Data management method and device, electronic equipment and computer readable storage medium

Abstract

The application relates to the technical field of financial technology, and provides a data management method and device, electronic equipment and a computer readable storage medium. The method comprises the following steps: acquiring data requirement information of a business system, wherein the data requirement information comprises business type marking information and business execution step information; selecting a corresponding target data application program from a preset data management middle platform according to the business type marking information and the business execution step information; acquiring a corresponding execution list from a preset database according to the target data application program, wherein the execution list carries execution sequence information; determining a corresponding executor combination according to the execution sequence information; and performing execution processing on the execution list according to the executor combination to obtain a data execution result. Through the above technical solution, the business requirements of different financial businesses can be solved through the data unified management mode, and the repeated construction of financial industry data is avoided.

Description

Technical Field

[0001] The embodiments of this application relate to, but are not limited to, the field of financial technology, and particularly to a data management method, apparatus, electronic device, and computer-readable storage medium. Background Technology

[0002] A data platform is a complete system situated between the underlying storage and computing platform and the upper-level data applications. It shields the underlying storage platform from the complexity of computing technology, reduces the need for technical talent, and lowers the cost of data usage. Due to these advantages, data platforms are widely used in the financial industry. By implementing layered data management, coupled with asset management and data services, data assets are transformed into data service capabilities to serve the business operations of financial enterprises. Before establishing a data platform, financial enterprises lacked sufficient understanding of data governance and lacked standardized systems. The financial industry faced high barriers to entry for using data services and long data acquisition cycles; data development was often redundant and siloed. Summary of the Invention

[0003] The following is an overview of the subject matter described in detail herein. This overview is not intended to limit the scope of the claims.

[0004] To address the problems mentioned in the background section, this application provides a data management method, apparatus, electronic device, and computer-readable storage medium that can solve different business needs in the financial industry through unified data management, effectively avoiding redundant data construction in the financial industry.

[0005] In a first aspect, embodiments of this application provide a data management method, the method comprising:

[0006] Obtain data requirement information from the business system, wherein the data requirement information includes business type marking information and business execution step information;

[0007] Based on the business type marking information and the business execution step information, the corresponding target data application is selected from the preset data management platform;

[0008] According to the target data, the application retrieves the corresponding execution list from the preset database, wherein the execution list carries execution order information;

[0009] The corresponding executor combination is determined based on the execution sequence information;

[0010] The execution list is processed according to the executor combination to obtain the data execution result.

[0011] According to some embodiments of this application, the data management platform is created in the following manner:

[0012] Information on the requirements for obtaining raw data;

[0013] The original data requirement information is processed by data domain partitioning to obtain data domain partitioning information;

[0014] Construct a bus matrix based on the data domain partitioning information and define statistical indicators based on the data domain partitioning information;

[0015] Construct a consistency logical dimension and dimension attributes based on the bus matrix; and construct a consistency metric and consistency index based on the statistical indicators.

[0016] A detailed model is constructed based on the consistency logical dimension and the dimension attribute; and a summary model is constructed based on the consistency metric and the consistency index.

[0017] The detailed model and the summary model are processed by data business logic editing to obtain the data management platform.

[0018] According to some embodiments of this application, the data management platform includes multiple data applications, each carrying application scenario information. The step of selecting a corresponding target data application from a preset data management platform based on the business type tagging information and the business execution step information includes:

[0019] The business type tagging information and the business execution step information are both matched with the application scenario information to obtain a matching result;

[0020] Based on the matching results, a corresponding data application is selected from the data management platform as the target data application.

[0021] According to some embodiments of this application, the target data application carries address tagging information, and the step of obtaining the corresponding execution list from a preset database based on the target data application includes:

[0022] The address tag information is analyzed to obtain the data storage address information;

[0023] The corresponding execution list is extracted from the database based on the data storage address information.

[0024] According to some embodiments of this application, the actuator combination includes multiple actuators, each actuator carrying execution attribute information, and determining the corresponding actuator combination based on the execution order information includes:

[0025] The execution sequence information is analyzed and processed to obtain execution marker information;

[0026] The comparison information is obtained by comparing the execution marker information with the execution attribute information;

[0027] Multiple actuators are selected based on the comparison information, and the selected multiple actuators are combined into the actuator combination.

