data query in the target tag table according to the target query statement, and obtain the target data.

[0105] Optionally, in the business data processing apparatus provided in Embodiment 2 of this application, the apparatus further includes: an establishment unit, configured to establish a connection between the target tag table and the target business system after determining the business system related to the target tag table based on business needs and obtaining the target business system; and a sending unit, configured to send the updated target tag table to the target business system through the target connection.

[0106] The business data processing device includes a processor and a memory. The first determining unit 401, processing unit 402, second determining unit 403, and acquisition unit 404 mentioned above are all stored in the memory as program units. The processor executes the program units stored in the memory to realize the corresponding functions.

[0107] A processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and adjusting kernel parameters can improve the response efficiency to data processing requests.

[0108] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0109] Embodiment 3 of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements a method for processing business data.

[0110] Embodiment 4 of the present invention provides a processor for running a program, wherein the program executes a method for processing business data during runtime.

[0111] like Figure 5As shown, Embodiment 5 of the present invention provides an electronic device. The device includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps: determining tag information of business data in the financial institution based on the business scenario and business requirements in the business scenario, wherein the tag information is used to describe the theme and attributes of the business data; processing the business data based on the tag information and writing the processed tag information into a data table to obtain a target tag table; determining the business system related to the target tag table based on the business requirements to obtain a target business system; and, upon receiving a data processing instruction sent by the target business system, obtaining the data requested by the data processing instruction based on the target tag table to obtain target data, and responding to the data processing instruction based on the target data.

[0112] When the processor executes the program, it also performs the following steps: determining the tag information of the business data in the financial institution based on the business scenario and the business requirements in the business scenario, including: determining the key fields of the business data based on the business scenario to obtain the tag body, wherein the key fields refer to the fields in the business data that are related to the business scenario; determining the attributes of the tag body in the business data based on the business requirements to obtain the tag attributes; and determining the tag information based on the tag body and the tag attributes.

[0113] The processor executes the program and also performs the following steps: processing business data based on tag information and writing the processed tag information into a data table to obtain a target tag table, including: collecting indicator data based on tag information in the source database of the financial institution to obtain a target indicator table; determining the tag paradigm corresponding to each indicator data in the target indicator table based on business requirements and tag information, wherein the tag paradigm is used to indicate the data content required for the target tag table to be generated; processing the indicator data in the target indicator table according to the tag paradigm to obtain a target tag set corresponding to the target indicator table; aggregating the tag data in the target tag set and writing the aggregated tag data into a data table to obtain the target tag table.

[0114] When the processor executes the program, it also performs the following steps: collecting indicator data based on tag information to obtain a target indicator table, including: collecting indicator data related to tag information from the source database to obtain an indicator data set; determining the business scenario to which each indicator data belongs in the indicator data set to obtain the business scenario corresponding to each indicator data; aggregating the indicator data in the indicator data set according to the business scenario corresponding to each indicator data, and writing the aggregated indicator data into a data table to obtain the target indicator table.

[0115] When the processor executes the program, it also performs the following steps: determining the label paradigm corresponding to each indicator data in the target indicator table based on business requirements and label information, including: determining the label body of each indicator data in the target indicator table based on label information; determining the label attribute of each indicator data based on business requirements and label information; determining the statistical frequency of the label attribute of each indicator data based on business requirements, and obtaining the label frequency of the label attribute of each indicator data; determining the label paradigm corresponding to each indicator data in the target indicator table based on the label body of each indicator data, the label attribute of each indicator data, and the label frequency of the label attribute of each indicator data.

[0116] When the processor executes the program, it also performs the following steps: aggregating the tag data in the target tag set and writing the aggregated tag data into a data table to obtain the target tag table, including: aggregating the target tags in the target tag set according to the tag paradigm of each target tag in the target tag set, and writing the aggregated tag data into a data table to obtain a first tag table; determining the association relationship between the tag subjects of each target tag in the first tag table; aggregating the tag data in the first tag table according to the association relationship between the paradigm subjects of each target tag, and writing the aggregated tag information into a data table to obtain the target tag table.

[0117] When the processor executes the program, it also performs the following steps: obtaining the data requested by the data processing instruction based on the target label table, and obtaining the target data includes: determining the label information required by the data processing instruction, and obtaining the target label body and target label attributes; determining the logical relationship between the target label bodies based on the data processing instruction; generating a query statement based on the target label attributes and logical relationship, and obtaining the target query statement; and performing a data query in the target label table based on the target query statement to obtain the target data.

[0118] When the processor executes the program, it also performs the following steps: After receiving the data processing instruction sent by the target business system, the above method further includes: establishing a connection between the target tag table and the target business system to obtain a target connection; and sending the updated target tag table to the target business system through the target connection.

[0119] The devices mentioned in this article can be servers, PCs, tablets, mobile phones, etc.

