Data expression method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a data expression method and device, equipment and a medium, and the method comprises the steps: storing common data of all transactions in a common data storage space in advance; and according to the generality intermediate field of the transaction, directly obtaining the generality data of the transaction from the generality data storage space, and meanwhile, according to the individuality intermediate field of the transaction, obtaining the individuality data of the transaction from pre-obtained source transaction data. And performing data processing on the common data and the personalized data to obtain transaction data, and encapsulating the transaction data in a transaction expression mode to obtain expression data of the transaction.

Description

Technical Field

[0001] This specification relates to the field of data applications, and more particularly, to a data expression method, apparatus, device, and storage medium in the field of data applications. Background Art

[0002] In the field of data applications, source data is expressed through multiple transactions. However, due to the different transaction expression requirements of each transaction, the focus on data expression is also different. Therefore, in order to meet the transaction expression requirements of each transaction, it is necessary to perform corresponding data processing on the source data according to the transaction expression requirements of each transaction. However, since there may be a lot of cross-reused intermediate logic in the transaction expression requirements of all transactions, when performing data processing on the source data, the same data processing is often performed on a certain requirement index multiple times. This method lacks sustainability, increases the computational amount of data processing, and reduces the data expression efficiency. Summary of the Invention

[0003] This specification provides a data expression method, apparatus, device, and storage medium. This method can pre-store the common data of all transactions in the common data storage space, separate data processing from data expression, achieve the sustainability of data processing, reduce the computational amount of data processing, and improve the data expression efficiency.

[0004] In a first aspect, an embodiment of this specification provides a data expression method, which includes: In response to a transaction expression request of a first transaction, determine the common intermediate fields and individual intermediate fields of the first transaction. The common intermediate fields are determined by matching the first requirement fields of the first transaction with the second requirement fields of a second transaction, and the second transaction is the remaining transactions in the transaction system other than the first transaction; Obtain the common data corresponding to the first transaction in the common data storage space based on the common intermediate fields. The common data storage space is used to store the common data corresponding to the common intermediate fields between the first transaction and the second transaction; Obtain the individual data corresponding to the first transaction from the pre-obtained source transaction data based on the individual intermediate fields; Perform data processing on the common data and the individual data according to the transaction expression requirements of the first transaction to obtain the transaction data of the first transaction; Package the transaction data according to the transaction expression method of the first transaction to obtain the expression data of the first transaction.

[0005] In a second aspect, an embodiment of this specification provides a data expression apparatus, which includes: An intermediate field determination unit, configured to determine a common intermediate field and a personalized intermediate field of a first transaction in response to a transaction expression request of the first transaction, where the common intermediate field is determined by matching a first requirement field of the first transaction with a second requirement field of a second transaction, and the second transaction is the remaining transactions in the transaction system except the first transaction; A common data acquisition unit, configured to acquire common data corresponding to the first transaction in a common data storage space based on the common intermediate field, where the common data storage space is used to store common data corresponding to the common intermediate field between the first transaction and the second transaction; A personalized data acquisition unit, configured to acquire personalized data corresponding to the first transaction from pre-acquired source transaction data based on the personalized intermediate field; A transaction data acquisition unit, configured to perform data processing on the common data and the personalized data based on the transaction expression requirement of the first transaction to obtain transaction data of the first transaction; A data expression unit, configured to encapsulate the transaction data based on the transaction expression mode of the first transaction to obtain expression data of the first transaction.

[0006] In a third aspect, an embodiment of the present specification provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the above method are implemented.

[0007] In a fourth aspect, an embodiment of the present specification provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0008] In a fifth aspect, an embodiment of the present specification provides a computer program product, including: a computer program. When the computer program is executed by a processor of a computer device, the processor can at least implement the method in the first aspect.

[0009] In the embodiment of the present specification, the common data of all transactions is stored in the common data storage space in advance. When a transaction expression request of a certain transaction is received, the common data of the transaction is directly acquired from the common data storage space according to the common intermediate field of the transaction, and at the same time, the personalized data of the transaction is acquired from the pre-acquired source transaction data according to the personalized intermediate field of the transaction. The common data and the personalized data are subjected to data processing to obtain transaction data, and the transaction data is encapsulated through the transaction expression mode to obtain the expression data of the transaction. This method stores the common data of all transactions in the common data storage space in advance. When expressing data for transactions, the data processing and the data expression are separated, so that some processed data can be continuously utilized by multiple transactions, realizing the sustainability of data processing, reducing the computational amount of data processing, and improving the data expression efficiency. Description of the Drawings

[0010] To more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of this specification. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0011] Figure 1 is a flowchart of a data expression method in a related art provided by an embodiment of this specification; Figure 2 is a system architecture diagram of a data expression method provided by an embodiment of this application; Figure 3 is a flowchart of a data expression method provided by an embodiment of this specification; Figure 4 is a flowchart of a common data acquisition method provided by an embodiment of this specification; Figure 5 is a flowchart of a personalized data acquisition method provided by an embodiment of this specification; Figure 6 is a structural diagram of a data expression device provided by an embodiment of this specification; Figure 7 is a structural diagram of a computer device provided by an embodiment of this specification. Detailed implementation manners

[0012] The following will clearly and completely describe the technical solutions in the embodiments of this specification with reference to the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only some embodiments of this specification, rather than all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope protected by this specification.

[0013] The data expression method provided by the embodiments of this specification is applicable to data application scenarios. The data application aims to achieve the conversion from data to transactions, and its core application scenarios include multiple industry scenarios such as fintech, e-commerce, healthcare, logistics supply chain, educational technology, and media entertainment.

[0014] Please refer to Figure 1 , Figure 1 is a flowchart of a data expression method in a related art provided by an embodiment of this specification. As Figure 1As shown in the figure, in the related art, a data application scenario includes multiple transactions, such as Transaction 1, Transaction 2, … Transaction n. When expressing data for each transaction, it is necessary to separately obtain the source transaction data of each transaction, that is, the raw data generated by each transaction without being processed, such as data like user identifier (Identifier, ID), transaction time, account login location, etc. According to the transaction expression requirements of each transaction, data processing is performed on its corresponding source transaction data to obtain the intermediate data required for obtaining its transaction data. Furthermore, data processing is performed on the intermediate data to obtain the transaction data corresponding to each transaction, and each transaction is expressed through the transaction data. Among them, the transaction data is determined according to the transaction expression requirements of each transaction, directly serves the front-end application, decision support, and transaction operations, and has highly customized and scenario-based characteristics. Therefore, the transaction data of each transaction is differential data.