[0028] According to some embodiments of this application, the execution list includes multiple stages of execution sub-information, and the step of performing execution processing on the execution list according to the executor combination to obtain data execution results includes:

[0029] Execution information is determined based on the combination of multiple stage execution sub-information and the executor;

[0030] The executor combination processes the execution information of multiple stage execution sub-information according to the execution information to obtain the data execution result.

[0031] According to some embodiments of this application, after performing execution processing on the execution list according to the executor combination to obtain the data execution result, the method further includes:

[0032] Add cache address tagging information to the execution result;

[0033] The execution result is stored in a preset cache range according to the cache address marking information.

[0034] Secondly, embodiments of this application also provide a data management device, the device comprising:

[0035] The first processing module is used to obtain data requirement information from the business system, wherein the data requirement information includes business type marking information and business execution step information;

[0036] The second processing module is used to select the corresponding target data application from the preset data management platform according to the business type marking information and the business execution step information;

[0037] The third processing module is used to obtain the corresponding execution list from a preset database according to the target data application, wherein the execution list carries execution order information;

[0038] The fourth processing module is used to determine the corresponding executor combination based on the execution order information;

[0039] The fifth processing module is used to perform execution processing on the execution list according to the executor combination to obtain data execution results.

[0040] Thirdly, embodiments of this application also provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the data management method described in the first aspect above.

[0041] Fourthly, embodiments of this application also provide a computer-readable storage medium storing computer-executable instructions for performing the data management method described in the first aspect above.

[0042] The data management method according to the embodiments provided in this application has at least the following beneficial effects: In the process of data management in the financial industry, firstly, data requirement information of the business system is obtained, wherein the data requirement information includes business type marking information and business execution step information; then, a corresponding target data application is selected from a preset data management platform according to the business type marking information and business execution step information; next, a corresponding execution list is obtained from a preset database according to the target data application, wherein the execution list carries execution order information; then, a corresponding executor combination is determined according to the execution order information; finally, the execution list can be executed according to the executor combination to obtain the data execution result. Through the above technical solution, different business needs in the financial industry can be solved through unified data management, effectively avoiding the duplication of data construction in the financial industry. Attached Figure Description

[0043] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0044] Figure 1 This is a flowchart of a data management method provided in one embodiment of this application;

[0045] Figure 2 This is a flowchart illustrating the creation of a data management platform in a data management method provided in one embodiment of this application;

[0046] Figure 3 This is a flowchart illustrating the selection of a target data application in a data management method provided in one embodiment of this application;

[0047] Figure 4 This is a flowchart illustrating the process of obtaining an execution list in a data management method provided in one embodiment of this application;

[0048] Figure 5 This is a flowchart illustrating the determination of a corresponding actuator combination in a data management method provided in one embodiment of this application;

[0049] Figure 6 This is a flowchart illustrating the execution processing of an execution list in a data management method provided in one embodiment of this application;

[0050] Figure 7 This is another embodiment of the data management method provided in this application;

[0051] Figure 8 This is a schematic diagram of a data management device provided in one embodiment of this application;

[0052] Figure 9 This is a schematic diagram of an electronic device provided in one embodiment of this application. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0054] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0055] It should be noted that, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0056] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0057] AI is a new technical science that studies and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence. Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce new intelligent machines that can react in a way similar to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, and expert systems. Artificial intelligence can simulate the information processes of human consciousness and thought. Furthermore, artificial intelligence utilizes digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceiving the environment, acquiring knowledge, and using that knowledge to achieve optimal results—the theories, methods, technologies, and application systems available for use.

