Data mart-based supervisory data processing method, device, equipment, and medium

Abstract

The embodiment of the present application relates to the field of big data processing technology, and provides a method, device, equipment and medium for processing regulatory data based on data marts, which generates data detail tables of different dimensions at the data detail layer, then maps the fields in the ODS table with the fields in the data detail table, and writes the data in the ODS table into the corresponding detail table; generates a dimension table according to the pre-defined regulatory data dimension at the data dimension layer; extracts corresponding data from each data detail table according to the dimension in the dimension table, and integrates them to obtain regulatory data; stores the regulatory data in the regulatory data table located at the data service layer, and connects the data service layer to the regulatory system to report the regulatory data table to the regulatory system. By integrating the data in the detail table to obtain regulatory data, the unification of data reported to the regulatory system is achieved, the time cost of extracting and processing data from the business system library is reduced, and the efficiency of reporting to the regulatory system is improved.

Description

Technical Field

[0001] The present application relates to the field of big data processing, and in particular to a method, apparatus, device and medium for processing regulatory data based on a data mart. Background Art

[0002] With the increasing demand for automated financial data regulation, institutions are increasingly adopting data mart technology to submit vast amounts of financial data to regulatory systems. However, due to differences in data storage methods between institutions and the formats used for reporting to regulatory systems, data processing before submission to the regulatory system is time-consuming, resulting in relatively low data reporting efficiency. During the data collection process, business data may need to be repeatedly extracted for related regulatory data entries, resulting in high resource consumption for data marts. Summary of the Invention

[0003] The main purpose of the embodiments of the present application is to propose a regulatory data processing method and apparatus, equipment and medium based on a data mart, aiming to improve the efficiency of the reporting regulatory system and reduce the resource overhead of reporting.

[0004] To achieve the above objectives, a first aspect of an embodiment of the present application provides a supervisory data processing method based on a data mart, wherein the data mart includes a data detail layer, a data dimension layer, and a data service layer. The method includes the following steps:

[0005] Generate multiple detail tables according to predefined domain dimensions and time dimensions, and store the multiple detail tables in a first database corresponding to the data detail layer;

[0006] Determine the mapping relationship between each field in each of the detailed tables and the operation data storage ODS table;

[0007] Read the ODS table at a preset time interval, and write the business data of the ODS table into the corresponding detail table according to the mapping relationship;

[0008] Generate a dimension table according to predefined regulatory data dimensions, and store the dimension table in a second database corresponding to the data dimension layer;

[0009] Extracting corresponding business data from each of the detail tables according to the supervision data dimension in the dimension table;

[0010] Obtaining regulatory data based on business data integration corresponding to the regulatory data dimension;

[0011] Writing the supervision data into a supervision data table, and storing the supervision data table in a third database corresponding to the data service layer;

[0012] The third database is connected to a supervision system to report the supervision data table to the supervision system.

[0013] In some possible embodiments, the ODS table includes multiple fields. Before determining the mapping relationship between each field in each of the detailed tables and the operation data storage ODS table, the method further includes:

[0014] Extracting a plurality of business data from a business system library;

[0015] Determining, based on a source interface for collecting the business data, fields corresponding to the business data;

[0016] Determine the ODS table corresponding to the business data according to the fields corresponding to the business data;

[0017] The business data is written into the corresponding ODS table.

[0018] In some possible embodiments, determining the mapping relationship between each field in each of the detailed tables and the operation data storage (ODS) table includes:

[0019] Traversing each field in each of the detailed tables, and for the currently traversed field, determining the ODS table containing the currently traversed field as the target ODS table;

[0020] When the number of the target ODS table is one, a mapping relationship is established between the target ODS table and the currently traversed field;

[0021] When there are multiple target ODS tables, one of the target ODS tables is selected to establish a mapping relationship with the currently traversed field.

[0022] In some possible embodiments, generating a dimension table according to predefined supervisory data dimensions includes:

[0023] Acquire the attribute data identifier corresponding to the supervision data dimension, wherein the attribute data identifier includes the attribute data identifier of the business system library and the attribute data identifier of the supervision system;

[0024] The attribute data identifier corresponding to the supervision data dimension is recorded in the dimension table.

[0025] In some possible embodiments, the time dimension includes daily frequency and monthly frequency, and the detailed list includes a detailed list of daily frequency category and a detailed list of monthly frequency category;

[0026] Writing the business data of the ODS table into the corresponding detail table according to the mapping relationship includes:

[0027] According to the mapping relationship and the date of the business data in the ODS table, the business data in the ODS table is written into the full detail table of the corresponding daily frequency class;

[0028] Aggregate the business data of the daily frequency full-scale detailed table of the same month into the monthly frequency full-scale detailed table.

[0029] In some possible embodiments, after generating the full detailed list of the monthly frequency class from the full detailed list of the daily frequency class in the same month, the method further includes:

[0030] Get the full detailed list of monthly frequency classes corresponding to the current month and the previous month respectively;

[0031] Generate the increment detail list for the current month based on the full detail list for the current month and the full detail list for the previous month;

[0032] The data detail layer is connected to the inspection and analysis system, and the increment variable detail table is reported to the inspection and analysis system.

[0033] In some possible embodiments, the method further includes:

[0034] When a change in the business data of a predefined specific field is detected, trajectory data is generated according to the changed business data, and the trajectory data is written into the corresponding daily frequency trajectory detail table according to the date of the change;

[0035] The business data of the daily frequency trajectory details table of the same month are aggregated into the monthly frequency trajectory details table.