[0015] However, since there may be a lot of cross-reused intermediate logic in the transaction expression requirements of each transaction, when performing data processing on the source transaction data, the same data processing is often performed multiple times for a certain requirement index. Therefore, there may be data shared by one transaction and at least one other transaction in the intermediate data of each transaction, that is, the intermediate data includes both the unique individual data of each transaction and the common data shared with at least one other transaction. Based on this, the transaction expression method in the related art lacks sustainability when obtaining intermediate data, increases the computational amount of data processing, and reduces the data expression efficiency.

[0016] Based on the above problems, the embodiments of this specification provide a data expression method. Please refer to Figure 2 , Figure 2 which is the system architecture diagram of a data expression method provided by the embodiments of this specification. As Figure 2 shown, the embodiments of this specification implement the data expression of each transaction in the data application scenario through a three-layer data model according to the data processing flow in the data expression method and in accordance with the hierarchical architecture of the basic layer - intermediate layer - polymorphic layer.

[0017] Among them, the basic layer is used to collect and save the source transaction data of the transaction system composed of all transactions in the data application scenario, and store the source transaction data in the form of source data tables according to the mapping relationship between the source transaction data in the basic layer. It can be understood that due to the diversity of transactions, each transaction generates at least one source data table, and multiple source data tables will be stored in the basic layer.

[0018] The middle layer is used to close the similar calibers of each transaction. After determining the common data in the intermediate data required for each transaction in the data application scenario, the data processing logics for each transaction to obtain the common data are unified. The middle layer calls the source transaction data required for each common data from the basic layer according to the unified data processing logic, performs corresponding data processing on the called source transaction data, obtains each common data, and saves each common data.

[0019] The polymorphic layer is used to represent transaction data and perform visual interaction. Since the transaction data of each transaction is differentiated data, when the polymorphic layer obtains transaction data, it calls the common data required for each transaction from the middle layer and calls the personalized data required for each transaction from the basic layer, performs data processing on the common data and the personalized data, and obtains differentiated transaction data. In order to maximize the transaction value, considering various factors such as the transaction characteristics, user requirements, cost-benefit, and system capabilities of each transaction, the transaction expression methods matching each transaction are determined, so that when the polymorphic layer represents transaction data, it performs data representation on each transaction based on the transaction expression methods and transaction data corresponding to each transaction. Among them, the transaction expression method is the method of providing visual interaction for each transaction, including methods such as Data Integration Report (DI) reports, data display views, broadcasts, user unified interaction platforms, and external interfaces.

[0020] Exemplarily, taking the e-commerce scenario as an example, assume that the e-commerce scenario includes security risk control transactions, business indicator transactions, and R & D transactions. In its basic layer, the source transaction data generated by the security risk control transactions, business indicator transactions, and R & D transactions is stored in the form of source data tables. There are multiple source data tables stored in the basic layer, and each source data table includes mutually mapped data, the named fields of the data in the code, the data type, and the data value. The source data tables of the e-commerce scenario include, but are not limited to, user behavior log tables, transaction flow tables, order detail tables, and system log tables. The user behavior log table is used to record the full-link behavior of users (login, payment, browsing), construct risk features through dimensions such as device fingerprint, IP, and geographical location, and includes data such as user ID, event type, device ID, event occurrence time, operation IP address, and account login location; the transaction flow table is used to associate user behavior with transaction data, and includes data such as user ID, merchant ID, order ID, transaction amount, transaction time, payment method, and whether it is refunded; the order detail table is used to split the order and product dimensions and support the calculation of business indicators, and includes data such as order ID, product ID, purchase quantity, product unit price, discount amount, order creation time, and order status (pending payment, completed, refunded, etc.); the system log table is used to collect full-link service logs and support system fault location and performance analysis, and includes data such as log ID, service name, log level, log content, log time, and server IP. Taking the user behavior log table as an example, please refer to Table 1. Table 1 is an example schematic diagram of a source data table in the basic layer provided by an embodiment of the present application.

[0021] Table 1

[0022] If there is common intermediate data in at least two of the security risk control affairs, business indicator affairs, and R & D affairs, then this common intermediate data is the common data in the e-commerce scenario. Taking the security risk control affairs and business indicator affairs as an example, the transaction expression requirements of the security risk control affairs are to ensure the transaction security, user privacy, and compliance of the e-commerce platform, and prevent risks such as fraud and data leakage. Based on the analysis of the transaction expression requirements of the security risk control affairs, the transaction data finally expressed by the security risk control affairs are data such as risk user IDs and risk transaction interception times. The intermediate data required to obtain the transaction data of the security risk control affairs includes data such as account login locations, account transaction frequencies, transaction amounts, and user portrait tags. The transaction expression requirements of the business indicator affairs are to optimize operation efficiency, user experience, and profitability. Based on the analysis of the transaction expression requirements of the business indicator affairs, the transaction data finally expressed by the business indicator affairs are data such as commodity profits, conversion rates, user repurchase rates, and marketing return rates. The intermediate data required to obtain the transaction data of the business indicator affairs includes user behavior data, user portrait tags, account transaction frequencies, transaction amounts, etc. User portrait tags are tags added according to the classification of users based on their consumption behaviors such as consumption levels and consumption habits. For example, tags such as high-consumption user tags, low-consumption user tags, and electronic product enthusiast tags. The account transaction frequency includes high frequency, medium frequency, and low frequency, which is determined according to the number of transactions made by the user daily / weekly / monthly / yearly. The transaction amount is the amount of each order in the user account. Therefore, the security risk control affairs and business indicator affairs have common data, and the data stored in the intermediate layer includes but is not limited to data such as user portrait tags, account transaction frequencies, and transaction amounts.

[0023] In the embodiments of this specification, the common data of all transactions is stored in the common data storage space in advance. When a transaction expression request for a certain transaction is received, the common data of this transaction is directly obtained from the common data storage space according to the common intermediate fields of the transaction, and at the same time, the personalized data of this transaction is obtained from the pre-obtained source transaction data according to the personalized intermediate fields of the transaction. The common data and personalized data are processed to obtain transaction data, and the transaction data is encapsulated through the transaction expression method to obtain the expression data of this transaction. This method stores the common data of all transactions in the common data storage space in advance. When expressing data for transactions, it separates data processing from data expression, enabling some processed data to be continuously utilized by multiple transactions, realizing the sustainability of data processing, reducing the computational amount of data processing, and improving the data expression efficiency.