[0058] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0059] Artificial intelligence, or AI, is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0060] The servers involved in artificial intelligence technology can be standalone servers or cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0061] This application provides a data management method, apparatus, electronic device, and computer-readable storage medium. In the process of data management in the financial industry, the method first acquires data requirement information from the business system, including business type labeling information and business execution step information. Next, based on the business type labeling information and business execution step information, a corresponding target data application is selected from a preset data management platform. Then, based on the target data application, a corresponding execution list is retrieved from a preset database, where the execution list carries execution order information. Next, based on the execution order information, a corresponding executor combination is determined. Finally, the execution list is processed according to the executor combination to obtain the data execution result. This technical solution addresses different business needs in the financial industry through unified data management, effectively avoiding redundant data construction in the financial industry.

[0062] The data management method provided in this application relates to the field of financial technology. The data management method provided in this application can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application implementing the data management method, but is not limited to the above forms.

[0063] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: 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, and distributed computing environments including any of the above systems or devices. This 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, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0064] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0065] The embodiments of this application will be further described below with reference to the accompanying drawings.

[0066] like Figure 1 As shown, Figure 1This is a flowchart of a data management method provided in one embodiment of this application, which includes, but is not limited to, steps S100 to S500.

[0067] Step S100: Obtain data requirement information from the business system, wherein the data requirement information includes business type marking information and business execution step information;

[0068] Step S200: Select the corresponding target data application from the preset data management platform according to the business type marking information and business execution step information;

[0069] Step S300: Based on the target data, the application retrieves the corresponding execution list from the preset database, wherein the execution list carries execution order information;

[0070] Step S400: Determine the corresponding actuator combination based on the execution sequence information;

[0071] Step S500: Perform execution processing on the execution list according to the executor combination to obtain the data execution result.

[0072] It should be noted that in the process of data management in the financial industry, the first step is to obtain the data requirement information of the business system. This information includes business type identification information and business execution step information. Next, based on the business type identification information and execution step information, the corresponding target data application is selected from the preset data management platform. Then, based on the target data application, the corresponding execution list is retrieved from the preset database. This execution list carries execution order information. Next, based on the execution order information, the corresponding executor combination is determined. Finally, the execution list can be processed according to the executor combination to obtain the data execution result. This technical solution addresses the diverse business needs of the financial industry through unified data management, effectively avoiding redundant data construction within the financial sector.

[0073] It is worth noting that a business system is a system that can provide services to customers. For example, a business system can be a big data engineering platform, a model development platform, a profiling platform, a data asset platform, a bank loan platform, a bank deposit platform, a transaction platform, an insurance platform, an order platform, and a master data management platform. In the process of obtaining data requirement information from a business system, this can be achieved by sending request commands. This data requirement information includes business type marking information and business execution step information. The business type marking information indicates the type of business to be executed, and the business execution step information indicates the relevant steps to be performed. For example, in the insurance industry, the data requirement information of the insurance business system can be obtained first. This information includes insurance business type marking information and insurance business execution step information. Based on the insurance business type marking information and the insurance agent's execution step information, the corresponding insurance business target data application can be selected from a pre-set financial industry data management platform. Next, based on the insurance business target data application, the corresponding insurance business execution list can be retrieved from a pre-set database. Then, based on the execution order information of the insurance business execution list, the corresponding insurance business executor combination can be determined. Finally, the insurance business execution list can be processed by the insurance business executor combination to obtain the insurance business data execution result.

[0074] It should be noted that, based on the business type marking information and business execution step information, the corresponding target data application can be selected from the preset data management platform; the data management platform may include multiple target data applications. In some specific embodiments of this application, the corresponding target data application can be selected from the data management platform based on the business type marking information and business execution step information.