[0036] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a supervisory data processing device based on a data mart, wherein the data mart includes a data detail layer, a data dimension layer, and a data service layer, and the device includes:

[0037] A detail table generating module, configured to generate a plurality of detail tables according to a predefined domain dimension and a predefined time dimension, and store the plurality of detail tables in a first database corresponding to the data detail layer;

[0038] A determination module, configured to determine a mapping relationship between each field in each of the detailed tables and the operation data storage ODS table;

[0039] A first data writing module is configured to obtain the ODS table from the ODS layer at a preset time interval, scan the business data in the ODS table, and write the business data in the ODS table into the corresponding detail table according to the mapping relationship;

[0040] A dimension table generation module, configured to generate a dimension table according to predefined supervisory data dimensions, and store the dimension table in a second database corresponding to the data dimension layer;

[0041] A data extraction module, configured to extract corresponding business data from each of the detail tables according to the regulatory data dimension in the dimension table;

[0042] A calculation module, configured to calculate and obtain regulatory data based on the business data corresponding to the regulatory data dimension;

[0043] A second data writing module is used to write the supervision data into a supervision data table, and store the supervision data table in a third database corresponding to the data service layer;

[0044] A reporting module is used to connect the data service layer to the supervision system so as to report the supervision data table to the supervision system through the data service layer.

[0045] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, including a memory and a processor, wherein the memory stores a computer program or instructions, and the processor implements the method described in the first aspect when executing the computer program or instructions.

[0046] To achieve the above-mentioned purpose, the fourth aspect of the embodiment of the present application proposes a computer-readable storage medium, on which a computer program or instructions are stored. When the computer program or instructions are executed by a processor, the method described in the first aspect above is implemented.

[0047] The present application proposes a data mart-based supervisory data processing method, device, and medium. The method generates data detail tables of different dimensions at the data detail layer, then maps the fields in the ODS table with the fields in the data detail table, and writes the data in the ODS table into the corresponding detail table; generates a dimension table according to the pre-defined supervisory data dimension at the data dimension layer; extracts corresponding data from each data detail table according to the dimensions in the dimension table, and integrates them to obtain supervisory data; stores the supervisory data in the supervisory data table located at the data service layer, and connects the data service layer to the supervisory system to report the supervisory data table to the supervisory system. By integrating the data in the detail table to obtain supervisory data, the unified data reported to the supervisory system is achieved, the time cost of extracting and processing data from the business system library is reduced, and the efficiency of reporting to the supervisory system is improved. In addition, the solution of the embodiment of the present application extracts the business data that needs to be supervised from the ODS layer and stores it in the data detail layer. In this way, the associated supervisory data entries can reuse the business data of the data detail layer, avoiding repeated extraction and saving the resource overhead of the data mart. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 Schematic diagram of the structure of the data mart in the embodiment of the present application;

[0049] Figure 2 This is a schematic diagram of the steps of the data mart-based supervisory data processing method provided in an embodiment of the present application;

[0050] Figure 3 yes Figure 2 Schematic diagram of sub-steps of step S102;

[0051] Figure 4 This is a schematic diagram of the steps of another embodiment provided by the present application;

[0052] Figure 5 This is a schematic diagram of the steps of another embodiment provided by the present application;

[0053] Figure 6 yes Figure 2 Schematic diagram of sub-steps of step S103;

[0054] Figure 7 yes Figure 2 Schematic diagram of sub-steps of step S104;

[0055] Figure 8 is a schematic diagram of sub-steps of step S103 provided in another embodiment;

[0056] Figure 9 This is a schematic diagram of steps of another embodiment of the present application;

[0057] Figure 10 The embodiment of the present application provides a supervisory data processing device based on a data mart;

[0058] Figure 11 This is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0060] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0061] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0062] First, let’s analyze some of the terms used in this application:

[0063] A data mart, also known as a data market, is an integrated, subject-oriented data collection used to meet the needs of specific departments or users and is designed to support decision support system (DSS) functions. In a data warehouse, each data unit is related to a specific time. A data warehouse includes atomic-level data and lightly summarized data. It is a subject-oriented, integrated, non-updatable (stable), and time-varying (different time) data collection used to support the decision-making process in business management. It is stored in a multidimensional manner, including defined dimensions, indicators to be calculated, and dimensional hierarchies, to generate data cubes for decision analysis needs. In terms of scope, data is extracted from enterprise-wide databases, data warehouses, or more specialized data warehouses. The focus of a data center is that it caters to the specific needs of professional user groups in terms of analysis, content, presentation, and ease of use.

[0064] ODS table: A data table located in the Operation Data Store (ODS). The data in this table has the following characteristics: 1. The data in the table comes from various operational databases and other external data sources. Before entering the ODS, the data must undergo a data cleaning and processing process (Extract-Transform-Load, ETL) including extraction, cleaning, conversion, and loading; 2. After data cleaning and processing, a certain degree of integration is performed; 3. It can be modified online; 4. The data is obtained in the most recent period.

[0065] The Examination & Analysis System Technology (EAST) is the CBRC's inspection and analysis system, designed to meet the needs of big data development and help regulators improve inspection efficiency. The system includes functional modules such as standardized bank data extraction, on-site inspection project management, data model generation tools, and data model publishing and management. Its core objectives are: 1. Building a relatively open data analysis platform to enable flexible organization, screening, extraction, modeling, mining, and analysis of bank business data; 2. Establishing a universal, relatively closed set of data collection standards to incorporate risk data points of interest to regulators.

[0066] With the increasing demand for automated financial data regulation, institutions are increasingly adopting data marts to submit vast amounts of financial data to regulatory systems. However, because data storage methods differ from the formats used for submission to regulatory systems, data processing in data marts can be time-consuming.

