Business data processing method and device, equipment, medium and program product

Abstract

The invention provides a business data processing method based on a bridging mode, which can be applied to the technical field of big data. The method comprises the steps of obtaining an enterprise basic information table and a business data wide table based on imported enterprise list data; reading customer group parameter information according to the customer group request data, and configuring a rule model table corresponding to the customer group parameter information; based on the rule model table, performing model processing on the customer group parameter table and the index parameter table to obtain a business data result; wherein the customer group parameter table and the index parameter table are data obtained by performing customer group index association on the enterprise basic information table and the business data wide table through a bridging mode. Therefore, according to the business data processing method disclosed by the invention, the business data result related to the customer group business index can be rapidly extracted. The invention further provides a business data processing device and equipment based on the bridging mode, a medium and a program product.

Description

Technical Field

[0001] The present disclosure relates to the field of big data, and more specifically to a business data processing method, apparatus, device, medium, and program product based on a bridging mode. Background Art

[0002] To effectively provide technology financial services and accelerate the expansion of the blue ocean market for technological innovation, technology companies will be included in the whitelist management. Based on the massive amount of enterprise data in the Hubiao database, it is necessary to implement labeling, intelligent, and digital management for national high-tech enterprises, specialized and innovative enterprises, and technology-based SMEs. Leveraging big data analysis and processing, this will help business personnel improve work efficiency, grasp marketing trends, support operational decision-making, and promote a virtuous cycle of "technology-industry-finance."

[0003] Currently, the database contains a wide variety of enterprise qualifications, enterprise tags cannot be dynamically expanded, and there are many existing marketing activity indicators and scattered assessment and reporting data, making data retrieval complicated. Conventional manual ledger-style data processing is inefficient, making it impossible to quickly extract effective business report data from large amounts of enterprise data to meet business needs such as marketing activity monitoring and operational decision-making. Summary of the Invention

[0004] In view of at least one aspect of the above problems, embodiments of the present disclosure provide a method, apparatus, device, medium, and program product for processing business data based on a bridging mode to improve the efficiency of business data extraction.

[0005] According to a first aspect of the present disclosure, a business data processing method based on a bridging mode is provided, comprising: obtaining an enterprise basic information table and a business data wide table based on imported enterprise list data; reading customer group parameter information according to customer group request data, and configuring a rule model table corresponding to the customer group parameter information; performing model processing on the customer group parameter table and the indicator parameter table based on the rule model table to obtain business data results; wherein the customer group parameter table and the indicator parameter table are data obtained by associating customer group indicators between the enterprise basic information table and the business data wide table through a bridging mode.

[0006] According to an embodiment of the present disclosure, the bridging mode includes: introducing an indicator interface class into a customer group common class to associate indicator parameters and customer group parameters; wherein each indicator class implements the method of the indicator interface class; and each customer group class inherits the method of the customer group common class.

[0007] According to an embodiment of the present disclosure, obtaining the enterprise basic information table and the business data wide table based on the imported enterprise list data includes: filling the imported enterprise list data according to the enterprise information in the multidimensional data source to obtain the enterprise basic information table; and loading the business data of the remote table based on the enterprise basic information table to generate the business data wide table; wherein the remote table is a data table in a non-local database.

[0008] According to an embodiment of the present disclosure, the business data of the remote table is loaded based on the enterprise basic information table to generate the business data wide table, including: analyzing the data status of the remote table based on the data date; if the data status is static, loading the business data in the remote table to the local table, and based on the preset association logic, associating and aggregating the local table and the enterprise basic information table to generate the business data wide table.

[0009] According to an embodiment of the present disclosure, configuring the rule model table corresponding to the customer group parameter information includes: configuring the operation rules corresponding to the customer group parameter information based on a label tree structure; and converting the operation rules into a first database statement to construct the rule model table.

[0010] According to an embodiment of the present disclosure, the label tree structure includes ordinary nodes and label nodes; the operation rules corresponding to the customer group parameter information are configured based on the label tree structure, including: based on the query conditions, combining and nesting multiple ordinary nodes in the customer group parameters; based on the field information, independently assembling a single label node in the customer group parameters; according to the nested ordinary nodes and the assembled label nodes, using a preset connection method, configuring the operation rules corresponding to the customer group parameter information.

[0011] According to an embodiment of the present disclosure, the customer group parameter table and the indicator parameter table are model processed based on the rule model table to obtain business data results, including: splicing the customer group parameter table and the indicator parameter table according to the rule model table to obtain a second database statement; executing the second database statement based on the corresponding computing power models in the customer group parameter table and the indicator parameter table to obtain the business data results.

[0012] According to an embodiment of the present disclosure, the method further includes: screening the indicator data and module data corresponding to the aging date based on the customer group parameter table; and splicing the module data and the indicator data in module order to obtain customer group business data.

[0013] A second aspect of the present disclosure provides a business data processing device based on a bridging mode, comprising: a data conversion module for obtaining an enterprise basic information table and a business data wide table based on imported enterprise list data; a rule interpretation module for reading customer group parameter information according to customer group request data, and configuring a rule model table corresponding to the customer group parameter information; and a computing power scheduling module for performing model processing on the customer group parameter table and the indicator parameter table based on the rule model table to obtain business data results; wherein the customer group parameter table and the indicator parameter table are data obtained by associating customer group indicators between the enterprise basic information table and the business data wide table through the bridging mode.

[0014] According to an embodiment of the present disclosure, the computing power scheduling module includes: a bridging unit for introducing an indicator interface class into a customer group common class to associate indicator parameters and customer group parameters; wherein each indicator class implements the method of the indicator interface class; and each customer group class inherits the method of the customer group common class.