[0075] It's important to note that a data platform is a complete system situated between the underlying storage and computing platform and the upper-level data applications. It shields the underlying storage platform from the complexity of its computing technology, reduces the need for technical talent, and lowers the cost of data usage. By implementing layered data management, along with asset management and data services, it transforms data assets into data service capabilities to serve enterprise business. Functionally, the data management platform is mainly divided into data foundation, data products, and data governance. The data source primarily consists of internal and external data inputs. The data foundation includes the operational data layer, the common dimension model layer, the data application layer, and the common dimension layer. The operational data layer is the source of data access; it's a copy of the raw data, forming an isolation layer between the business system and the data warehouse. When performing computational tasks on the data platform, calculations can be based on the data in the operational data layer, thus not burdening the business database. The common dimension model layer stores detailed fact data, dimension table data, and common indicator summary data. Detailed fact data and dimension table data are generally generated by processing data from the operational data layer, while common indicator summary data is generally generated by processing dimension table data and detailed fact data. Detailed factual data must be built, primarily handling dimension value transcoding, data deduplication, null value handling, and junk data cleanup. Data filtering is not allowed, data divergence is prohibited, and cross-layer and reverse calls are forbidden. If data is integrated within the same business scenario, granularity must be consistent, and the business scenario must be the same. The common summary layer is oriented towards the analysis object, building summary tables with common granularity based on the upper-layer indicator requirements. Processing process and business scenario-related data to form basic business analysis data is key to quickly supporting business needs and maximizing the value of data assets. It's important to note that dimension table data is shared throughout the entire data foundation. The data application layer can design data indicator and tag systems, processing data based on the common dimension model layer data. Designing the data application layer provides the final data support for data visualization applications.

[0076] It's important to note that financial data products provide one-stop, intelligent data services to businesses by building a complete data platform product matrix. Data development involves a complete set of data processing tools. Because data aggregated to the platform through the data aggregation module is unprocessed and essentially piled up in its raw state, it's difficult for businesses to use directly. Therefore, the data development module is needed to process the data, creating valuable data for business departments. Data management, built upon the data platform, is more technically oriented and harder for business personnel to understand. Data management presents data assets to business personnel in a way they can better comprehend. Examples include data asset platforms and master data management. Data application transforms data into a service capability, allowing it to participate in business operations and activate the entire data platform. The data service system is the core value of the data platform. Data governance is a strategic strategy, not a tactical method. From defining data strategies to developing implementation plans, it requires the participation and final decision-making of senior management. It spans the entire data lifecycle. Data standards management provides normative constraints to ensure the consistency and accuracy of data use and exchange both internally and externally, eliminating ambiguity through unified standards. Data security offers various data security strategies such as data encryption, anonymization, obfuscation, and account monitoring to ensure appropriate authentication, authorization, access, and auditing measures are in place during data use. The data platform's functional positioning is the abstraction, sharing, and reuse of data capabilities. It organizes the data and interfaces of big data platforms and data warehouses, enhancing data capabilities through data integration and improving overall business value through sharing. Unlike other data warehouses and platforms, this project establishes a data platform suitable for life insurance based on specific circumstances. At the data layer, various business domains are divided, with each layer having data standards and specific responsibilities. Tools and platforms are developed to abstract data products and provide services. The data platform is a sustainable project requiring continuous improvement driven by a high-level global strategy.

[0077] Understandably, the application can retrieve the corresponding execution list from a pre-defined database based on the target data. This execution list contains execution order information. Subsequently, the corresponding executor combination can be determined based on the execution order information. Then, the execution list can be processed according to the executor combination to obtain the data execution result.

[0078] like Figure 2 As shown, the data management platform can be created through steps S210 to S260:

[0079] Step S210: Obtain the original data requirement information;

[0080] Step S220: Perform data domain partitioning on the original data requirement information to obtain data domain partitioning information;

[0081] Step S230: Construct a bus matrix based on the data domain partitioning information and define statistical indicators based on the data domain partitioning information;

[0082] Step S240: Construct the consistency logical dimension and dimension attributes based on the bus matrix, and construct the consistency metric and consistency index based on the statistical indicators;

[0083] Step S250: Construct a detailed model based on the consistency logical dimension and dimension attributes, and construct a summary model based on the consistency measure and consistency index;

[0084] Step S260: Perform data business logic editing on the detailed model and the summary model to obtain the data management platform.