[0067] Based on this, the embodiments of the present application provide a regulatory data processing method and apparatus, equipment and medium based on a data mart, aiming to improve the efficiency of the reporting regulatory system.

[0068] The data mart-based regulatory data processing method and device, electronic device, and storage medium provided in the embodiments of the present application are specifically illustrated through the following embodiments. First, the data mart-based regulatory data processing method in the embodiments of the present application is described.

[0069] The embodiment of the present application can acquire and process relevant data based on data mart technology. Among them, data mart technology requires the establishment of a data mart server, and this technology needs to acquire data from data sources such as data warehouses, business databases, data lakes, etc.

[0070] The embodiment of the present application provides a method for processing regulatory data based on a data mart, which relates to the field of big data processing technology. The embodiment of the present application provides a method for processing regulatory data based on a data mart, which can be applied to a terminal, or to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or as a server cluster or distributed system composed of multiple physical servers, or as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements a method for processing regulatory data based on a data mart, etc., but is not limited to the above forms.

[0071] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0072] It should be noted that, due to the involvement of big data technology, in each specific embodiment of this application, when it comes to the need to perform relevant processing based on data related to user identity or characteristics such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with the relevant laws, regulations, and standards of the relevant countries and regions. In addition, when the embodiment of this application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of this application will be obtained.

[0073] See Figure 1 , Figure 1 It is a structural diagram of the data mart in the embodiment of this application.

[0074] In the embodiment of the present application, based on the data mart 100 technology and in accordance with the steps of the data mart-based supervisory data processing method provided in the embodiment of the present application, the data mart's storage tables are divided into three layers, including a data detail layer 101, a data dimension layer 102, and a data service layer 103. The three layers are respectively provided in a first database 110, a second database 120, and a third database 130. The third database 130 is connected to the first database 110 and the second database 120. The data service layer 103 obtains business data or data dimensions from the data detail layer 101 and the data dimension layer 102 through the connection between the third database 130 and other databases.

[0075] In addition, outside the data mart 100 there are a business system library 104 , an ODS layer 105 , and a supervisory system 106 . The business system library 104 is connected to the ODS layer 105 , and the ODS layer 105 is connected to the first database 110 .

[0076] It should be understood that the number of business databases 104 here can be one or more. Those skilled in the art can set up one or more business databases 104 according to actual business data storage requirements and connect the one or more business databases 104 to the ODS layer 105. This application does not limit this.

[0077] This embodiment of the application provides a data mart-based supervisory data processing method based on the above data mart.

[0078] See Figure 2 , Figure 2 Schematic diagram of the steps of the data mart-based supervisory data processing method provided in the embodiment of the present application. Figure 2 The method may include but is not limited to steps S101 to S108.

[0079] It should be understood that the data mart division level here can be multi-layer, three-layer, or four-layer. Those skilled in the art can add any data operations based on the embodiments of this application according to actual needs, and the increased levels thereby also fall within the scope of protection of this application, and this application does not limit this.

[0080] Step S101: Generate multiple detail tables according to predefined domain dimensions and time dimensions, and store the multiple detail tables in a first database corresponding to the data detail layer.

[0081] It should be understood that the "predefined domain dimensions" mentioned here refer to data domain dimensions within a specific attribute or feature or that are highly correlated with a specific attribute or feature in a field. For example, when it is necessary to obtain financial information, multiple detailed tables will be generated according to the financial domain dimension and the time dimension. The remittance domain dimension, accounting domain dimension, audit domain dimension, and domain dimensions related to finance are all predefined domain dimensions.

[0082] It should be understood that the detail table here includes one or more fact tables, and the fact table here is a detail table used to expand the domain dimension.

[0083] It should be understood that the first database and the business system library here can be set on the same server, or the first database can be set independently on an independent server. Those skilled in the art can set the first database to store multiple detailed tables according to actual conditions, and this application does not limit this.

[0084] It should be understood that the high degree of correlation, as well as specific attributes and characteristics, can be defined by those skilled in the art based on actual conditions, and this application does not limit this.

[0085] It should be understood that the categories of detailed lists here are diverse. Detailed lists can be set according to date or month. Technical personnel in this field can set detailed lists of different categories according to actual needs to meet data requirements. This application does not make any settings for this.

[0086] It should be understood that the data granularity of the detailed list here can be diverse, and those skilled in the art can design the granularity of the detailed list according to actual conditions, and this application does not limit this.

[0087] In some possible embodiments of the present application, the predefined domain dimension is a domain dimension under the business domain. According to the setting of the business domain dimension, a type of detailed list is generated with a predetermined correlation and the same data granularity, and a type of detailed list is generated with the same attributes or the same characteristics.

[0088] Step S102: Determine the mapping relationship between each field in each detail table and the operation data storage (ODS) table.

[0089] It should be understood that the mapping relationship here refers to the correspondence between each field in each detailed table and the field in the operational data storage ODS table. For example, the field related to the customer name is "Customer" in one storage ODS table and "Contact" in another operational data storage ODS table. The data in these two operational data storage ODS tables needs to be integrated in the detailed table and set to "Customer Name", then the "Customer" and "Contact" fields are mapped to "Customer Name".

[0090] It should be understood that the mapping relationship here is diverse. It can be that a field in the operation data storage ODS table is mapped to fields in multiple detailed tables, or it can be similar to the above example, where different multiple fields in multiple operation data storage ODS tables are mapped to fields in a detailed table. Those skilled in the art can determine the mapping relationship between the detailed table fields and the operation data storage ODS table based on actual conditions, and this application does not limit this.