[0120] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program with the following method steps: determining tag information for business data in a financial institution based on the business scenario and business requirements within the business scenario, wherein the tag information is used to describe the subject and attributes of the business data; processing the business data based on the tag information and writing the processed tag information into a data table to obtain a target tag table; determining the business system related to the target tag table based on business requirements to obtain a target business system; and, upon receiving a data processing instruction sent by the target business system, obtaining the data requested by the data processing instruction based on the target tag table to obtain target data, and responding to the data processing instruction based on the target data.

[0121] When executed on a data processing device, it is also suitable to execute an initialization program with the following steps: determining the tag information of the business data in the financial institution based on the business scenario and the business requirements in the business scenario, including: determining the key fields of the business data based on the business scenario to obtain the tag body, wherein the key fields refer to the fields in the business data that are related to the business scenario; determining the attributes of the tag body in the business data based on the business requirements to obtain the tag attributes; and determining the tag information based on the tag body and the tag attributes.

[0122] When executed on a data processing device, it is also suitable to execute an initialization program with the following steps: processing business data based on tag information and writing the processed tag information into a data table to obtain a target tag table, including: collecting indicator data based on tag information in the source database of the financial institution to obtain a target indicator table; determining the tag paradigm corresponding to each indicator data in the target indicator table based on business needs and tag information, wherein the tag paradigm is used to indicate the data content required for the target tag table to be generated; processing the indicator data in the target indicator table according to the tag paradigm to obtain a target tag set corresponding to the target indicator table; aggregating the tag data in the target tag set and writing the aggregated tag data into a data table to obtain the target tag table.

[0123] When executed on a data processing device, it is also suitable to execute an initialization program with the following steps: collecting indicator data based on tag information to obtain a target indicator table, including: collecting indicator data related to tag information from the source database to obtain an indicator data set; determining the business scenario to which each indicator data belongs in the indicator data set to obtain the business scenario corresponding to each indicator data; aggregating the indicator data in the indicator data set according to the business scenario corresponding to each indicator data, and writing the aggregated indicator data into a data table to obtain the target indicator table.

[0124] When executed on a data processing device, it is also suitable to execute an initialization program with the following steps: determining the label paradigm corresponding to each indicator data in the target indicator table based on business requirements and label information, including: determining the label body of each indicator data in the target indicator table based on label information; determining the label attribute of each indicator data based on business requirements and label information; determining the statistical frequency of the label attribute of each indicator data based on business requirements, and obtaining the label frequency of the label attribute of each indicator data; determining the label paradigm corresponding to each indicator data in the target indicator table based on the label body of each indicator data, the label attribute of each indicator data, and the label frequency of the label attribute of each indicator data.

[0125] When executed on a data processing device, it is also suitable to execute an initialization program with the following steps: aggregating tag data in the target tag set and writing the aggregated tag data into a data table to obtain a target tag table, including: aggregating the target tags in the target tag set according to the tag paradigm of each target tag in the target tag set, and writing the aggregated tag data into a data table to obtain a first tag table; determining the association relationship between the tag subjects of each target tag in the first tag table; aggregating the tag data in the first tag table according to the association relationship between the paradigm subjects of each target tag, and writing the aggregated tag information into a data table to obtain a target tag table.

[0126] When executed on a data processing device, it is also suitable to execute an initialization program with the following method steps: obtaining the data requested by the data processing instruction based on the target label table, and obtaining the target data including: determining the label information required by the data processing instruction, obtaining the target label body and target label attributes; determining the logical relationship between the target label bodies based on the data processing instruction; generating a query statement based on the target label attributes and logical relationship, and obtaining the target query statement; and performing a data query in the target label table based on the target query statement to obtain the target data.

[0127] When executed on a data processing device, it is also suitable to execute an initialization program with the following method steps: after receiving a data processing instruction sent by the target business system, the above method further includes: establishing a connection between the target tag table and the target business system to obtain a target connection; and sending the updated target tag table to the target business system through the target connection.

[0128] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0129] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0130] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0131] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0132] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0133] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0134] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0135] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0136] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0137] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for processing business data, characterized in that, include: The labeling information of the business data in the financial institution is determined based on the business scenarios and business needs in the business scenarios, wherein the labeling information is used to describe the theme and attributes of the business data; The business data is processed based on the tag information, and the processed tag information is written into a data table to obtain the target tag table; Based on the aforementioned business requirements, the business systems related to the target tag table are determined, thus obtaining the target business systems; Upon receiving a data processing instruction from the target business system, the system retrieves the data requested by the data processing instruction based on the target tag table, obtains the target data, and responds to the data processing instruction based on the target data. Specifically, the business data is processed based on the tag information, and the processed tag information is written into a data table to obtain the target tag table, which includes: In the source database of the financial institution, indicator data is collected based on the tag information to obtain the target indicator table; Based on the business requirements and the tag information, determine the tag paradigm corresponding to each indicator data in the target indicator table, wherein the tag paradigm is used to indicate the data content required for the target tag table to be generated; The indicator data in the target indicator table is processed according to the label paradigm to obtain the target label set corresponding to the target indicator table; The tag data in the target tag set is aggregated, and the aggregated tag data is written into a data table to obtain the target tag table; Based on the business requirements and the tag information, the tag paradigm corresponding to each indicator data in the target indicator table is determined as follows: The label subject for each indicator data in the target indicator table is determined based on the label information; The tag attributes of each indicator data are determined based on the business requirements and the tag information; Based on the business requirements, determine the statistical frequency of the tag attribute of each indicator data, and obtain the tag frequency of the tag attribute of each indicator data; The label paradigm corresponding to each indicator data in the target indicator table is determined based on the label subject, label attribute, and label frequency of each indicator data.