[0085] It should be noted that the process of creating a data management platform involves first obtaining the original data requirements information, then dividing the original data requirements information into data domains to obtain the data domain division information; next, constructing a bus matrix and defining statistical indicators based on the data domain division information; then, constructing consistent logical dimensions and dimension attributes based on the bus matrix, and constructing consistency measures and consistency indicators based on the statistical indicators; constructing detailed models based on the consistent logical dimensions and dimension attributes, and constructing summary models based on the consistency measures and consistency indicators; finally, editing the data business logic of the detailed models and summary models to obtain the data management platform.

[0086] Specifically, in the process of creating a data management platform for an insurance system, the first step is to obtain the original insurance data requirements information. Next, the original insurance data requirements information is divided into data domains to obtain insurance data domain division information. Then, an insurance bus matrix is ​​constructed based on the insurance data domain division information, and insurance statistical indicators are defined accordingly. Next, consistent logical dimensions and dimension attributes are constructed based on the insurance bus matrix, and consistent measures and indicators are constructed based on the insurance statistical indicators. Then, detailed models are constructed based on the consistent logical dimensions and dimension attributes, and summary models are constructed based on the consistent measures and indicators. Finally, the detailed models and summary models are processed with insurance data business logic to obtain the corresponding insurance data platform.

[0087] It's important to clarify that the functional positioning of a data platform is the abstraction, sharing, and reuse of data capabilities. It organizes the data and interfaces of big data platforms and data warehouses, enhancing data capabilities through data integration and improving overall business value through sharing. Unlike other data warehouses and platforms, this project establishes a data platform suitable for life insurance based on specific circumstances. At the data layer, various business domains are divided, with each layer having data specifications and specific responsibilities. Tools and platforms are developed to abstract data products and provide services. The data platform is a sustainable project that requires continuous improvement driven by a high-level global strategy.

[0088] In some embodiments, such as Figure 3 As shown, the data management platform includes multiple data applications, each carrying application scenario information. The above step S200 may include, but is not limited to, steps S270 to S280.

[0089] Step S270: Match the business type tagging information and business execution step information with the application scenario information to obtain the matching result;

[0090] Step S280: Select the corresponding data application from the data management platform as the target data application based on the matching results.

[0091] It should be noted that when selecting the corresponding target data application from the preset data management platform, the business type tag information and business execution step information are first matched with the application scenario information to obtain the matching result; then, the corresponding data application is selected from the data management platform as the target data application based on the matching result.

[0092] Understandably, matching the business type tagging information and business execution step information with the application scenario information yields the corresponding matching results. Based on these results, the appropriate data application can then be selected from the data management platform as the target data application. The data management platform can include multiple data applications, each applicable to different scenarios, such as insurance, banking, transaction, or order processing. For example, matching the insurance business type tagging information and insurance business execution step information with the application scenario information yields the matching results, allowing the selection of an insurance business data application as the target data application from the data management platform.

[0093] In some embodiments, such as Figure 4As shown, the target data application carries address tagging information, and the above step S300 may include, but is not limited to, steps S310 to S320.

[0094] Step S310: Analyze the address tag information to obtain the data storage address information;

[0095] Step S320: Extract the corresponding execution list from the database based on the data storage address information.

[0096] It should be noted that when an application needs to retrieve the corresponding execution list from a preset database based on target data, it can first analyze the address tag information to obtain the data storage address information; then, based on the data storage address information, the corresponding execution list can be extracted from the database.

[0097] It is worth noting that because the target data application carries address tag information, the data storage address information can be obtained by analyzing and processing the address tag information. Then, the corresponding execution list can be extracted from the database based on the data storage address information. Each execution list corresponds to a unique address information. Therefore, given the data storage address information, the corresponding execution list can be obtained conveniently and quickly.

[0098] In some embodiments, such as Figure 5 As shown, the actuator assembly includes multiple actuators, each of which carries execution attribute information. The above step S400 may include, but is not limited to, steps S410 to S430.

[0099] Step S410: Analyze and process the execution sequence information to obtain execution marker information;

[0100] Step S420: Compare the execution marker information with the execution attribute information to obtain comparison information;

[0101] Step S430: Select multiple actuators based on the comparison information, and combine the selected multiple actuators into an actuator combination.