[0015] According to an embodiment of the present disclosure, the data conversion module includes: a data filling unit, which is used to fill the imported enterprise list data according to the enterprise information in the multidimensional data source to obtain the enterprise basic information table; and a data loading unit, which is used to load the business data of the remote table based on the enterprise basic information table to generate the business data wide table; wherein, the remote table is a data table in a non-local database.

[0016] According to an embodiment of the present disclosure, the data loading unit includes: a data association and aggregation sub-unit, which is used to analyze the data status of the remote table based on the data date; if the data status is a static state, the business data in the remote table is loaded into the local table, and based on the preset association logic, the local table is associated and aggregated with the enterprise basic information table to generate the business data wide table.

[0017] According to an embodiment of the present disclosure, the rule interpretation module includes: a configuration unit for configuring the operation rules corresponding to the customer group parameter information based on a label tree structure; and a construction unit for converting the operation rules into a first database statement to construct a rule model table.

[0018] According to an embodiment of the present disclosure, the label tree structure includes ordinary nodes and label nodes; the configuration unit includes: a combined nesting sub-unit, which is used to combine and nest multiple ordinary nodes in the customer group parameters based on query conditions; an independent assembly sub-unit, which is used to independently assemble a single label node in the customer group parameters based on field information; and a connection sub-unit, which is used to configure the operation rules corresponding to the customer group parameter information according to the nested ordinary nodes and the assembled label nodes using a preset connection method.

[0019] According to an embodiment of the present disclosure, the computing power scheduling module includes: a splicing unit for splicing the customer group parameter table and the indicator parameter table according to the rule model table to obtain a second database statement; a model operation unit for executing the second database statement based on the corresponding computing power models in the customer group parameter table and the indicator parameter table to obtain the business data result.

[0020] According to an embodiment of the present disclosure, the device further includes: a customer data processing module, which filters the indicator data and module data corresponding to the expiration date based on the customer parameter table; and splices the module data and the indicator data in module order to obtain customer business data.

[0021] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above method.

[0022] The fourth aspect of the present disclosure further provides a computer-readable storage medium having a computer program or instructions stored thereon, which implements the steps of the above method when the computer program or instructions are executed by a processor.

[0023] The fifth aspect of the present disclosure further provides a computer program product, comprising a computer program or instructions, which implement the steps of the above method when executed by a processor.

[0024] In an embodiment of the present disclosure, due to the low efficiency of existing business report data extraction, the present disclosure is implemented to obtain an enterprise basic information table and a wide business data table based on imported enterprise list data; read customer group parameter information based on customer group request data, and configure a rule model table corresponding to the customer group parameter information; based on the rule model table, model processing is performed on the customer group parameter table and the indicator parameter table to obtain business data results; wherein the customer group parameter table and the indicator parameter table are obtained by associating customer group indicators between the enterprise basic information table and the wide business data table using a bridge mode. After obtaining the enterprise basic information table and the wide business data table, a rule model table corresponding to the customer group parameter information is configured, while the indicators and customer groups change independently. The indicators and customer groups are associated through a bridge mode in the middle. Based on the enterprise basic information table and the wide business data table, the customer group parameter table and the indicator parameter table are obtained, and model processing is performed based on the constructed rule model table, thereby achieving automated data acquisition and quickly extracting business data results related to customer group business indicators from a complex range of enterprise qualifications and a large number of marketing activity indicators. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above contents and other objects, 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:

[0026] Figure 1 Schematically illustrates an application scenario diagram of a service data processing method, apparatus, device, medium, and program product based on a bridge mode according to an embodiment of the present disclosure;

[0027] Figure 2 The flowchart of the service data processing method based on the bridge mode according to the embodiment of the present disclosure is schematically shown;

[0028] Figure 3 A system structure diagram schematically shows a method for processing service data based on a bridge mode according to an embodiment of the present disclosure;

[0029] Figure 4 Another flowchart of the service data processing method based on the bridge mode according to an embodiment of the present disclosure is schematically shown;

[0030] Figure 5 Schematically shows a flow chart of obtaining a data table of a method for processing business data based on a bridge mode according to an embodiment of the present disclosure;

[0031] Figure 6 Schematically shows a flow chart of configuration rules of a service data processing method based on a bridge mode according to an embodiment of the present disclosure;

[0032] Figure 7 Schematically shows an operation rule information diagram of a business data processing method based on a bridge mode according to an embodiment of the present disclosure;

[0033] Figure 8 The following schematically shows a flow chart of customer group business data acquisition of a business data processing method based on a bridge mode according to an embodiment of the present disclosure;

[0034] Figure 9 A schematic diagram shows a structural block diagram of a service data processing device based on a bridge mode according to an embodiment of the present disclosure; and

[0035] Figure 10 A block diagram of an electronic device suitable for implementing a service data processing method based on a bridge mode according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0036] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the detailed description below, 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 well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0037] 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 presence of the features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0038] All terms used herein (including technical and scientific terms) 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.

[0039] When expressions such as "at least one of A, B, and C, etc." are used, they should generally be interpreted in accordance with the meaning 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.).

[0040] In the technical solutions disclosed herein, the user / enterprise information involved, including but not limited to user / enterprise personal information, user / enterprise image information, user / enterprise device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.), 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 relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users / enterprises to choose to authorize or refuse.