[0091] See Figure 3 , Figure 3 for Figure 2 Schematic diagram of sub-steps of step S102. In some possible embodiments of the present application, step S102 includes but is not limited to the following sub-steps.

[0092] Step S201: traverse each field in each detail table, and for the currently traversed field, determine the ODS table containing the currently traversed field as the target ODS table.

[0093] It should be understood that the fields currently traversed here refer to fields with the same words or the same attributes. For example, in step S102, when the detail table field "Customer Name" is traversed, the above two ODS tables will be determined as the target ODS tables.

[0094] Step S202: When the number of target ODS tables is one, a mapping relationship is established between the target ODS table and the currently traversed field.

[0095] Step S203: When there are multiple target ODS tables, one of the target ODS tables is selected to establish a mapping relationship with the currently traversed field.

[0096] It should be understood that step S202 and step S203 are parallel steps. When step S202 is executed, step S203 is not executed, and when step S203 is executed, step S202 is not executed.

[0097] It should be understood that in step S03, the selection method here can be diverse, it can be random selection, it can be biased selection, or it can be selected according to the update time of the data table. For example, if a customer has a phone number A under the "Contact Information" field in the customer information ODS table, and also has a phone number A under the "Phone" field in the beneficiary information ODS table, when it is necessary to map to a detailed table about the customer's insurance policy, select the ODS table with the closest record time in the two ODS tables to establish a mapping with the detailed table; for example, taking the above example, for example, setting the beneficiary information ODS table to be more biased than the customer information ODS table, when both ODS tables are target ODS tables, it is preferred to map the beneficiary ODS table to the detailed table. Technical personnel in this field can select a target ODS table based on preset rules according to actual conditions, and this application does not limit this.

[0098] See Figure 4 , Figure 4 This is a schematic diagram of steps of another embodiment provided by the present application. In some possible embodiments of the present application, before step S102, the following steps are included but not limited to.

[0099] Step S301: extract multiple business data from the business system library.

[0100] It should be understood that the business system library here refers to the database of data stored under different businesses. The business data stored is different. Since the data recording method and table in each business system library are different, the operations on each business data are also different. The business data needs to be extracted to the ODS layer for processing to reduce the difficulty of business data operations.

[0101] It should be understood that the business data here is stored in the business system library in the form of data tables.

[0102] Step S302: Determine the fields corresponding to the business data according to the source interface for collecting the business data.

[0103] It should be understood that the source interface here refers to the interface for obtaining multiple business data in the business system library. The source of each business data is different, and the interface is also different; the corresponding fields here refer to the fields originally set for the business data. Therefore, each different source interface represents the type of data from this interface. These types of data will be stored in the originally set fields. According to the interface, it can be determined which originally set fields the current business data was previously stored in, that is, it is stored in the fields corresponding to the business data. For example, if the data of interface A comes from the insurance business department, then the business data under this department is stored in the original fields "customer name" and "insurance amount". When obtaining data from interface A, it can be known that the business data obtained by the current interface will have the two fields "customer name" and "insurance amount".

[0104] It should be understood that the number of corresponding fields here can be the same or different in each business data, and this application does not limit the number of fields corresponding to the business data.

[0105] Step S303: Determine the ODS table corresponding to the business data according to the fields corresponding to the business data.

[0106] It should be understood that there are multiple ODS tables here, and those skilled in the art can set a specific number of ODS tables in detail according to actual conditions to match data processing requirements, and this application does not limit this.

[0107] It should be understood that the corresponding ODS table is determined here based on the field, and the ODS table corresponding to the business data is determined based on one or more fields in the business data. For example, if an ODS table is named "Insurance Business Department Data Table" and a certain business data includes the "Insurance Amount" field, then it can be determined that the business data corresponds to the ODS table named "Insurance Business Department Data Table".

[0108] It should be understood that those skilled in the art may preset rules based on actual conditions to determine the ODS table corresponding to the business data using one or more fields included in the business data, and this application does not limit this.

[0109] It should be understood that the number of corresponding ODS tables here is diverse, which can be one or multiple different types of ODS tables. Those skilled in the art can set the number of ODS tables corresponding to a certain business data according to actual data processing requirements, and this application does not limit this.

[0110] Step S304: Write the business data into the corresponding ODS table.

[0111] It should be understood that the ODS table here can be designed to be the same as the table originally storing the business data, or it can be different. Those skilled in the art can design the ODS table according to data processing requirements, and this application does not limit this.

[0112] It should be understood that the data in the ODS table is the original business data, and no changes are made to the specific data when it is written into the detail table.

[0113] By extracting business data and writing it into the ODS table in the ODS layer, damage to the original data in the business system library terminal is reduced, and the difficulty of data call operations for technical personnel is also reduced.

[0114] Step S103 : obtaining the ODS table from the ODS layer at a preset time interval, scanning the business data in the ODS table, and writing the business data in the ODS table into the corresponding detail table according to the mapping relationship.

[0115] It should be understood that when multiple ODSs map a detailed table, there may be problems such as different data record formats and data time synchronization. Technical personnel in this field can handle the problems of different mapped data according to actual needs. For example, as in step S203, an ODS table data is selected as the data of the field in the name table. This application does not limit this.

[0116] It should be understood that the data in the ODS table is changeable. Writing the business data into the ODS table here can refer to writing all business data into the corresponding detail table at the beginning of the data mart establishment to complete the establishment of the data mart detail layer, or it can refer to obtaining and scanning the ODS table after establishment and writing the newly added data in the table into the corresponding detail table.