[0102] It should be noted that in the process of determining the executor combination, the execution sequence information is first analyzed and processed to obtain the execution mark information. Then, the execution mark information and the execution attribute information are compared and processed to obtain the comparison information. Finally, multiple executors are selected based on the comparison information, and the selected multiple executors are combined into the corresponding executor combination.

[0103] It is understandable that each executor carries execution attribute information. Analyzing and processing the execution sequence information yields execution marker information. Comparing the execution marker information with the execution attribute information determines which executor is needed for each step. By comparing the information, multiple executors can be selected and combined into an executor combination. In the process of querying insurance bills, executors may include insurance record queries, insurance claim scope queries, and insurance recommendation queries, etc., and these executors can be combined into an executor combination.

[0104] In some embodiments, such as Figure 6 As shown, the execution list includes multiple stages of execution sub-information, and the above step S500 may include, but is not limited to, steps S510 to S520.

[0105] Step S510: Determine execution information based on the combination of multiple stage execution sub-information and executor;

[0106] Step S520: The executor combination performs execution processing on the execution information of multiple stage execution sub-information to obtain the data execution result.

[0107] It should be noted that during the execution of the execution list, the execution information can be determined based on the combination of multiple stage execution sub-information and executors. Then, by combining executors to process the multiple stage execution sub-information based on the execution information, the final data execution result can be obtained. Each stage execution sub-information corresponds to one executor; therefore, multiple stage execution sub-information correspond to executor combinations.

[0108] It is understandable that the corresponding execution information can be determined based on the execution sub-information of multiple stages and the combination of executors; then, the execution sub-information of multiple stages can be processed by the combination of executors based on the execution information determined above, and finally the corresponding data execution results can be obtained.

[0109] In some embodiments, such as Figure 7 As shown, after performing the above step S500, steps S610 and S620 may be included, but are not limited to.

[0110] Step S610: Add cache address tag information to the execution result;

[0111] Step S620: Store the execution result in a preset cache range according to the cache address marking information.

[0112] It should be noted that after obtaining the execution result, cache address marker information can be added to the execution result. Then, the execution result is stored in the preset cache range according to the cache address marker information. In this way, the execution result can be quickly transferred to the preset cache range for subsequent retrieval and processing.

[0113] In addition, such as Figure 8 As shown, one embodiment of this application also provides a data management device 10, including:

[0114] The first processing module 100 is used to obtain data requirement information from the business system, wherein the data requirement information includes business type marking information and business execution step information;

[0115] The second processing module 200 is used to select the corresponding target data application from the preset data management platform according to the business type marking information and business execution step information;

[0116] The third processing module 300 is used to obtain the corresponding execution list from the preset database according to the target data application, wherein the execution list carries execution order information;

[0117] The fourth processing module 400 is used to determine the corresponding executor combination based on the execution sequence information;

[0118] The fifth processing module 500 is used to process the execution list according to the executor combination to obtain the data execution result.

[0119] It should be noted that the data management process first involves acquiring data requirement information from the business system, including business type identification information and business execution step information. Next, based on the business type identification information and business execution step information, the corresponding target data application is selected from the preset data management platform. Then, based on the target data application, the corresponding execution list is retrieved from the preset database, where the execution list carries execution order information. Next, based on the execution order information, the corresponding executor combination is determined. Finally, the execution list can be processed according to the executor combination to obtain the data execution result. This technical solution effectively addresses different business needs through unified data management, significantly avoiding redundant data construction.

[0120] It should be noted that, based on the business type marking information and business execution step information, the corresponding target data application can be selected from the preset data management platform; the data management platform may include multiple target data applications. In some specific embodiments of this application, the corresponding target data application can be selected from the data management platform based on the business type marking information and business execution step information.