[0024] Based on Figure 2 the system architecture diagram shown, the data expression method provided by the embodiments of this application will be introduced in detail below in conjunction with Figures 3 - 5 .

[0025] Please refer toFigure 3 , Figure 3 is a schematic flowchart of a data expression method provided by an embodiment of this specification. As Figure 3 shown, the method of the embodiment of this specification may include the following steps S102-step S110.

[0026] S102. In response to a transaction expression request of a first transaction, determine a common intermediate field and a personalized intermediate field of the first transaction; Specifically, when receiving a transaction expression request of the first transaction, in response to the transaction expression request of the first transaction, determine a common intermediate field and a personalized intermediate field of the first transaction. Among them, the transaction expression request is used to determine the transaction that currently needs to perform data expression. Among them, the common intermediate field is determined by matching a first requirement field of the first transaction with a second requirement field of a second transaction, and the personalized intermediate field is the remaining intermediate fields in the first requirement field except the common intermediate field. The second transaction is the remaining transactions in the transaction system except the first transaction. As can be seen from the above, the common intermediate field and the personalized intermediate field are determined before data expression of the transaction. Therefore, when receiving a transaction expression request of the first transaction, directly determine the common intermediate field and the personalized intermediate field of the first transaction.

[0027] Among them, a field is the naming of data in the code. Exemplarily, if the data is a user ID, then its field can be user-id. The requirement field includes a transaction data field of the transaction data finally expressed by the transaction, and an intermediate data field obtained by performing data lineage tracing on the transaction data field. After obtaining the intermediate data field, use the data dictionary technology to clarify the meaning of each intermediate data field, match the meanings of the intermediate data fields of all transactions, and determine the intermediate data fields with the same meaning as the common intermediate fields. The requirement field is obtained according to the transaction expression requirement of the transaction, and the transaction expression requirement is the goal of each transaction. The intermediate data is the data required before obtaining the transaction data. The intermediate data includes common data and personalized data. The intermediate data field is the naming of the intermediate data in the code, and the common intermediate field is the naming of the common data in the code. The common intermediate field and the personalized intermediate field of the transaction together constitute the intermediate data field of the transaction. It should be noted that if the intermediate data of the first transaction matches the intermediate data of at least one transaction in the second transaction, then the intermediate data is determined as the common intermediate data.

[0028] Exemplarily, assume that the application scenario of the embodiments of this specification is e-commerce. The first transaction is a security risk control transaction in e-commerce, and the second transactions are business metric transactions and R & D transactions in e-commerce. The security risk control transaction and the business metric transaction have common data, which includes but is not limited to data such as user portrait tags, account transaction frequencies, and transaction amounts. The common intermediate field is the naming in the code for user portrait tags, account transaction frequencies, and transaction amounts, such as user-data. The personalized intermediate data of the security risk control transaction includes but is not limited to the account login location, and the personalized intermediate field is the naming in the code for the account login location, such as login_location.

[0029] S104. Obtain the common data corresponding to the first transaction in the common data storage space based on the common intermediate field. Specifically, obtain the common data corresponding to the common intermediate field in the common data storage space based on the common intermediate field of the first transaction, and determine this common data as the common data of the first transaction. The common data storage space is used to store the common data corresponding to the common intermediate field between the first transaction and the second transaction, and the common data is the common intermediate data required to obtain the transaction data of the first transaction.

[0030] It should be noted that the common data includes static data and dynamic data. Static data is data that remains unchanged during the transaction life cycle, such as data like user IDs, product categories, etc.; dynamic data is data that changes in real time with user behavior, transaction status, or external environment, such as data like user account balances, order statuses, product inventories, user portrait tags, etc. The common data stored in the common data storage space includes not only static data but also dynamic data that is collected, processed, and synchronized frequently, so as to quickly obtain the common data from the common data storage space when receiving a transaction expression request and improve the data expression efficiency.

[0031] S106. Obtain the personalized data corresponding to the first transaction from the pre-obtained source transaction data based on the personalized intermediate field. Specifically, obtain the personalized data corresponding to the personalized intermediate field from the pre-obtained source transaction data based on the personalized intermediate field, and determine this personalized data as the personalized data of the first transaction. The personalized data is the personalized intermediate data required to obtain the transaction data of the first transaction. The pre-obtained source transaction data refers to the raw data generated by all transactions of the transaction system obtained through cross-domain collaboration capabilities before obtaining the common data and the personalized data, without any processing, and is used to directly reflect the events occurring in the transaction, such as raw data directly obtained like user IDs, account login times, account login locations, order transaction times, order transaction locations, etc. Similar to the common data, the personalized data also includes static data that remains unchanged for a long time and dynamic data that changes in real time.

[0032] Optionally, the embodiments of this specification may provide a personalized data storage space, which stores the static data in the personalized data. At the same time, based on the continuously updated source transaction data, the dynamic data in the personalized data is obtained in real time, so as to quickly obtain the personalized data from the personalized data storage space when a transaction expression request is received. The embodiments of this specification may also obtain the personalized data from the source transaction data after receiving the transaction expression request.

[0033] S108. Perform data processing on the common data and the personalized data based on the transaction expression requirements of the first transaction to obtain the transaction data of the first transaction; Specifically, the polymorphic layer calls the common data of the first transaction from the common data storage space, obtains the personalized data of the first transaction from the source transaction data, or calls the personalized data of the first transaction from the personalized data storage space. Perform data processing on the common data and the personalized data based on the transaction expression requirements of the first transaction to obtain the transaction data of the first transaction. The polymorphic layer is used to express the transaction data. The personalized data and the common data together form the intermediate data of the first transaction. By performing data processing on the intermediate data, the final transaction data is obtained. The intermediate data of the transaction can be the data directly obtained from the source transaction data, such as user ID, transaction time, account login location, etc., or the data obtained by performing data processing on the data in the source transaction data.