[0117] Specifically, the ODS table is obtained from the ODS layer at a preset time interval, and the business data in the ODS table is scanned, and the business data in the ODS table is written into the corresponding detail table in the first database according to the mapping relationship.

[0118] See Figure 5 , Figure 5 This is a schematic diagram of steps of another embodiment provided by the present application. In some possible embodiments of the present application, before step S103, the following steps are included but not limited to:

[0119] Step S401: When the mapping relationship between the fields in the detail table and the ODS table cannot be determined, the ODS table data is supplemented.

[0120] It should be understood that the number of detailed tables and the number of fields in the detailed tables are diverse. It may be that a field in a detailed table cannot determine the mapping relationship, or it may be that multiple fields in a detailed table cannot determine the mapping relationship, or it may be that one field or multiple fields in multiple detailed tables cannot determine the mapping relationship. This application does not limit this.

[0121] By supplementing the data in the ODS table, the detailed table data can be kept complete and the system errors in subsequent data calculation and processing can be reduced.

[0122] See Figure 6 , Figure 6 for Figure 2 Schematic diagram of sub-steps of step S103. In some possible embodiments of the present application, step S103 includes but is not limited to the following sub-steps.

[0123] Step S501: Based on the mapping relationship and the date of the business data in the ODS table, the business data in the ODS table is written into the corresponding full detail table of the daily frequency class.

[0124] It should be understood that the time dimension mentioned in step S101 includes the daily frequency and monthly frequency mentioned here; the daily frequency mentioned here refers to one day, and the monthly frequency refers to one month.

[0125] It should be understood that the full detailed list here refers to the statistics of all data within a certain frequency. For example, the full detailed list of the daily frequency class refers to all the information collected on a certain day. Taking the example described in step S102, the daily frequency class data of B month C day is collected, and the "Customer Name" field will search for all data with the date of B month C day in the ODS table, and write the data mapped to the "Customer Name" field in these data into the full detailed list of the daily frequency class corresponding to B month C day.

[0126] Step S502: aggregate the business data of the full detailed list of the daily frequency class in the same month into the full detailed list of the monthly frequency class.

[0127] It should be understood that the summary here can be diverse. It can be to summarize only the full detailed list of the daily frequency category of the same month, or to combine the data in certain fields in other detailed lists with the full detailed list of the daily frequency category of the same month to assist in summarizing the full detailed list of the monthly frequency category. Technical personnel in this field can summarize the full detailed list of the monthly frequency category according to actual data requirements, and this application does not limit this.

[0128] It should be understood that the daily frequency category and monthly frequency category here are just information tables divided into different categories based on the time dimension. For example, they are daily frequency category business details table, daily frequency category trajectory details table, monthly frequency category business details table, and monthly frequency category trajectory details table. This application does not limit this.

[0129] The embodiment of the present application summarizes the data of daily frequency category and monthly frequency category, and the system reporting data can directly extract data from the monthly frequency category table for reporting, thereby improving the efficiency of the subsequent data reporting system and reducing the time cost of extracting data during reporting.

[0130] Step S104: Generate a dimension table according to the predefined supervisory data dimension, and store the dimension table in a second database corresponding to the data dimension layer.

[0131] It should be understood that the pre-defined regulatory data dimension here refers to the expression mapping of the same data between the business system library and the regulatory reporting system. Since the data in the detailed table is obtained from the business system library and has not been changed in the above steps, the specific data in the detailed table is the same as the specific data in the business system library. For example, if the gender data represented in the business system library is a number, then the business data representing gender in the detailed table is also the same number. Therefore, it is necessary to generate a dimension table to provide a mapping basis for certain specific data in the detailed table and the specific data in the regulatory data table submitted to the regulatory reporting system. For example, in the "gender" field in the regulatory data table submitted to the regulatory reporting system, male is represented by M, female is represented by F, and unknown gender is represented by X. In the business system library, all genders are represented by numbers, with male represented by 1, female represented by 2, and unknown gender represented by 0. At this time, the generated dimension table will include their corresponding relationships, with M corresponding to 1, F corresponding to 2, and X corresponding to 0.

[0132] It should be understood that the number of dimension tables here can be one or more, and those skilled in the art can set them according to actual data requirements, and this application does not limit this.

[0133] It should be understood that there are various ways to obtain the pre-defined regulatory data dimensions here. They can be obtained from the interface provided by the regulatory system or from the reporting history. Technical personnel in this field can choose the corresponding dimension acquisition method according to actual needs, and this application does not limit this.

[0134] It should be understood that the second database and the business system library here can be set on the same server, or the second database can be set independently on an independent server, or the second database and the first database can be set on the same server. Those skilled in the art can set the second database to store multiple dimension tables according to actual conditions, and this application does not limit this.

[0135] See Figure 7 , Figure 7 for Figure 2 Schematic diagram of sub-steps of step S104. In some possible embodiments of the present application, step S104 includes but is not limited to the following sub-steps.

[0136] Step S601: Obtain the attribute data identifier corresponding to the supervision data dimension.

[0137] Step S602: Record the attribute data identifier corresponding to the supervision data dimension in the dimension table.

[0138] It should be understood that the attribute data identification here includes the attribute identification of the business system library and the attribute identification of the supervision system.

[0139] It should be understood that the specific setting method of the attribute identification here can be diverse. For example, in step S104, the corresponding conversion between letters and numbers for gender representation is performed; for another example, the "insurance amount" field in the business system library records detailed numbers, and the detailed numbers in a certain range are recorded as insured risk types in the regulatory data table. For example, if the insurance amount is 14,000, the regulatory data table records it as a small risk. Technical personnel in this field can record the attribute data identification corresponding to certain specific data according to actual conditions, and this application does not limit this.