[0121] It's important to note that a data platform is a complete system situated between the underlying storage and computing platform and the upper-level data applications. It shields the underlying storage platform from the complexity of its computing technology, reduces the need for technical talent, and lowers the cost of data usage. By implementing layered data management, along with asset management and data services, it transforms data assets into data service capabilities to serve enterprise business. Functionally, the data management platform is mainly divided into data foundation, data products, and data governance. The data source primarily consists of internal and external data inputs. The data foundation includes the operational data layer, the common dimension model layer, the data application layer, and the common dimension layer. The operational data layer is the source of data access; it's a copy of the raw data, forming an isolation layer between the business system and the data warehouse. When performing computational tasks on the data platform, calculations can be based on the data in the operational data layer, thus not burdening the business database. The common dimension model layer stores detailed fact data, dimension table data, and common indicator summary data. Detailed fact data and dimension table data are generally generated by processing data from the operational data layer, while common indicator summary data is generally generated by processing dimension table data and detailed fact data. Detailed factual data must be built, primarily handling dimension value transcoding, data deduplication, null value handling, and junk data cleanup. Data filtering is not allowed, data divergence is prohibited, and cross-layer and reverse calls are forbidden. If data is integrated within the same business scenario, granularity must be consistent, and the business scenario must be the same. The common summary layer is oriented towards the analysis object, building summary tables with common granularity based on the upper-layer indicator requirements. Processing process and business scenario-related data to form basic business analysis data is key to quickly supporting business needs and maximizing the value of data assets. It's important to note that dimension table data is shared throughout the entire data foundation. The data application layer can design data indicator and tag systems, processing data based on the common dimension model layer data. Designing the data application layer provides the final data support for data visualization applications.

[0122] The specific implementation of the data management device 10 is basically the same as the specific embodiment of the data management method described above, and will not be repeated here.

[0123] In addition, such as Figure 9As shown, one embodiment of this application also provides an electronic device 700, which includes: a memory 720, a processor 710, and a computer program stored on the memory 720 and executable on the processor 710.

[0124] The processor 710 and memory 720 can be connected via a bus or other means.

[0125] The non-transitory software program and instructions required to implement the data management method of the above embodiments are stored in the memory 720. When executed by the processor 710, the data management method of each of the above embodiments is executed, for example, the method described above. Figure 1 Method steps S100 to S500 Figure 2 Method steps S210 to S260 in the text Figure 3 Method steps S270 to S280 in the text Figure 4 Method steps S310 to S320 in the text Figure 5 Method steps S410 to S430 in the text Figure 6 Method steps S510 to S520 and Figure 7 Method steps S610 to S620.

[0126] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0127] Furthermore, one embodiment of this application also provides a computer-readable storage medium storing computer-executable instructions that are executed by a processor 710 or a controller, for example, by a processor 710 in the above-described device embodiment, causing the processor 710 to perform the data management method described above, for example, performing the above-described... Figure 1 Method steps S100 to S500 Figure 2 Method steps S210 to S260 in the text Figure 3 Method steps S270 to S280 in the text Figure 4 Method steps S310 to S320 in the text Figure 5 Method steps S410 to S430 in the text Figure 6 Method steps S510 to S520 and Figure 7 Method steps S610 to S620.

[0128] The above embodiments can be used in combination, and modules with the same name in different embodiments may be the same or different.

[0129] The foregoing has described specific embodiments of this application; other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than those shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily have to follow the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0130] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and computer-readable storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0131] The apparatus, device, computer-readable storage medium and method provided in the embodiments of this application are corresponding. Therefore, the apparatus, device and non-volatile computer storage medium also have similar beneficial technical effects as the corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, device and computer storage medium will not be described again here.

[0132] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0133] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0134] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0135] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, in implementing the embodiments of this application, the functions of each unit can be implemented in one or more software and / or hardware.

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

[0137] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0138] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0139] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0140] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0141] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0142] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0143] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0144] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0145] The embodiments of this application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The embodiments of this application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can reside in local and remote computer storage media, including storage devices.