2. The method according to claim 1, characterized in that, The tagging information for business data in financial institutions, determined based on the business scenarios and business needs within those scenarios, includes: Based on the business scenario, the key fields of the business data are determined to obtain the tag body, wherein the key fields refer to the fields in the business data that are related to the business scenario; Based on the business requirements, determine the attributes of the tag body in the business data to obtain the tag attributes; The tag information is determined based on the tag body and the tag attributes.

3. The method according to claim 1, characterized in that, Based on the collected indicator data using the aforementioned label information, the target indicator table is obtained, including: Collect indicator data related to the tag information from the source database to obtain an indicator data set; Determine the business scenario to which each indicator data belongs in the indicator data set to obtain the business scenario corresponding to each indicator data; The indicator data in the indicator data set are aggregated according to the business scenario corresponding to each indicator data, and the aggregated indicator data is written into a data table to obtain the target indicator table.

4. The method according to claim 1, characterized in that, The target tag table is obtained by aggregating the tag data in the target tag set and writing the aggregated tag data into a data table, including: The target tags in the target tag set are aggregated according to the tag paradigm of each target tag in the target tag set, and the aggregated tag data is written into a data table to obtain the first tag table; Determine the association relationships between the tag bodies of each target tag in the first tag table; The tag data in the first tag table is aggregated based on the association between the paradigm subjects of each target tag, and the aggregated tag information is written into the data table to obtain the target tag table.

5. The method according to claim 1, characterized in that, Based on the target label table, the data requested by the data processing instruction is obtained, and the target data includes: Determine the tag information required by the data processing instructions to obtain the target tag body and target tag attributes; The logical relationship between the target tag entities is determined based on the data processing instructions; A query statement is generated based on the target tag attributes and the logical relationship to obtain the target query statement; The target data is obtained by querying the target label table according to the target query statement.

6. The method according to claim 1, characterized in that, After receiving the data processing instruction sent by the target business system, the method further includes: Establish a connection between the target tag table and the target business system to obtain the target connection; The updated target tag table is sent to the target business system via the target connection.

7. A business data processing apparatus, characterized in that, include: The first determining unit is used to determine the tag information of the business data in the financial institution based on the business scenario in the financial institution and the business needs in the business scenario, wherein the tag information is used to describe the theme and attributes of the business data; The processing unit is used to process the business data based on the tag information and write the processed tag information into a data table to obtain a target tag table; The second determining unit is used to determine the business system related to the target tag table based on the business requirements, and obtain the target business system. The acquisition unit is configured to, upon receiving a data processing instruction sent by the target business system, acquire the data requested by the data processing instruction based on the target tag table, obtain the target data, and respond to the data processing instruction based on the target data; The processing unit includes: a collection subunit, used to collect indicator data from the source database of the financial institution based on the tag information to obtain a target indicator table; a fourth determination subunit, used to determine the tag paradigm corresponding to each indicator data in the target indicator table based on the business requirements and the tag information, wherein the tag paradigm is used to indicate the data content required for the target tag table to be generated; a processing subunit, used to process the indicator data in the target indicator table according to the tag paradigm to obtain a target tag set corresponding to the target indicator table; and an aggregation subunit, used to aggregate the tag data in the target tag set and write the aggregated tag data into a data table to obtain the target tag table. The fourth determining subunit includes: a second determining module, used to determine the label subject of each indicator data in the target indicator table based on the label information; a third determining module, used to determine the label attribute of each indicator data based on the business requirements and the label information; a fourth determining module, used to determine the statistical frequency of the label attribute of each indicator data based on the business requirements, thereby obtaining the label frequency of the label attribute of each indicator data; and a fifth determining module, used to determine the label paradigm corresponding to each indicator data in the target indicator table based on the label subject of each indicator data, the label attribute of each indicator data, and the label frequency of the label attribute of each indicator data.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the business data processing method according to any one of claims 1 to 6.

9. An electronic device, characterized in that, It includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the business data processing method according to any one of claims 1 to 6.

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