[0140] The embodiment of the present application improves the efficiency of the subsequent data reporting system by setting a dimension table and reduces the time cost of extracting data during reporting.

[0141] Step S105: extract corresponding business data from each detail table according to the supervision data dimension in the dimension table.

[0142] It should be understood that the business data in the detailed table is sorted business data and does not meet the requirements of reporting to the regulatory system, and not all business data needs to be reported to the regulatory system. Therefore, the corresponding data needs to be extracted from the detailed table and processed to meet the requirements of reporting to the regulatory system.

[0143] It should be understood that the extraction here is carried out according to the preset extraction rules, and the extraction rules corresponding to each regulatory data dimension are different. For example, as shown in the example of step S601 to step S602, for a customer, the preset extraction rule of the insured risk type is to extract the business data of the customer under the "insurance amount" field from the detailed table with the "insurance amount" field. Those skilled in the art can set the extraction rules according to actual needs and extract the corresponding business data from the detailed table according to the regulatory data, and this application does not limit it.

[0144] It should be understood that the extraction here refers to screening out detailed tables containing table headers corresponding to the regulatory data dimensions from various data tables in the first database according to the needs of the regulatory data dimensions, and extracting corresponding business data from these detailed tables.

[0145] Step S106: Integrate the business data corresponding to the regulatory data dimension to obtain regulatory data.

[0146] It should be understood that the integration forms here are diverse. For example, as in the example in step S105, the extracted insurance amount data is calculated according to the preset financial calculation rules to obtain a total insurance amount data; for example, as in the gender example in step S104, the gender is integrated from numerical representation to alphabetical representation. Those skilled in the art can integrate the business data corresponding to the regulatory data dimension according to the requirements of the reporting regulatory system, and this application does not limit this.

[0147] It should be understood that the preset financial calculation rules mentioned here refer to an algorithm for processing data. These algorithms have multiple options and can be a reserve algorithm or a reinsurance algorithm. Those skilled in the art can obtain and apply a corresponding algorithm as the preset financial calculation rules according to actual conditions. This application does not limit this.

[0148] Step S107: writing the supervision data into the supervision data table, and storing the supervision data table in the third database corresponding to the data service layer.

[0149] It should be understood that the number of regulatory data tables here can be diverse, it can be one or more, and the number varies according to the requirements of the reporting regulatory system. Technical personnel in this field can set the corresponding number of regulatory data tables according to the actual requirements of the reporting regulatory system, and this application does not limit this.

[0150] It should be understood that the regulatory data written into the regulatory data table here can be diverse, and can be written in accordance with the types and number of regulatory systems that the service layer needs to access. For example, if the data table submitted to regulatory system A and the data table submitted to regulatory system B are different, but both systems need to supervise the insurance amount, then the business data of the insurance amount integrated in step S106 needs to be written into the data table of regulatory system A and the data table submitted to regulatory system B at the same time. Technical personnel in this field can write the regulatory data into the corresponding regulatory data table according to actual needs, and this application does not limit this.

[0151] It should be understood that there are various ways to set up the third database on the server side. For example, if it is set up on the same server side as the first database and the second database, those skilled in the art can set up the third database according to actual conditions to store multiple regulatory data tables. This application does not limit this.

[0152] Step S108: Connect the data service layer to the supervision system to report the supervision data table to the supervision system through the data service layer.

[0153] It should be understood that the regulatory systems here can be diverse and multiple, and can be an inspection subsystem, an anti-money laundering reporting system, or an insurance policy registration system. Technical personnel in this field can access one or more regulatory systems according to actual reporting needs, and this application does not limit this.

[0154] It should be understood that the data service layer here is connected to the supervision system through the third database to achieve data service layer access to the supervision system

[0155] It should be understood that in addition to the data service layer, the data detail layer and the data dimension layer are also connected to the supervision system through their respective databases. The data detail layer and the data dimension layer can directly report the corresponding tables to the supervision system. When the supervision system needs additional detail tables and dimension tables in addition to the supervision data table, it can directly extract and report them from the corresponding data layer to assist in the reporting of the supervision data table.

[0156] Specifically, the data service layer is connected to the supervision system. When a report needs to be submitted to a certain supervision system, the corresponding supervision data table in the data service layer is extracted and submitted to the supervision system.

[0157] In addition, the solution of the embodiment of the present application extracts the business data that needs to be regulated from the ODS layer and stores it in the data detail layer, so that the associated regulatory data entries can reuse the business data of the data detail layer, avoiding repeated extraction and saving the resource overhead of the data mart.

[0158] See Figure 8 , Figure 8A schematic diagram of sub-steps of step S103 is provided for another embodiment. In some possible embodiments of the present application, when the last reported supervision system is an inspection and analysis system, after step S502, the sub-steps of step 103 also include but are not limited to the following steps.

[0159] Step S701: Obtain the full detailed list of monthly frequency categories corresponding to the current month and the previous month respectively.

[0160] It should be understood that the current month here refers to the month corresponding to the full detailed list of the monthly frequency class summarized in step S502, for example, month B mentioned in step S502.

[0161] It should be understood that the steps for obtaining the full detailed list of monthly frequency categories corresponding to the current month and the previous month are the same, and both can be obtained through steps S501 to S502.

[0162] Step S702: Generate the increment detail list of the current month based on the full detail list of the current month and the full detail list of the previous month.