[0034] Exemplarily, in the security risk control transaction, a risk score is given to the user account according to the account login location, account transaction frequency, transaction amount, and user portrait label, and then the risk user ID is determined and the risk user ID is displayed. Among them, the user portrait label, account transaction frequency, and transaction amount are the common data in the intermediate data of the security risk control transaction. The user portrait label is the data for classifying users according to the consumption behaviors such as the consumption level and consumption habits of users in the source transaction data. The account transaction frequency includes high frequency, medium frequency, and low frequency, which is determined according to the number of transactions made by the user in a day / week / month / year. The transaction amount can be directly obtained from the source transaction data; the account login location is the personalized data in the intermediate data of the security risk control transaction and can be directly obtained from the source transaction data. Determining a risky account requires meeting multiple conditions. Taking the account of user A as an example, after obtaining the account login location, account transaction frequency, transaction amount, and user portrait label of user A, compare the current data of user A with the historical data. It is determined that the account login location of user A is a high-risk area, and the account transaction frequency of user A suddenly changes from low frequency to high frequency. At the same time, the user portrait label of user A indicates that user A is a low-consumption user, but the transaction amount of user A does not conform to the consumption habits of low-consumption users. Then it can be determined that the account of user A is a risky account.

[0035] S110, encapsulate transaction data based on the transaction expression mode of the first transaction to obtain the expression data of the first transaction.

[0036] Specifically, at the polymorphic layer, encapsulate transaction data based on the transaction expression mode of the first transaction to obtain the expression data of the first transaction, and perform data expression on the first transaction based on this expression data to display the transaction status for users or staff. The transaction expression mode is a way to provide visual interaction for each transaction, including methods such as DI reports, data display views, broadcasts, user unified interaction platforms, external interfaces, etc. Each transaction can correspond to at least one transaction expression mode.

[0037] Among them, the DI report is a standardized transaction report generated by integrating multiple transaction data, used to display transaction indicators such as commodity sales and user repurchase rates, including various types such as reporting state reports, inspection state reports, and operation and maintenance state reports. Among them, the reporting state report can be used as the transaction expression mode for business indicator transactions, used to present key transaction indicators to management, such as profit margins, user growth, etc. The reporting state report can be generated on a daily, monthly, or quarterly basis; the inspection state report can be used as the transaction expression mode for security risk control transactions, used to detect transaction process compliance and risk points; the operation and maintenance state report can be used as the transaction expression mode for R & D transactions, used to detect the system stability of the e-commerce platform. The data display view can dynamically present transaction data and can be used to display dynamic changing data such as the risk event trend and real-time interception statistics of security risk control transactions. The broadcast includes online broadcast and offline broadcast. The offline broadcast is usually a periodic report generated based on historical data or batch processing, used to summarize and analyze non-real-time transaction data. The offline broadcast can be used for the weekly / monthly sales summary report in business indicator transactions; the online broadcast is usually a push report generated based on real-time updated data streams. The online broadcast is usually used to detect and respond to immediate transactions, such as real-time interception statistics in security risk control transactions. The user unified interaction platform is a platform that integrates user services, user interfaces, and data analysis functions, such as a customer service system, user personal center, or self-service portal. This platform can provide data display for users using the e-commerce platform, facing user management transactions. Users can view data such as personal order status through the user unified interaction platform. The external interface is an external data service interface for third-party applications or partners to call. Third-party applications or partners can be platforms that generate data interactions with the e-commerce platform, such as payment platforms or logistics platforms.

[0038] It should be noted that the information (including but not limited to user device information, user personal information, user behavior information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the embodiments of this specification are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions. For example, the order information, interaction information, and user information involved in this specification are all obtained under full authorization.

[0039] In the embodiments of this specification, the common data of all transactions is pre-stored in the common data storage space. When a transaction expression request for a certain transaction is received, the common data of the transaction is directly obtained from the common data storage space according to the common intermediate field of the transaction, and at the same time, the personalized data of the transaction is obtained from the pre-obtained source transaction data according to the personalized intermediate field of the transaction. The common data and the personalized data are processed to obtain transaction data, and the transaction data is encapsulated through the transaction expression method to obtain the expression data of the transaction. This method pre-stores the common data of all transactions in the common data storage space. When expressing data for a transaction, it separates data processing from data expression, enabling some processed data to be continuously utilized by multiple transactions, realizing the sustainability of data processing, reducing the computational amount of data processing, and improving the data expression efficiency.

[0040] Please refer to Figure 4 , Figure 4 which is a schematic flow chart of a method for obtaining common data provided by the embodiments of this specification. As Figure 4 shown, the method of the embodiments of this specification may include the following steps S202 - step S214.

[0041] S202, determining the first requirement field of the first transaction based on the transaction expression requirement of the first transaction; Specifically, the first requirement field of the first transaction is determined based on the transaction expression requirement of the first transaction. In the transaction system of the current application scenario, there are multiple transactions, and the requirement field of each transaction can be determined based on its transaction expression requirement. The transaction expression requirement is the goal of the transaction, which is used to determine the transaction data that the transaction finally needs to express, and then determine the requirement field of the transaction. A field is the naming of data in the code. Exemplarily, if the data is a user identifier (Identifier, ID), its field can be user-id. The requirement field includes the transaction data field of the transaction data finally expressed by the transaction, and the intermediate data field obtained by performing data lineage tracing on the transaction data field. The intermediate data is the data required before obtaining the transaction data, and the intermediate data field is the naming of the intermediate data in the code. Data lineage tracing refers to tracking the entire life cycle process of data from the generation source to the final consumption, including the source, processing process, conversion logic, and usage of the data. Its core lies in recording and displaying the flow path and dependency relationship of data in different transactions and processes, so as to enhance data transparency, ensure data quality, support compliance auditing, and troubleshoot problems.

[0042] Exemplarily, assume that the application scenario of the embodiments of this specification is e-commerce, and the first transaction is the security risk control transaction in e-commerce. The transaction expression requirement of the security risk control transaction is to ensure the security of e-commerce platform transactions, user privacy, and compliance, and prevent risks such as fraud and data leakage. Based on the analysis of the transaction expression requirement of the security risk control transaction, the transaction data finally expressed by the security risk control transaction is data such as risky user ID and the number of risky transaction interceptions. Then, the transaction data fields in the first requirement field of the security risk control transaction include, but are not limited to, the naming of the risky user ID and the number of risky transaction interceptions in the code, such as risky_account_id. Taking the risky user ID as an example, performing lineage tracing on it, the intermediate data required to obtain the risky user ID includes data such as the account login location, account transaction frequency, transaction amount, and user portrait label. Then, the intermediate data fields in the first requirement field include, but are not limited to, the naming of the data such as the account login location, account transaction frequency, transaction amount, and user portrait label in the code, such as login_location, transaction_frequency, single_transaction_amount, user-data.