[0041] In the scenario of using user / enterprise information to make automated decisions, the methods, devices, and systems provided by the embodiments of the present disclosure all provide users / enterprises with corresponding operation portals for users / enterprises to choose to agree or reject the automated decision results; if the user / enterprise chooses to reject, it will enter the expert decision-making process. The expression "automated decision-making" here refers to the activity of automatically analyzing and evaluating an individual's behavioral habits, interests and hobbies, or economic, health, credit status, etc. through computer programs and making decisions. The expression "expert decision-making" here refers to the activity of making decisions by people who specialize in a certain field, have specialized experience, knowledge and skills, and have reached a certain level of professionalism.

[0042] The embodiment of the present disclosure provides a business data processing method based on a bridging mode. Based on the imported enterprise list data, the enterprise basic information table and the business data wide table are obtained; according to the customer group request data, the customer group parameter information is read, and the rule model table corresponding to the customer group parameter information is configured; based on the rule model table, the customer group parameter table and the indicator parameter table are model processed to obtain business data results; wherein, the customer group parameter table and the indicator parameter table are data obtained by associating the customer group indicators between the enterprise basic information table and the business data wide table through the bridging mode. After obtaining the enterprise basic information table and the business data wide table, the rule model table corresponding to the customer group parameter information is configured, and the indicators and customer groups change independently. In the middle, the indicators and customer groups are associated through the bridging mode. Based on the enterprise basic information table and the business data wide table, the customer group parameter table and the indicator parameter table are obtained, and the model processing is performed according to the constructed rule model table, thereby realizing automated data acquisition. Among the complex types of enterprise qualifications and the indicators of a large number of marketing activities, the business data results related to the customer group business indicators can be quickly extracted.

[0043] Figure 1 The application scenario diagram of the business data processing method, apparatus, device, medium and program product based on the bridge mode according to the embodiment of the present disclosure is schematically shown.

[0044] like Figure 1 As shown, the application scenario 100 according to this embodiment may include business data processing scenarios such as marketing indicator monitoring, business data retrieval, and customer group marketing indicator extraction. The network 104 is used as a medium for providing 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 or wireless communication links or fiber optic cables.

[0045] A user may use a first terminal device 101, a second terminal device 102, or a third terminal device 103 to interact with a server 105 via a 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, or the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (for example only).

[0046] 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.

[0047] The server 105 may be a server that provides various services, such as a background management server (for example only) that supports 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 received data such as user requests, and feed back processing results (e.g., web pages, information, or data obtained or generated based on user requests) to the terminal devices.

[0048] It should be noted that the business data processing method based on the bridge mode provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the business data processing device based on the bridge mode provided in the embodiment of the present disclosure can generally be set in the server 105. The business data processing method based on the bridge mode 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 business data processing device based on the bridge mode 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.

[0049] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0050] The following will be based on Figure 1 The scene described by Figures 2 to 8 The business data processing method based on the bridge mode of the disclosed embodiment is described in detail.

[0051] Figure 2The flowchart of the service data processing method based on the bridge mode according to the embodiment of the present disclosure is schematically shown.

[0052] Figure 3 The system structure diagram of the service data processing method based on the bridge mode according to an embodiment of the present disclosure is schematically shown.

[0053] like Figure 2 As shown, the business data processing method based on the bridge mode of this embodiment includes operations S210 to S230, and the business data processing method based on the bridge mode can be automatically executed. Figure 3 As shown, the system structure for implementing the business data processing method based on the bridge mode includes a data converter, a rule interpreter and a computing power scheduler.

[0054] In operation S210 , based on the imported enterprise list data, an enterprise basic information table and a business data wide table are obtained.

[0055] Import company list data through a data converter, collect raw data from the imported company list, and collect data from related databases to obtain basic company information tables and wide business data tables. The data converter can implement data processing functions such as managing company tag information, data collection logic, and business report processing. It can also create wide business data tables, add company profile tags, output business reports, and display reports. Company list data can include unified social credit codes and company names.

[0056] In an embodiment of the present disclosure, before importing the enterprise list data, the consent or authorization of the enterprise user may be obtained. For example, before operation S210, a request for obtaining enterprise user information may be issued to the enterprise user. If the enterprise user consents or authorizes the acquisition of the enterprise user information, operation S210 is executed.

[0057] After the company list changes, the original customer list can be directly overwritten through list import to achieve dynamic updating of the company list. After the company list changes, it is necessary to automatically initialize the beginning of the year data (account opening information, loan information, deposit information), recalculate according to the model rules (customer level, institution level statistics), generate model indicator historical data, and display the business performance of the latest list by re-querying the historical point-in-time report.

[0058] In operation S220 , customer group parameter information is read according to the customer group request data, and a rule model table corresponding to the customer group parameter information is configured.

[0059] The rule interpreter is used to obtain customer group request data, read customer group parameter information, and configure the rule model table. The rule interpreter can parse customer group request data, including the table, filter conditions, and matching method selected by the user on the front-end page, and implement rule processing to obtain the rule model table. The rule interpreter can be used to define raw data collection rules, marketing activity rules, and processing operation rules.

[0060] Users can enter the activity name, start date, and end date on the front-end page, select a data customer group tag (specialized, specialized, innovative, high-tech, or high-tech SMEs), and a business model name. The rule interpreter can retrieve the customer group request data entered by the user. Customer group request data includes but is not limited to the activity name, start date, end date, data customer group tag, business model name, and customer group parameter information, including but not limited to customer group code, model name, model description, model code, and indicator code. The customer group code is determined based on the data customer group tag, the model name, model description, and model code are determined based on the business model name, and the indicator code is determined based on the activity name, start date, and end date.