[0146] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0147] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

Claims

1. A data management method characterized by, The method comprises: obtaining data requirement information of a business system, wherein the data requirement information comprises business type marking information and business execution step information; selecting a corresponding target data application program from a preset data management platform according to the business type marking information and the business execution step information; obtaining a corresponding execution list from a preset database according to the target data application program, wherein the execution list carries execution sequence information; determining a corresponding executor combination according to the execution sequence information; performing execution processing on the execution list according to the executor combination to obtain a data execution result; wherein the data management platform is created by the following method: obtaining original data requirement information; performing data domain division processing on the original data requirement information to obtain data domain division information; constructing a bus matrix according to the data domain division information and explicitly statistical indicators according to the data domain division information; constructing consistency logical dimensions and dimension attributes according to the bus matrix and consistency metrics and consistency indicators according to the statistical indicators; constructing a detailed model according to the consistency logical dimensions and the dimension attributes and a summary model according to the consistency metrics and the consistency indicators; performing data business logic editing processing on the detailed model and the summary model to obtain the data management platform; The data management platform comprises a plurality of data application programs, each of which carries application scenario information, and the target data application program is selected from the preset data management platform according to the business type marking information and the business execution step information, which comprises: matching the business type marking information and the business execution step information with the application scenario information to obtain a matching result; selecting a corresponding data application program from the data management platform as the target data application program according to the matching result; The target data application program carries address marking information, and the execution list corresponding to the target data application program is obtained from the preset database according to the target data application program, which comprises: analyzing the address marking information to obtain data storage address information; extracting the execution list corresponding to the data storage address information from the database.

2. The data management method according to claim 1, characterized by, The executor combination comprises a plurality of executors, each of which carries execution attribute information, and the corresponding executor combination is determined according to the execution sequence information, which comprises: analyzing the execution sequence information to obtain execution marking information; comparing the execution marking information with the execution attribute information to obtain comparison information; selecting a plurality of executors according to the comparison information and combining the selected plurality of executors into the executor combination.

3. The data management method of claim 1, wherein, The execution list comprises a plurality of stage execution sub-information, and the data execution result is obtained by performing execution processing on the execution list according to the executor combination, which comprises: determining execution information according to a plurality of stage execution sub-information and the executor combination; The executor combination performs execution processing on the execution list according to the execution information to obtain a data execution result.

4. The data management method of claim 1, wherein, After the execution list is processed according to the executor combination to obtain the data execution result, the method further comprises: adding cache address marking information to the execution result; storing the execution result into a preset cache area according to the cache address marking information.

5. A data management apparatus characterized by comprising: The device comprises: a first processing module configured to acquire data requirement information of a business system, wherein the data requirement information comprises business type marking information and business execution step information; a second processing module configured to select a corresponding target data application program from a preset data management platform according to the business type marking information and the business execution step information; a third processing module configured to acquire a corresponding execution list from a preset database according to the target data application program, wherein the execution list carries execution sequence information; a fourth processing module configured to determine a corresponding executor combination according to the execution sequence information; a fifth processing module configured to perform execution processing on the execution list according to the executor combination to obtain a data execution result; The data management platform is created by the following methods: acquiring original data requirement information; performing data domain division processing on the original data requirement information to obtain data domain division information; constructing a bus matrix according to the data domain division information and explicitly counting indicators according to the data domain division information; constructing a consistency logical dimension and dimension attribute according to the bus matrix and constructing a consistency measure and consistency indicator according to the counting indicators; constructing a detailed model according to the consistency logical dimension and the dimension attribute and constructing a summary model according to the consistency measure and the consistency indicator; performing data business logic editing processing on the detailed model and the summary model to obtain the data management platform; The data management platform comprises a plurality of data application programs, each of which carries application scenario information, and the selection of the corresponding target data application program from the preset data management platform according to the business type marking information and the business execution step information comprises: matching the business type marking information and the business execution step information with the application scenario information to obtain a matching result; selecting a corresponding data application program from the data management platform as the target data application program according to the matching result; The target data application program carries address marking information, and the acquisition of the corresponding execution list from the preset database according to the target data application program comprises: analyzing the address marking information to obtain data storage address information; extracting the corresponding execution list from the database according to the data storage address information.

6. An electronic device comprising: A memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the data management method of any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium storing computer-executable instructions, characterized in that, The computer executable instructions are for performing the data management method of any one of claims 1 to 4.

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