[0043] S204. Cross-compare the first requirement field with the second requirement field of the second transaction to determine the common intermediate fields in the first requirement field and the second requirement field, and the individual intermediate fields in the first requirement field; Specifically, the first requirement fields of the first transaction are cross-compared with the second requirement fields of the second transaction to determine the common intermediate fields in the first and second requirement fields, as well as the individual intermediate fields in the first requirement fields. Here, the second transaction refers to the remaining transactions in the transaction system other than the first transaction. The common intermediate fields are determined by matching the first requirement fields of the first transaction with the second requirement fields of the second transaction, and the individual intermediate fields are the remaining intermediate fields in the first requirement fields excluding the common intermediate fields. It should be noted that the common intermediate fields can be the common intermediate fields between at least one of the first transaction and the second transaction. Cross-comparison is a technique for identifying common fields in the requirement field sets of different transactions. Related techniques for implementing cross-comparison include metadata management, data mapping and matching, visualization analysis, etc. The specific process of cross-comparison is to use a metadata management platform to aggregate the requirement fields of all transactions. During the aggregation process, data dictionary techniques are used to clarify the meaning and data processing logic of each requirement field of each transaction, and then data mapping and matching are performed through pattern matching algorithms or semantic analysis algorithms. The meaning of all requirement fields of all transactions is compared and analyzed to identify the common intermediate fields, and finally all common intermediate fields are displayed through a visualization analysis tool. It should be noted that after determining the common intermediate fields, unified processing is performed on the common intermediate fields, that is, the naming of the common data is unified.

[0044] Exemplarily, in the e-commerce scenario, the first transaction is the security risk control transaction, and the second transactions are the business indicator transaction and the R & D transaction. The transaction expression requirements of the business indicator transaction are to optimize operation efficiency, user experience, and profitability. Based on the analysis of the transaction expression requirements of the business indicator transaction, the transaction data finally expressed by the business indicator transaction are data such as commodity profit, conversion rate, user repurchase rate, and marketing return rate. Then, the transaction data fields in the second requirement fields of the business indicator transaction include, but are not limited to, the naming of data such as commodity profit, conversion rate, user repurchase rate, and marketing return rate in the code. By performing data lineage tracing on the transaction data of the business indicator transaction, the intermediate data required for the transaction data of the business indicator transaction are found to include data such as user behavior data, user portrait tags, account transaction frequency, and transaction amount. Then, the intermediate data fields in the second requirement fields of the business indicator transaction include, but are not limited to, the naming of data including user behavior data, user portrait tags, account transaction frequency, and transaction amount in the code, such as user_behavior_log, user_profile_tags, purchase_frequency, single_tx_amount.

[0045] Cross - compare the intermediate data fields of security risk control transactions and those of business indicator transactions. Since the field naming methods of the two transactions are different, the data dictionary technology, pattern matching algorithm, and semantic analysis algorithm are combined. Based on the meanings of the intermediate data fields of the two transactions, the intermediate data fields are matched, and the common data of the two transactions are obtained as account transaction frequency, transaction amount, and user portrait labels. The naming of the common data in the unified code is standardized to obtain common intermediate fields. In the intermediate data of the security risk control transaction, all the data except the common data are personalized data. For example, the account login location is the personalized data of the security risk control transaction, and the personalized intermediate field can be "login_location".

[0046] S206. Obtain the common source fields corresponding to the common intermediate fields, and the common processing logics corresponding to the common source fields. Specifically, perform data lineage tracing on the common intermediate fields to obtain the source fields corresponding to the common intermediate fields and the initial processing logics corresponding to the source fields. Then, perform unified processing on the source fields and the initial processing logics respectively to obtain the common source fields corresponding to the source fields and the common processing logics corresponding to the initial processing logics. It should be noted that the intermediate data can be data directly obtained from the source transaction data, such as user ID, transaction time, account login location, etc., or data obtained by processing the data in the source transaction data.

[0047] Among them, the source field is the field corresponding to all the source data required to obtain the common data corresponding to the common intermediate field, and the initial processing logic is the data processing logic from the source data to the common intermediate data. Since the source fields and initial processing logics in different transactions are different, in the embodiments of this specification, after obtaining the source fields and initial processing logics, unified processing is performed on them respectively.

[0048] Exemplarily, perform data lineage tracing on the common data such as the account transaction frequency, transaction amount, and user portrait tags obtained in step S204 to obtain the source data. The account transaction frequency includes daily / weekly / monthly / yearly transaction frequencies, which are determined based on the number of transactions made by the user on a daily / weekly / monthly / yearly basis. Therefore, the source data corresponding to the account transaction frequency is the daily / weekly / monthly / yearly transaction counts of the user, and the source fields are daily_transaction_count, weekly_transaction_count, monthly_transaction_count, yearly_transaction_count. Combining with the naming of the source fields in the second transaction, perform unified processing on the source fields to obtain common source fields. Classify the account transaction frequency into high frequency, medium frequency, and low frequency according to the transaction count. Taking the daily transaction count as an example, its initial processing logic is as follows: "Every natural day, obtain the total transaction count of the user in the past preset number of days, calculate the daily average transaction count of the user based on the total transaction count and the preset number of days, and determine the daily average transaction count as the daily transaction count of the user. If the daily transaction count is greater than or equal to 30 times, determine that the account transaction frequency of the user is high frequency; if the daily transaction count is greater than or equal to 10 times and less than 30 times, determine that the account transaction frequency of the user is medium frequency; if the daily transaction count is less than 10 times, determine that the account transaction frequency of the user is low frequency." If the threshold values of the transaction counts set by the second transaction for high frequency, medium frequency, and low frequency are different, then combine the first transaction and the second transaction to determine the unique transaction count threshold for classifying high frequency, medium frequency, and low frequency, and unify the initial processing logic for determining the account transaction frequency based on the daily transaction count in the first transaction and the second transaction according to the unique transaction count threshold to obtain the common processing logic.

[0049] S208, obtain the source transaction data generated by the transaction system; Specifically, the basic data required for data representation of the transaction comes from the source transaction data generated by the transaction system. Therefore, before obtaining the common data and personalized data, first obtain the source transaction data generated by the transaction system and store the source transaction data in the basic layer data model. Through the cross-transaction collaboration ability, integrate all transactions in the transaction system, which can eliminate data islands, promote the centralized integration of the source transaction data of different transactions, reduce the blind spots from the perspective of a single transaction, and improve data accuracy. The source transaction data is the raw data generated by all transactions without any processing, such as the directly obtained raw data like user identification, account login time, account login location, transaction time, transaction location, etc.