[0061] Configuring the rule model table corresponding to customer group parameter information refers to the configuration process for the imported customer group list. For example, a customer group can be configured with multiple models. For example, for specialized and new customer groups, it is necessary to configure computing power models such as account opening, loan status, loan account status, deposit status, and financing status.

[0062] In operation S230, based on the rule model table, the customer group parameter table and the indicator parameter table are model processed to obtain business data results; wherein, the customer group parameter table and the indicator parameter table are data obtained by associating customer group indicators between the enterprise basic information table and the business data wide table through the bridge mode.

[0063] The computing scheduler performs model processing based on the configured rule model table. In bridge mode, data is processed according to the configured customer group rules. The computing scheduler calculates various customer group indicators based on customer group parameters (data in the customer group parameter table), model rules (computing model in the rule model table), and business data (data in the indicator parameter table). These indicators represent marketing monitoring results, or business data results, which can include marketing monitoring reports. The computing scheduler can load business data and company lists and execute computing models according to the rules.

[0064] It should be noted that indicator parameters represent business indicator data, which can be monthly marketing target values. Marketing target data is regularly imported into the database to track and compare actual business performance indicators, thereby completing marketing business assessment and scoring and business evaluation. Customer group parameters represent enterprise information, which can include customer groups such as specialized, high-tech, and small and medium-sized enterprises. The indicator parameter table represents business data, and the customer group parameter table represents enterprise information. Through the bridge mode, the customer group indicators are linked between the enterprise basic information table and the business data wide table. The corresponding interface classes are used to obtain the corresponding data to obtain the customer group parameter table and indicator parameter table.

[0065] According to an embodiment of the present disclosure, the bridging mode includes: introducing the indicator interface class into the customer group common class to associate indicator parameters and customer group parameters; wherein each indicator class implements the method of the indicator interface class; and each customer group class inherits the method of the customer group common class.

[0066] The indicator parameters and customer group parameters change independently. The bridge mode is to associate the indicator parameters and customer group parameters through bridging. The implementation method is: introduce the indicator interface class into the customer group public class to associate the indicator parameters and customer group parameters. For example, indicator parameters such as deposits, loans, loan accounts, and account openings are independently extended, and customer group parameters such as small giants, small and medium-sized science and technology, and high-tech are dynamically extended. The indicator interface class introduces the customer group public class, and each specific indicator class implements the methods of the indicator interface class (such as initialization, data loading, customer group list update, indicator statistics, etc.). The specific customer group class inherits the customer group public class to meet the compatibility of commonality and individuality, thereby realizing the association between business indicators and customer groups.

[0067] Through the bridge mode, indicator data can also be generated. The specific process is: read the current indicator parameter table, and according to the company's organization number, indicator code and data date in the current indicator parameter table, bridge the corresponding customer group data tag according to the company's organization number. You can determine the customer group code in the customer group parameter table, obtain the target value corresponding to the customer group code, and calculate the indicator data corresponding to the current organization number, such as the indicator completion rate. The formula is as follows:

[0068] Indicator completion rate = (current value - value at the beginning of the year) / target value * 100

[0069] According to the embodiment of the present disclosure, the indicator interface class is introduced into the customer group public class to associate the indicator parameters and the customer group parameters. The beneficial effect is that the indicators and customer groups can change independently in the bridging mode, and are associated through bridging, which satisfies the compatibility of commonality and individuality. The customer group and indicator parameters can be adjusted, and marketing indicator tasks can be dynamically issued, further creating an interactive scientific and technological value dashboard with automated data acquisition, customized analysis, and visual display to empower business decisions.

[0070] For example, Figure 4Another flowchart of the service data processing method based on the bridge mode according to an embodiment of the present disclosure is schematically shown.

[0071] like Figure 4 As shown, the data converter is used to import the company list and collect raw data, and the data converter is used to perform the operation S210 described above, which will not be repeated here. The rule interpreter is used to read customer group parameters and read rules, and the rule interpreter is used to perform the operation S220 described above, which will not be repeated here. The computing power scheduler is used to execute the computing power model and output business reports, and the computing power scheduler is used to perform the operation S230 described above, which will not be repeated here.

[0072] Figure 5 The flowchart of obtaining a data table of the business data processing method based on the bridge mode according to an embodiment of the present disclosure is schematically shown.

[0073] like Figure 5 As shown, according to an embodiment of the present disclosure, in operation S210 , based on the imported enterprise list data, the enterprise basic information table and the business data wide table are obtained, including operations S510 - S520 .

[0074] In operation S510 , the imported enterprise list data is filled in according to the enterprise information in the multidimensional data source to obtain an enterprise basic information table.

[0075] Multidimensional data sources may include public business registration data sources, account opening data sources, and loan data sources.

[0076] Based on the unified social credit code in the enterprise list data, query the industrial and commercial registration data source to supplement enterprise information such as registration place, former name, and enterprise size; based on the account opening data source, supplement enterprise information such as enterprise customer number and account opening institution; based on the loan data source, supplement enterprise information such as the first loan date and loan amount, and store this enterprise information in the enterprise basic information table. For example, part of the enterprise basic information table is shown in Table 1 below:

[0077] Table 1

[0078]

[0079] In operation S520 , based on the enterprise basic information table, business data of a remote table is loaded to generate a business data wide table; wherein the remote table is a data table in a non-local database.

[0080] Remote tables are stored in remote databases (such as data centers, data warehouses, and database clusters). During data processing, data associated with remote tables needs to be loaded and updated into local tables to facilitate multi-table joins and quickly generate wide tables of aggregated business data. Local tables are data tables in the local (system) database.