[0163] It should be understood that the incremental variables recorded in the incremental variable details table here can be diverse, and can be the growth in the number of customers or the growth in the corresponding customer insurance coverage. Technical personnel in this field can set it according to the actual reporting requirements of the regulatory system, and this application does not limit this.

[0164] Step S703: Connect the data detail layer to the inspection and analysis system, and submit the incremented variable detail table to the inspection and analysis system.

[0165] It should be understood that the data detail layer is connected to the inspection and analysis system. When it is necessary to report to the inspection and analysis system, in addition to extracting the corresponding regulatory data table from the data service layer, the incremental variable detail table will also be extracted from the data detail layer to meet the special reporting requirements of the inspection and analysis system.

[0166] It should be understood that connecting the data detail layer to the inspection and analysis system here means connecting the data detail layer to the inspection and analysis system through the first database.

[0167] See Figure 9 , Figure 9 This is a schematic diagram of steps in another embodiment of the present application. In some possible embodiments of the present application, after step S108, the following steps are also included but not limited to.

[0168] Step S109: When a change in the business data of a predefined specific field is detected, trajectory data is generated according to the changed business data, and the trajectory data is written into the corresponding daily frequency trajectory list according to the date of the change.

[0169] It should be understood that step S109 of obtaining the daily frequency track list is the same as step S501 , and the track data with business data changes are written into the daily frequency track list of the day according to the corresponding date.

[0170] It should be understood that when the business data here changes, the detail table, dimension table and regulatory data table will be updated synchronously.

[0171] It should be noted that when the trajectory data enters the data detail layer, steps S301 to S304 are not executed, but the data is directly written into the corresponding detail table in the data detail layer, that is, no mapping is performed.

[0172] Step S110: Aggregate the business data of the daily frequency trajectory details table of the same month into a monthly frequency trajectory details table.

[0173] It should be understood that step S110 of obtaining the monthly frequency track list is the same as step S502 , and the track data with business data changes are written into the monthly frequency track list of the corresponding month.

[0174] The embodiment of the present application compares the data submitted to the supervision system through a data trajectory table to prevent the updated business data from being submitted to the supervision system without being summarized and integrated, thereby reducing the probability of reporting accidents.

[0175] The embodiment of the present application generates data detail tables of different dimensions at the data detail layer, then maps the fields in the ODS table with the fields in the data detail table, and writes the data in the ODS table into the corresponding detail table; generates a dimension table according to the pre-defined regulatory data dimension at the data dimension layer; extracts corresponding data from each data detail table according to the dimension in the dimension table, and integrates them to obtain regulatory data; stores the regulatory data in the regulatory data table located at the data service layer, and connects the data service layer to the regulatory system to report the regulatory data table to the regulatory system. By integrating the data in the detail table to obtain regulatory data, the unification of data reported to the regulatory system is achieved, the time cost of extracting and processing data from the business system library is reduced, and the efficiency of reporting to the regulatory system is improved.

[0176] See Figure 10 , Figure 10 The present invention provides a data mart-based supervisory data processing apparatus for implementing the aforementioned data mart-based supervisory data processing method. It should be understood that the data mart referred to herein is the same as the data mart referred to in the aforementioned data mart-based supervisory data processing method. The apparatus 900 includes:

[0177] The detail table generating module 901 is used to generate multiple detail tables according to predefined domain dimensions and time dimensions, and store the multiple detail tables in the data detail layer.

[0178] The determination module 902 is used to determine the mapping relationship between each field in each detail table and the operation data storage ODS table.

[0179] The first data writing module 903 is used to write the business data of the ODS table into the corresponding detail table according to the mapping relationship.

[0180] The dimension table generating module 904 is configured to generate a dimension table according to predefined supervisory data dimensions and store the dimension table in a data dimension layer.

[0181] The data extraction module 905 is used to extract corresponding business data from the detail table according to the supervision data dimension in the dimension table.

[0182] The calculation module 906 is used to calculate the supervision data according to the business data corresponding to the supervision data dimension.

[0183] The second data writing module 907 is configured to write the supervision data into the supervision data table and store the supervision data table in the data service layer.

[0184] The reporting module 908 is used to connect the data service layer to the supervision system to report the supervision data table to the supervision system.

[0185] The specific implementation of the data mart-based supervisory data processing device 900 is substantially the same as the specific embodiment of the above-mentioned data mart-based supervisory data processing method, and will not be described in detail here.

[0186] The present application also provides an electronic device comprising a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned data mart-based supervisory data processing method. The electronic device can be any smart terminal, including a tablet computer and an in-vehicle computer.

[0187] See Figure 11 , Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device 1000 includes:

[0188] The processor 1001 can be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0189] The memory 1002 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1002 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program codes are stored in the memory 1002 and are called by the processor 1001 to execute the data mart-based supervisory data processing method of the embodiments of this application.

[0190] Input / output interface 1003, used to implement information input and output;

[0191] Communication interface 1004, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);

[0192] Bus 1005 , which transmits information between various components of the device (e.g., processor 1001 , memory 1002 , input / output interface 1003 , and communication interface 1004 );

[0193] The processor 1001 , the memory 1002 , the input / output interface 1003 and the communication interface 1004 are connected to each other in communication within the device via the bus 1005 .

[0194] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned data mart-based regulatory data processing method.