[0050] S210, determine the common data corresponding to the common intermediate fields based on the common source data corresponding to the common source fields and the common processing logic; Specifically, the common source data corresponding to the common source fields is obtained from the source transaction data based on the common source fields, and the common source data is processed based on the common processing logic to obtain the common data corresponding to the common intermediate fields. The common source fields include all the fields of the source data before the common data corresponding to the common intermediate fields is obtained.

[0051] After the common data is obtained, the common data is stored in the common data storage space for the polymorphic layer to call. The common data storage space is used to store the common data corresponding to the common intermediate fields between the first transaction and the second transaction. It should be noted that the common data stored in the common data storage space includes static data and dynamic data. Static data is data that remains unchanged during the transaction life cycle, such as user ID, commodity category, etc.; dynamic data is data that changes in real time with user behavior, transaction status, or external environment, such as user account balance, order status, commodity inventory, user portrait label, etc. The common data stored in the common data storage space includes not only static data but also dynamically data that is frequently collected, processed, and synchronized, so as to quickly obtain the common data from the common data storage space when receiving a transaction expression request, improving the data expression efficiency.

[0052] Optionally, the common data storage space can be a funnel model, and the common data is hierarchically stored based on the funnel model. The specific process is to determine the first level where the common source field is located and the second level where the common intermediate field is located based on the common processing logic; the common source data corresponding to the common source field is stored in the first level, and the common data corresponding to the common intermediate field is stored in the second level. Among them, the first level includes at least one level. Taking the common data of the account transaction frequency in the security risk control transaction as an example, first obtain the user ID and transaction records from the source transaction data. The transaction records include original data such as transaction time, transaction amount, and transaction status. The user ID and transaction records are saved in the basic data layer of the first level. Aggregate the transaction time in the user ID and transaction records, and count the daily transaction times of the user. The user ID, date, and the transaction times corresponding to each date are saved in the daily transaction aggregation layer of the first level. Every natural day, aggregate the user ID, the dates of the past preset number of days, and the transaction times corresponding to each date, count the total transaction times of the user in the past preset number of days, and calculate the daily average transaction times according to the preset number of days and the total transaction times. The user ID, total transaction times, and daily average transaction times are saved in the total transaction aggregation layer of the first level. According to the daily average transaction times, determine the account transaction frequency of the user, and save the user ID and account transaction frequency in the frequency classification layer of the first level. Regularly update the account transaction frequency of the user, and save the user ID, account transaction frequency, historical transaction frequency, and update time in the second level, where the historical transaction frequency is the transaction frequency before the current account transaction frequency of the user is updated.

[0053] S212, in response to the transaction expression request of the first transaction, determine the common intermediate field and the individual intermediate field of the first transaction based on the transaction expression requirements of the first transaction; S214, obtain the common data corresponding to the first transaction from the common data storage space based on the common intermediate field.

[0054] Specifically, pre-obtain the common data of the first transaction and store the common data in the common data storage space. When receiving the transaction expression request of the first transaction, the common data corresponding to the first transaction can be directly called from the common data storage space based on the common intermediate field of the first transaction, so as to obtain the transaction data of the first transaction expressed finally according to the common data.

[0055] It should be noted that the information involved in the embodiments of this specification (including but not limited to user equipment information, user personal information, user behavior information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions. For example, the order information, interaction information, and user information involved in this specification are all obtained under full authorization.

[0056] In the embodiments of this specification, the demand fields of each transaction are determined through transaction expression requirements, and the demand fields of all transactions are cross-compared to determine the common intermediate fields between at least two transactions among all transactions. By performing data lineage tracing on the common intermediate fields, the common source fields and the corresponding common processing logics of the common source fields are obtained. Furthermore, the common source data can be obtained from the pre-acquired source transaction data through the common source fields, and the common source data is processed based on the common processing logics to obtain the common data of each transaction and at least one of the remaining transactions, and the common data is stored in the common data storage space. When expressing data for a transaction, the common data corresponding to the transaction is directly obtained from the common data storage space. In the embodiments of this specification, the common intermediate fields of all transactions are determined in advance, and then unified data processing is performed to obtain the common data of each transaction and at least one of the remaining transactions, without repeatedly calculating the common data of each transaction and at least one of the remaining transactions. Through the unified common source fields and common processing logics, the sustainable use of common data is realized, and the computational amount of data processing is reduced. The common data is stored in a separate common data storage space. When expressing data for a transaction, the common data of the transaction is directly called from the common data storage space, which improves the efficiency of data expression. At the same time, the responsibility boundaries in the data expression system are clarified through the common data storage space, ensuring the independence and low coupling of the code, and improving the maintainability and reusability of the entire system.

[0057] Please refer to Figure 5 , Figure 5 is a schematic flowchart of a method for obtaining personalized data provided by the embodiments of this specification. As Figure 5 shown, the method of the embodiments of this specification may include the following steps S302 - step S314.

[0058] S302, determining the first demand field of the first transaction based on the transaction expression requirement of the first transaction; For the specific process, please refer to step S202, which will not be elaborated here.

[0059] S304. Cross - compare the first requirement field with the second requirement field of the second transaction to determine the common intermediate fields in the first and second requirement fields, and the individual intermediate fields in the first requirement field; For the specific process, please refer to step S204 and will not be elaborated here.

[0060] S306. Obtain the individual source fields corresponding to the individual intermediate fields, and the individual processing logics corresponding to the individual source fields; Specifically, perform data lineage tracing on the individual intermediate fields to obtain the individual source fields corresponding to the individual intermediate fields, and the individual processing logics corresponding to the individual source fields. Among them, the individual source fields are the fields corresponding to all individual source data required to obtain the individual intermediate data corresponding to the individual intermediate fields, and the individual processing logic is the data processing logic from the individual source data to the individual intermediate data. It should be noted that the intermediate data can be data directly obtained from the source transaction data, such as user ID, transaction time, account login location, etc., or data obtained by processing the data in the source transaction data.

[0061] Exemplarily, in the e - commerce scenario, the intermediate data of the security risk control transaction includes but is not limited to data such as account login location, account transaction frequency, transaction amount, user portrait tags, etc. Among them, the account transaction frequency, transaction amount, and user portrait tags are common data, and the account login location is individual data. Perform data lineage tracing on the account login location, and it is found that the account login location is data that can be directly obtained from the source transaction data. Therefore, the individual source data of the security risk control transaction includes but is not limited to the account login location, the individual source fields include but are not limited to the naming of the account login location in the code, such as login_location, and its individual processing logic can be data processing methods such as data cleaning.