[0081] According to an embodiment of the present disclosure, the imported enterprise list data is filled in and combined with the business data loaded from the remote table to generate a wide business data table, which can integrate multi-source data, improve data integrity and analysis efficiency, and support complex business scenarios.

[0082] According to an embodiment of the present disclosure, in operation S520 , based on the enterprise basic information table, business data of a remote table is loaded to generate a business data wide table, including operations S5201 - S5202 .

[0083] In operation S5201, the data status of the remote table is analyzed based on the data date.

[0084] The data date of the remote table corresponds to the data date of the local table. The number of records in the remote table for a specified date is counted. If the current number of records is 0, the collection process stops. If the current number of records is not 0, the process sleeps for 20 seconds and then counts the number of records in the remote table for the specified date again. If the number of records before and after the sleep is the same, the remote data is static, that is, the data state of the remote table is static. If the number of records before and after the sleep is different, the remote data is dynamic, that is, the data state of the remote table is not static.

[0085] In operation S5202, if the data state is static, the business data in the remote table is loaded into the local table, and based on the preset association logic, the local table and the enterprise basic information table are associated and aggregated to generate a business data wide table.

[0086] When the data status of the remote table is static, data loading and wide table creation are executed. That is, the business data in the remote table is loaded into the local table, and a wide business data table is created. The generation logic of the wide business data table is based on a pre-set association logic fixed in advance, and business data related to enterprise information is created. For example, the customer basic information table and the account details table are associated and aggregated by the customer number to obtain the customer's business data with account details.

[0087] When the data status of the remote table is not static, the loading operation cannot be performed. The data collection action is exited and the next data loading task is called. The data loading task is to obtain basic business data related to the enterprise. Basic business data includes at least loan note tables, public account tables, account details tables, and other business data. The scheduling plan of the data loading task can be configured through parameters, for example, it can be executed once every hour.

[0088] According to an embodiment of the present disclosure, when the data state of a remote table is static, the business data of the remote table is loaded and related data is associated and aggregated, which can ensure data consistency, improve processing efficiency, and reduce the impact on the business.

[0089] Figure 6 A flow chart of configuration rules of a service data processing method based on a bridge mode according to an embodiment of the present disclosure is schematically shown.

[0090] like Figure 6 As shown, according to an embodiment of the present disclosure, configuring the rule model table corresponding to the customer group parameter information in operation S220 includes operations S610-S620.

[0091] In operation S610 , an operation rule corresponding to the customer group parameter information is configured based on the tag tree structure.

[0092] The tag tree structure includes the node connection function, node type (normal node and tag node), query method, field type, etc. Specifically, the tag tree structure table is shown in Table 2 below.

[0093] Table 2

[0094]

[0095] According to the embodiments of the present disclosure, by configuring the operation rules corresponding to the customer group parameter information based on the tag tree structure, hierarchical rule management and flexible expansion can be achieved, thereby improving configuration efficiency and customer group segmentation accuracy.

[0096] According to an embodiment of the present disclosure, the tag tree structure includes common nodes and tag nodes; in operation S610 , configuring operation rules corresponding to customer group parameter information based on the tag tree structure includes operations S6101 - S6103 .

[0097] In operation S6101 , a plurality of common nodes in the nested customer group parameters are combined based on a query condition.

[0098] For common nodes, the current node and all nodes below it are treated as a whole and nested based on multiple query conditions. Nested combinations can be enclosed in parentheses. For example, the new customer judgment logic is: (max(openflag)=1 andmax(open_date) > 20250101), which means filtering out customers who first or most recently opened an account after January 1, 2025. max(openflag)=1 indicates that the maximum value of the account opening flag (openflag) in the customer's history is 1, meaning the customer has opened an account (usually 1 indicates an account opened, 0 indicates an account not opened). max(open_date) > 20250101 indicates that the customer's most recent account opening date (open_date) is greater than January 1, 2025 (in the format of YYYYMMDD, where Y represents year, M represents month, and D represents day).

[0099] In operation S6102 , a single tag node in the customer group parameter is independently assembled based on the field information.

[0100] For label nodes, field information (such as field name, symbol, field value, etc.) is independently assembled into an expression that conforms to the database language. For example, if the loan account flag ydhflag=1, it means that in the business system, the customer is a user with a loan. Among them, ydhflag represents the field name of the loan account. It is a marker field that identifies whether the customer has a loan and is used to quickly determine whether the customer currently has a loan business. 1 indicates that the field value is 1, indicating that there is a loan. If the corresponding field value is 0, it means that there is no loan.

[0101] In operation S6103, based on the nested common nodes and the assembled label nodes, a calculation rule corresponding to the customer group parameter information is configured using a preset connection method.

[0102] Figure 7 The diagram schematically shows an operation rule information diagram of a business data processing method based on a bridge mode according to an embodiment of the present disclosure, as shown in FIG. Figure 7 As shown, the operation rule information input by the front end includes and (connection function), age (field), negation, etc. According to the operation rule information, the sub-conditions are spliced ​​in the form of connection function + negation + database language (field name + symbol + field value), and the final operation rule is recursively derived based on the label tree structure and written into the rule model table.

[0103] According to the embodiments of the present disclosure, based on the query conditions, multiple common nodes in the customer group parameters are combined and nested, and based on the field information, a single label node in the customer group parameters is independently assembled. By combining and nesting common nodes and independently assembling single label nodes, a complex label system can be flexibly constructed, supporting on-demand expansion and reuse, and improving the flexibility of label combination and the accuracy of customer group analysis.