[0195] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0196] The regulatory data processing method based on data mart, the regulatory data processing device based on data mart, the electronic device and the storage medium provided by the embodiment of the present application generate data detail tables of different dimensions at the data detail layer, then map the fields in the ODS table with the fields in the data detail table, and write the data in the ODS table into the corresponding detail table; generate a dimension table according to the predefined regulatory data dimensions at the data dimension layer; extract the corresponding data from each data detail table according to the dimensions in the dimension table, and integrate them to obtain regulatory data; store the regulatory data in the regulatory data table located at the data service layer, and connect the data service layer to the regulatory system to report the regulatory data table to the regulatory system. By integrating the data in the detail table to obtain regulatory data, the unification of data reported to the regulatory system is achieved, the time cost of extracting and processing data from the business system library is reduced, and the efficiency of reporting to the regulatory system is improved.

[0197] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0198] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0199] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0200] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0201] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0202] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0203] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0204] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0205] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0206] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0207] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A supervisory data processing method based on a data mart, characterized in that: The data mart includes a data detail layer, a data dimension layer, and a data service layer. The method includes the following steps: Generate multiple detail tables according to predefined domain dimensions and time dimensions, and store the multiple detail tables in a first database corresponding to the data detail layer; Determine the mapping relationship between each field in each of the detailed tables and the operation data storage ODS table; Obtain the ODS table from the ODS layer at a preset time interval, scan the business data in the ODS table, and write the business data in the ODS table into the corresponding detail table according to the mapping relationship; Generate a dimension table according to predefined regulatory data dimensions, and store the dimension table in a second database corresponding to the data dimension layer; Extracting corresponding business data from each of the detail tables according to the supervision data dimension in the dimension table; Obtaining regulatory data based on business data integration corresponding to the regulatory data dimension; Writing the supervision data into a supervision data table, and storing the supervision data table in a third database corresponding to the data service layer; The data service layer is connected to the supervision system, so as to report the supervision data table to the supervision system through the data service layer.

2. The data mart-based supervisory data processing method according to claim 1, characterized in that: The ODS table includes a plurality of fields. Before determining the mapping relationship between each field in each of the detailed tables and the operation data storage ODS table, the method further includes: Extracting a plurality of business data from a business system library; Determining, based on a source interface for collecting the business data, fields corresponding to the business data; Determine the ODS table corresponding to the business data according to the fields corresponding to the business data; The business data is written into the corresponding ODS table.

3. The data mart-based supervisory data processing method according to claim 2, characterized in that: Determining the mapping relationship between each field in each detail table and the operation data storage ODS table includes: Traversing each field in each of the detailed tables, and for the currently traversed field, determining the ODS table containing the currently traversed field as the target ODS table; When the number of the target ODS table is one, a mapping relationship is established between the target ODS table and the currently traversed field; When there are multiple target ODS tables, one of the target ODS tables is selected to establish a mapping relationship with the currently traversed field.

4. The data mart-based supervisory data processing method according to claim 2, characterized in that: Generating a dimension table according to predefined regulatory data dimensions includes: Acquire the attribute data identifier corresponding to the supervision data dimension, wherein the attribute data identifier includes the attribute data identifier of the business system library and the attribute data identifier of the supervision system; The attribute data identifier corresponding to the supervision data dimension is recorded in the dimension table.

5. The supervisory data processing method based on data mart according to claim 1, characterized in that: The time dimension includes daily frequency and monthly frequency, and the detailed list includes a detailed list of daily frequency and a detailed list of monthly frequency; Writing the business data of the ODS table into the corresponding detail table according to the mapping relationship includes: According to the mapping relationship and the date of the business data in the ODS table, the business data in the ODS table is written into the full detail table of the corresponding daily frequency class; Aggregate the business data of the daily frequency full-scale detailed table of the same month into the monthly frequency full-scale detailed table.

6. The data mart-based supervisory data processing method according to claim 5, characterized in that: After aggregating the full detailed list of the daily frequency class in the same month into the full detailed list of the monthly frequency class, the method further includes: Get the full detailed list of monthly frequency classes corresponding to the current month and the previous month respectively; Generate the increment detail list for the current month based on the full detail list for the current month and the full detail list for the previous month; The data detail layer is connected to the inspection and analysis system, and the increment variable detail table is reported to the inspection and analysis system.

7. The supervisory data processing method based on data mart according to claim 5, characterized in that: The method further comprises: When a change in the business data of a predefined specific field is detected, trajectory data is generated according to the changed business data, and the trajectory data is written into the corresponding daily frequency trajectory detail table according to the date of the change; The business data of the daily frequency trajectory details table of the same month are aggregated into the monthly frequency trajectory details table.

8. A data supervision and processing device based on a data mart, characterized in that: The data mart includes a data detail layer, a data dimension layer and a data service layer, and the device includes: A detail table generating module, configured to generate a plurality of detail tables according to a predefined domain dimension and a predefined time dimension, and store the plurality of detail tables in a first database corresponding to the data detail layer; A determination module, configured to determine a mapping relationship between each field in each of the detailed tables and the operation data storage ODS table; A first data writing module is configured to obtain the ODS table from the ODS layer at a preset time interval, scan the business data in the ODS table, and write the business data in the ODS table into the corresponding detail table according to the mapping relationship; A dimension table generation module, configured to generate a dimension table according to predefined supervisory data dimensions, and store the dimension table in a second database corresponding to the data dimension layer; A data extraction module, configured to extract corresponding business data from each of the detail tables according to the regulatory data dimension in the dimension table; A calculation module, configured to calculate and obtain regulatory data based on the business data corresponding to the regulatory data dimension; A second data writing module is used to write the supervision data into a supervision data table, and store the supervision data table in a third database corresponding to the data service layer; The reporting module is used to connect the data service layer to the supervision system to report the supervision data table to the supervision system.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program or instructions, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program or instructions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program or instructions, which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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