[0062] S308. Obtain the source transaction data generated by the transaction system; For the specific process, please refer to step S208 and will not be elaborated here.

[0063] S310. In response to the transaction expression request of the first transaction, determine the common intermediate fields and individual intermediate fields of the first transaction based on the transaction expression requirements of the first transaction; S312. Based on the individual source fields corresponding to the individual intermediate fields, obtain the individual source data corresponding to the individual source fields in the pre - obtained source transaction data; S314. Perform data processing on the individual source data based on the individual processing logic to obtain the individual data corresponding to the first transaction.

[0064] Specifically, based on the personality source fields, obtain the personality source data corresponding to the personality source fields in the source transaction data, and perform data processing on the personality source data based on the personality processing logic to obtain the personality data corresponding to the first transaction. The personality source fields include all the source data fields before obtaining the personality data corresponding to the personality intermediate fields.

[0065] It should be noted that the information (including but not limited to user device information, user personal information, user behavior information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the embodiments of this specification are all authorized by users or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions. For example, the order information, interaction information, and user information involved in this specification are all obtained under sufficient authorization.

[0066] In the embodiments of this specification, the requirement fields of each transaction are determined by expressing requirements through transactions, and cross-comparison is performed on the requirement fields of all transactions to determine the personality intermediate fields of each transaction. By performing data lineage tracking on the personality intermediate fields, the personality source fields and the corresponding personality processing logic are obtained. When a transaction expression request is received, the personality source data corresponding to the personality source fields is obtained from the pre-obtained source transaction data, and data processing is performed on the personality source data based on the personality processing logic to obtain the personality data. The personality data is directly obtained from the source transaction data, and the acquisition channels of the personality data and the common data are separated, improving the flexibility of data processing.

[0067] Based on Figure 2 the system architecture diagram, the content display device provided in the embodiments of this specification will be introduced in detail below in conjunction with Figure 6 . It should be noted that Figure 6 the data expression device in Figures 3 - 5 is used to execute the method of the embodiment shown in this application Figures 3 - 5 . For the sake of convenience of description, only the parts related to the embodiments of this specification are shown. For the specific technical details not disclosed, please refer to the embodiments shown in this application Figures 3 - 5 .

[0068] Please refer to Figure 6 , Figure 6 which is a schematic structural diagram of a data expression device provided in the embodiments of this specification. As Figure 6 shown, the data expression device 1 in the embodiments of this specification may include: an intermediate field determination unit 11, a common data acquisition unit 12, a personality data acquisition unit 13, a transaction data acquisition unit 14, and a data expression unit 15.

[0069] An intermediate field determination unit 11, configured to determine a common intermediate field and a personalized intermediate field of the first transaction in response to a transaction expression request of the first transaction, where the common intermediate field is determined by matching a first requirement field of the first transaction with a second requirement field of a second transaction, and the second transaction is the remaining transactions in the transaction system except the first transaction; A common data acquisition unit 12, configured to acquire common data corresponding to the first transaction in a common data storage space based on the common intermediate field, where the common data storage space is used to store common data corresponding to the common intermediate field between the first transaction and the second transaction; A personalized data acquisition unit 13, configured to acquire personalized data corresponding to the first transaction from pre-acquired source transaction data based on the personalized intermediate field; A transaction data acquisition unit 14, configured to perform data processing on the common data and the personalized data based on the transaction expression requirement of the first transaction to obtain transaction data of the first transaction; A data expression unit 15, configured to encapsulate the transaction data based on the transaction expression mode of the first transaction to obtain expression data of the first transaction.

[0070] Optionally, the data expression device 1 is specifically configured to determine a first requirement field of the first transaction based on the transaction expression requirement of the first transaction; Perform cross-comparison between the first requirement field and a second requirement field of the second transaction to determine a common intermediate field in the first requirement field and the second requirement field, and a personalized intermediate field in the first requirement field; Obtain a common source field corresponding to the common intermediate field, and a common processing logic corresponding to the common source field; Based on the common source data corresponding to the common source field and the common processing logic, determine the common data corresponding to the common intermediate field.

[0071] Optionally, the data expression device 1 is specifically configured to perform data lineage tracing on the common intermediate field to obtain a source field corresponding to the common intermediate field, and an initial processing logic corresponding to the source field; Perform uniform processing on the source field and the initial processing logic respectively to obtain a common source field corresponding to the source field, and a common processing logic corresponding to the initial processing logic.

[0072] Optionally, the data expression device 1 is specifically configured to obtain source transaction data generated by the transaction system.

[0073] Optionally, the data expression device 1 is specifically configured to acquire common source data corresponding to the common source field from the source transaction data based on the common source field; Perform data processing on the common source data based on the common processing logic to obtain common data corresponding to the common intermediate field.

[0074] Optionally, the data presentation device 1 is specifically configured to determine the first level where the common source field is located and the second level where the common intermediate field is located based on the common processing logic; Store the common source data corresponding to the common source field in the first level, and store the common data corresponding to the common intermediate field in the second level.

[0075] Optionally, the data presentation device 1 is specifically configured to obtain the personalized source field corresponding to the personalized intermediate field, and the personalized processing logic corresponding to the personalized source field.

[0076] Optionally, the personalized data acquisition unit 13 is specifically configured to obtain the personalized source data corresponding to the personalized source field in the pre-acquired source transaction data based on the personalized source field corresponding to the personalized intermediate field; Perform data processing on the personalized source data based on the personalized processing logic to obtain the personalized data corresponding to the first transaction.

[0077] In the embodiments of this specification, first determine the common intermediate fields of all transactions in advance, and then perform unified data processing to obtain the common data of each transaction and at least one of the remaining transactions. There is no need to calculate the common data of each transaction and at least one of the remaining transactions multiple times. Through the unified common source fields and common processing logic, the sustainable use of common data is realized, and the computational complexity of data processing is reduced. Store the common data in a separate common data storage space. When presenting data for a transaction, directly call the common data of this transaction from the common data storage space, separate data processing from data presentation, so that some processed data can be continuously utilized by multiple transactions, realizing the sustainability of data processing, reducing the computational complexity of data processing, and improving data presentation efficiency. Obtain personalized data from the source transaction data, separate the acquisition channels of personalized data from those of common data, and improve the flexibility of data processing. At the same time, the responsibility boundaries in the data presentation system are clarified through the basic layer data model, common data storage space, and polymorphic layer, ensuring the independence and low coupling of the code, and improving the maintainability and reusability of the entire system.