[0104] In operation S620 , the operation rule is converted into a first database statement to construct a rule model table.

[0105] Through the rule interpreter, rule conditions such as the data source wide table, filtering conditions, and grouping logic are set. Based on the rule conditions, operation rules are configured for specific customer group parameter information. The corresponding operation rules are converted into first database statements. The model data corresponding to the first database statements of the customer group parameter information is counted to form a rule model table, as shown in Table 3 below. The first database statements can be executed and the resulting data is stored in the database to facilitate the subsequent management of the customer group parameter information. The first database statements are statements converted from the operation rules corresponding to the customer group parameter information and can be applied to databases. They can be statements such as Structured Query Language (SQL), non-relational database languages, data definition languages, and data manipulation languages.

[0106] Table 3

[0107]

[0108] According to an embodiment of the present disclosure, in operation S230 , model processing is performed on the customer group parameter table and the indicator parameter table based on the rule model table to obtain the business data results, including operations S2301 - S2302 .

[0109] In operation S2301, the customer group parameter table and the indicator parameter table are concatenated according to the rule model table to obtain a second database statement.

[0110] Read the basic information table and the original business data wide table, and read the customer parameter table and indicator parameter table in bridge mode. For example, the customer parameter table is shown in Table 4 below, and the indicator parameter table is shown in Table 5 below.

[0111] Table 4

[0112]

[0113] Table 5

[0114]

[0115] Based on the enterprise business information read from the enterprise basic information table and the original business data wide table, according to the customer parameter table and indicator parameter table of the enterprise business information, the second database statement (such as SQL statement) is spliced ​​according to the where, from, and group in the model rule table. The second database statement is the statement converted from the model rule table corresponding to the enterprise business information.

[0116] In operation S2302, based on the corresponding computing power models in the customer group parameter table and the indicator parameter table, a second database statement is executed to obtain business data results.

[0117] The computing model configured with customer group parameters includes models for account opening, loans, existing borrowers, and deposits. The computing model operates in the aforementioned bridge mode. Its operation rules implement bridge associations by holding references to customer group data tags. After executing the second database statement, all computing models are processed sequentially, and the business data results can be sent to the appropriate business personnel. These business data results can be marketing monitoring reports, such as institution name, customer group name, number of customers, loan balance, loan balance compared to the beginning of the year, loan balance compared to the previous month, number of scheduled tasks, and completion rate of scheduled tasks.

[0118] According to the embodiments of the present disclosure, the rule model table supports multi-dimensional configuration of operation rules, and the computing power model logic supports graphics, visualization, and personalized settings, giving full play to the advantages of wide table data, realizing customized analysis, and using the powerful computing power of computers to customize models and reports in a configured manner, thereby meeting the business indicator monitoring needs of marketing activities.

[0119] Figure 8 The flowchart of customer group business data acquisition of the business data processing method based on the bridge mode according to an embodiment of the present disclosure is schematically shown.

[0120] like Figure 8 As shown, according to an embodiment of the present disclosure, after the customer group parameter table is acquired in operation S230, the business data processing method further includes operations S810-S820.

[0121] In operation S810 , based on the customer group parameter table, index data and module data corresponding to the aging date are filtered.

[0122] The data converter reads the customer group parameter table based on the organization, customer group, and date in the indicator parameter table, filtering the latest module data and indicator data for the specified date. Module data is the actual business data of the business operation module. The expiration date indicates the validity period of the module data.

[0123] For example, due to the different timeliness of data in modules like account opening, loans, and deposits, the timeliness of account opening is T-1, and the timeliness of deposits is T-2, where T represents the date. For example, when a business queries a report dated 2025-04-25, the account opening data for 2025-04-24 and the deposit data for 2025-04-23 are dynamically concatenated to output the customer business data.

[0124] For the acquisition of module data, the corresponding record data in the database can be searched according to the selected customer group and the validity date of the data.

[0125] To obtain indicator data, the data converter can find the corresponding module indicator results based on the selected customer group and the validity date of the data according to the customer group parameter table and the customer group's associated model. Through a lightweight data exchange format, the data is stored and transmitted in plain text. The module number, module name, indicator number, indicator variable, indicator name, indicator value and other data are parsed to obtain the column name and column value to obtain the model indicator parameter table, as shown in Table 6 below.

[0126] Table 6

[0127]

[0128] According to the model code, column number, and column name, obtain the column name method corresponding to the report. According to the column number in the column name method, splice out the array variable name, and obtain the indicator data of the report through the array variable. For example, the indicator data results are shown in Table 7 below, where field1~field5 and data_dt represent the array variable names.

[0129] Table 7

[0130]

[0131] In operation S820, the module data and the indicator data are spliced ​​in module order to obtain customer group business data.

[0132] Dynamic splicing is performed according to the preset module order to obtain customer business data, which can be presented as business reports. The module order indicates the order corresponding to the module data. For example, the displayed data is displayed in the order of account opening, deposits, and loans.

[0133] According to the embodiments of the present disclosure, the indicator data and module data corresponding to the timeliness date are screened, the module data and indicator data are spliced ​​together, and the customer business data is obtained. This is to accurately integrate multi-dimensional data, improve data timeliness and relevance, clearly present the customer business status, and provide efficient and comprehensive data support for business analysis and decision-making.

[0134] According to the embodiments of the present disclosure, indicators and customer groups change independently, and are associated with each other through a bridging mode. Based on the enterprise basic information table and the business data wide table, the customer group parameter table and the indicator parameter table are obtained, and model processing is performed according to the constructed rule model table, thereby realizing automatic data acquisition and quickly extracting business data results from the complex types of enterprise qualifications and the indicators of a large number of marketing activities.

[0135] Based on the above-mentioned business data processing method based on the bridge mode, the present disclosure also provides a business data processing device based on the bridge mode. Figure 9 The device is described in detail.

[0136] Figure 9 The structural block diagram of the service data processing device based on the bridge mode according to an embodiment of the present disclosure is schematically shown.

[0137] like Figure 9 As shown, the business data processing device 900 based on the bridge mode of this embodiment includes a data conversion module 910, a rule interpretation module 920 and a computing power scheduling module 930.

[0138] The data conversion module 910 is used to obtain the enterprise basic information table and the business data wide table based on the imported enterprise list data. In one embodiment, the data conversion module 910 can be used to perform the operation S210 described above, which will not be repeated here.

[0139] The rule interpretation module 920 is used to read the customer group parameter information according to the customer group request data and configure the rule model table corresponding to the customer group parameter information. In one embodiment, the rule interpretation module 920 can be used to perform the operation S220 described above, which will not be repeated here.

[0140] Computing power scheduling module 930 is used to perform model processing on the customer group parameter table and the indicator parameter table based on the rule model table to obtain business data results. The customer group parameter table and the indicator parameter table are obtained by associating customer group indicators between the enterprise basic information table and the business data wide table in bridge mode. In one embodiment, computing power scheduling module 930 can be used to perform operation S230 described above, which will not be repeated here.

[0141] According to an embodiment of the present disclosure, the computing power scheduling module 930 includes: a bridging unit for introducing the indicator interface class into the customer group common class to associate indicator parameters and customer group parameters; wherein each indicator class implements the method of the indicator interface class; and each customer group class inherits the method of the customer group common class.

[0142] According to an embodiment of the present disclosure, the data conversion module 910 includes: a data filling unit, which is used to fill in the imported enterprise list data according to the enterprise information in the multidimensional data source to obtain the enterprise basic information table; and a data loading unit, which is used to load the business data of the remote table based on the enterprise basic information table to generate a business data wide table; wherein the remote table is a data table in a non-local database.

[0143] According to an embodiment of the present disclosure, the data loading unit includes: a data association and aggregation sub-unit, which is used to analyze the data status of the remote table based on the data date; if the data status is static, the business data in the remote table is loaded into the local table, and based on the preset association logic, the local table is associated and aggregated with the enterprise basic information table to generate a wide table of business data.

[0144] According to an embodiment of the present disclosure, the rule interpretation module 920 includes: a configuration unit for configuring operation rules corresponding to customer group parameter information based on a label tree structure; and a construction unit for converting the operation rules into a first database statement to construct a rule model table.

[0145] According to an embodiment of the present disclosure, the label tree structure includes ordinary nodes and label nodes; the configuration unit includes: a combined nested sub-unit, which is used to combine and nest multiple ordinary nodes in the customer group parameters based on query conditions; an independent assembly sub-unit, which is used to independently assemble a single label node in the customer group parameters based on field information; and a connection sub-unit, which is used to configure the operation rules corresponding to the customer group parameter information according to the nested ordinary nodes and the assembled label nodes using a preset connection method.

[0146] According to an embodiment of the present disclosure, the computing power scheduling module 930 includes: a splicing unit for splicing the customer group parameter table and the indicator parameter table according to the rule model table to obtain a second database statement; a model operation unit for executing the second database statement based on the corresponding computing power model in the customer group parameter table and the indicator parameter table to obtain business data results.

[0147] According to an embodiment of the present disclosure, the device also includes: a customer group data processing module, which filters the indicator data and module data corresponding to the expiration date based on the customer group parameter table; and splices the module data and indicator data in module order to obtain customer group business data.

[0148] According to embodiments of the present disclosure, any multiple modules among the data conversion module 910, the rule interpretation module 920, and the computing power scheduling module 930 can be combined into a single module, or any one of these modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in a single module. According to embodiments of the present disclosure, at least one of the data conversion module 910, the rule interpretation module 920, and the computing power scheduling module 930 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 in hardware or firmware through any other reasonable means of circuit integration or packaging, or can be implemented in any one of the three implementation methods of software, hardware, and firmware, or any appropriate combination of any of these. Alternatively, at least one of the data conversion module 910, the rule interpretation module 920, and the computing power scheduling module 930 can be at least partially implemented as a computer program module that, when executed, can perform the corresponding functionality.

[0149] Figure 10 A block diagram of an electronic device suitable for implementing a service data processing method based on a bridge mode according to an embodiment of the present disclosure is schematically shown.

[0150] like Figure 10As shown, the electronic device 1200 according to an embodiment of the present disclosure includes a processor 1201, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM 1202) or a program loaded from a storage unit 1208 into a random access memory (RAM 1203). The processor 1201 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 1201 may also include onboard memory for caching purposes. The processor 1201 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.

[0151] Various programs and data required for the operation of the electronic device 1200 are stored in the RAM 1203. The processor 1201, the ROM 1202, and the RAM 1203 are connected to each other via a bus 1204. The processor 1201 performs various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 1202 and / or the RAM 1203. It should be noted that the programs may also be stored in one or more memories other than the ROM 1202 and the RAM 1203. The processor 1201 may also perform various operations of the method flow according to the embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0152] According to an embodiment of the present disclosure, electronic device 1200 may further include an input / output (I / O) interface 1205, which is also connected to bus 1204. Electronic device 1200 may also include one or more of the following components connected to I / O interface 1205: an input section 1206 including a keyboard, mouse, etc.; an output section 1207 including devices such as a cathode ray tube (CRT), liquid crystal display (LCD), and speakers; a storage section 1208 including a hard disk; and a communication section 1209 including a network interface card such as a LAN card or modem. Communication section 1209 performs communication processing via a network such as the Internet. A drive 1210 is also connected to I / O interface 1205 as needed. Removable media 1211, such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed in drive 1210 as needed, so that computer programs read from the removable media can be installed into storage section 1208 as needed.

[0153] 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 and not be incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when executed, implements the method according to the embodiments of the present disclosure.

[0154] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, and may include, for example, but not limited to: a portable computer disk, a hard disk, a random access memory, a read-only memory, 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 that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 1202 and / or RAM 1203 described above, and / or one or more memories other than ROM 1202 and RAM 1203.

[0155] The embodiments of the present disclosure also include a computer program product, which includes a computer program containing program code for executing the method shown in the flowchart. When the computer program product is executed in a computer system, the program code is used to enable the computer system to implement the business data processing method based on the bridge mode provided by the embodiments of the present disclosure.

[0156] The computer program executes the above functions defined in the system / device of the embodiment of the present disclosure when the processor 1201 executes the computer program. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0157] In one embodiment, the computer program may be stored on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may be transmitted and distributed in the form of a signal on a network medium, downloaded and installed via the communication portion 1209, and / or installed from the removable medium 1211. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0158] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 1209 and / or installed from the removable medium 1211. When the computer program is executed by the processor 1201, the above-described functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the systems, devices, means, modules, units, etc. described above can be implemented by computer program modules.

[0159] 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 computer programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving 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 via the Internet).

[0160] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that 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 flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0161] Those skilled in the art will appreciate that the features described in the various embodiments of the present disclosure may be combined and / or coupled in various ways, even if such combinations or couplings are not explicitly described in the present disclosure. In particular, the features described in the various embodiments of the present disclosure may be combined and / or coupled in various ways without departing from the spirit and teachings of the present disclosure. All such combinations and / or couplings fall within the scope of the present disclosure.

[0162] The above describes the embodiments of the present disclosure. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be advantageously used in combination. Without departing from the scope of the present disclosure, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A business data processing method based on a bridge mode, characterized in that: The method comprises: Based on the imported enterprise list data, obtain the enterprise basic information table and business data wide table; Read customer group parameter information according to customer group request data, and configure the rule model table corresponding to the customer group parameter information; Based on the rule model table, the customer group parameter table and the indicator parameter table are model processed to obtain business data results; wherein, the customer group parameter table and the indicator parameter table are data obtained by associating customer group indicators between the enterprise basic information table and the business data wide table through a bridging mode.

2. The method according to claim 1, characterized in that The bridge mode includes: Introduce the indicator interface class into the customer group public class to associate the indicator parameters with the customer group parameters; Each indicator class implements the method of the indicator interface class; each customer group class inherits the method of the customer group common class.

3. The method according to claim 1, characterized in that The method of obtaining the enterprise basic information table and business data wide table based on the imported enterprise list data includes: Filling the imported enterprise list data according to the enterprise information in the multidimensional data source to obtain the enterprise basic information table; and Based on the enterprise basic information table, business data of a remote table is loaded to generate the business data wide table; wherein the remote table is a data table in a non-local database.

4. The method according to claim 3, characterized in that The step of loading the business data of the remote table based on the enterprise basic information table to generate the business data wide table includes: Analyzing the data status of the remote table based on the data date; If the data state is static, the business data in the remote table is loaded into the local table, and based on the preset association logic, the local table and the enterprise basic information table are associated and aggregated to generate the business data wide table.

5. The method according to claim 1, wherein The rule model table corresponding to the configuration of the customer group parameter information includes: Based on the label tree structure, configuring the operation rules corresponding to the customer group parameter information; and The operation rule is converted into a first database statement to construct the rule model table.

6. The method according to claim 5, characterized in that The label tree structure includes common nodes and label nodes; The configuration of the operation rules corresponding to the customer group parameter information based on the tag tree structure includes: Based on the query conditions, multiple common nodes in the nested customer group parameters are combined; Based on the field information, a single label node in the customer group parameter is independently assembled; According to the nested common nodes and the assembled label nodes, the operation rules corresponding to the customer group parameter information are configured using a preset connection method.

7. The method according to claim 1, characterized in that The customer group parameter table and the indicator parameter table are subjected to model processing based on the rule model table to obtain business data results, including: According to the rule model table, the customer group parameter table and the indicator parameter table are concatenated to obtain a second database statement; Based on the corresponding computing power models in the customer group parameter table and the indicator parameter table, the second database statement is executed to obtain the business data result.

8. The method according to claim 1, characterized in that The method further comprises: Based on the customer group parameter table, screening indicator data and module data corresponding to the aging date; and The module data and the indicator data are spliced ​​together in module order to obtain customer business data.

9. A service data processing device based on a bridge mode, characterized in that: The device comprises: The data conversion module is used to obtain the enterprise basic information table and business data wide table based on the imported enterprise list data; A rule interpretation module, configured to read customer group parameter information according to customer group request data and configure a rule model table corresponding to the customer group parameter information; and The computing power scheduling module is used to perform model processing on the customer group parameter table and the indicator parameter table based on the rule model table to obtain business data results; wherein, the customer group parameter table and the indicator parameter table are data obtained by associating customer group indicators between the enterprise basic information table and the business data wide table in a bridging mode.

10. An electronic device comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

12. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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