[0078] It should be noted that when the data presentation device provided in the above embodiments executes the data presentation method, only the division of the above functional modules is used for illustration. In practical applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the data presentation device provided in the above embodiments and the embodiments of the data presentation method belong to the same concept. The implementation process is detailed in the method embodiments and will not be repeated here.

[0079] The serial numbers of the embodiments in the present specification are only for description and do not represent the superiority or inferiority of the embodiments. In some cases, the actions or steps recited in the claims may be executed in a different order from those in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0080] Please refer to Figure 7 , Figure 7 which is a schematic structural diagram of a computer device provided by an embodiment of the present specification.

[0081] Exemplarily, as Figure 7 shown, the computer device 700 includes: a processor 701 and a memory 702, wherein the processor 701 is electrically connected to the memory 702.

[0082] The processor 701 is the control center of the computer device 700 and may include one or more processing cores. The processor 701 connects various parts of the entire computer device through various interfaces and lines, and by running or calling the computer programs stored in the memory 702 and the data stored in the memory 702, executes various functions of the computer device and processes data, thereby overall controlling the computer device 700. Optionally, the processor 701 may be implemented in at least one hardware form of digital signal processing (DSP), field programmable gate array (FPGA), or programmable logic array (PLA). The processor 701 may integrate one or a combination of several of a CPU, a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user pages, and application programs, etc.; the GPU is responsible for rendering and drawing the display content; the modem is used to process wireless communication. It can be understood that the above modem may not be integrated into the processor 701 and may be implemented separately through a communication chip.

[0083] The memory 702 can be used to store software programs and modules. The processor 701 executes various functional applications and data processing by running the computer programs and modules stored in the memory 702. The memory 702 mainly includes a program storage area and a data storage area. Among them, the program storage area can store the operating system, computer programs required for at least one function, etc.; the data storage area can store data created according to the use of the computer device 700.

[0084] In addition, the memory 702 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 702 may further include a memory controller to provide the processor 701 with access to the memory 702.

[0085] In the first feasible implementation manner of the embodiments of this specification, the processor 701 in the computer device 700 loads the instructions corresponding to the processes of one or more computer programs into the memory 702 according to the following steps, and the processor 701 runs the computer programs stored in the memory 702 to implement various functions as follows: In response to a transaction expression request of a first transaction, determine a common intermediate field and a personalized intermediate field of the first transaction, where the common intermediate field is determined by matching a first requirement field of the first transaction with a second requirement field of a second transaction, and the second transaction is the remaining transactions in the transaction system other than the first transaction; Obtain the common data corresponding to the first transaction in the common data storage space based on the common intermediate field, where the common data storage space is used to store the common data corresponding to the common intermediate field between the first transaction and the second transaction; Obtain the personalized data corresponding to the first transaction from the pre-acquired source transaction data based on the personalized intermediate field; Perform data processing on the common data and the personalized data based on the transaction expression requirements of the first transaction to obtain the transaction data of the first transaction; Encapsulate the transaction data based on the transaction expression mode of the first transaction to obtain the expression data of the first transaction.

[0086] Optionally, before the processor 701 executes to determine the common intermediate field and the personalized intermediate field of the first transaction in response to the transaction expression request of the first transaction, the processor 701 also executes: Determine the first requirement field of the first transaction based on the transaction expression requirements of the first transaction; Perform cross-comparison between the first requirement field and the second requirement field of the second transaction to determine the common intermediate field in the first requirement field and the second requirement field, and the personalized intermediate field in the first requirement field; Obtain the common source field corresponding to the common intermediate field, and the common processing logic corresponding to the common source field; Determine the common data corresponding to the common intermediate field based on the common source data corresponding to the common source field and the common processing logic.

[0087] Optionally, when the processor 701 executes to obtain the common source field corresponding to the common intermediate field and the common processing logic corresponding to the common source field, it specifically executes: Perform data lineage tracing on the common intermediate field to obtain the source field corresponding to the common intermediate field and the initial processing logic corresponding to the source field; Perform unified processing on the source field and the initial processing logic respectively to obtain the common source field corresponding to the source field and the common processing logic corresponding to the initial processing logic.

[0088] Optionally, after the processor 701 executes to cross-compare the first requirement field with the second requirement field of the second transaction to determine the common intermediate field in the first requirement field and the second requirement field and the individual intermediate field in the first requirement field, it also executes: Obtain the source transaction data generated by the transaction system.

[0089] Optionally, when the processor 701 executes to determine the common data corresponding to the common intermediate field based on the common source data corresponding to the common source field and the common processing logic, it specifically executes: Obtain the common source data corresponding to the common source field from the source transaction data based on the common source field; Perform data processing on the common source data based on the common processing logic to obtain the common data corresponding to the common intermediate field.

[0090] Optionally, the processor 701 also executes: Determine the first level where the common source field is located and the second level where the common intermediate field is located based on the common processing logic; Store the common source data corresponding to the common source field in the first level and store the common data corresponding to the common intermediate field in the second level.

[0091] Optionally, after the processor 701 executes to cross-compare the first requirement field with the second requirement field of the second transaction to determine the common intermediate field in the first requirement field and the second requirement field and the individual intermediate field in the first requirement field, it also executes: Obtain the individual source field corresponding to the individual intermediate field and the individual processing logic corresponding to the individual source field.

[0092] Optionally, when the processor 701 executes to obtain the individual data corresponding to the first transaction from the pre-obtained source transaction data based on the individual intermediate field, it specifically executes: Obtain the individual source data corresponding to the individual source field from the pre-obtained source transaction data based on the individual source field corresponding to the individual intermediate field; Perform data processing on the individual source data based on the individual processing logic to obtain the individual data corresponding to the first transaction.

[0093] In the embodiments of this specification, the common intermediate fields of all transactions are determined in advance, and then data processing is performed uniformly to obtain the common data of each transaction and at least one of the remaining transactions. There is no need to calculate the common data of each transaction and at least one of the remaining transactions multiple times. Through the unified common source fields and common processing logic, the sustainable use of common data is realized, and the computational amount of data processing is reduced. The common data is stored in a separate common data storage space. When expressing data for a transaction, the common data of the transaction is directly called from the common data storage space, separating data processing from data expression, enabling some processed data to be continuously utilized by multiple transactions, realizing the sustainability of data processing, reducing the computational amount of data processing, and improving data expression efficiency. The personalized data is obtained from the source transaction data, and the acquisition channels of the personalized data and the common data are separated, improving the flexibility of data processing. At the same time, the responsibility boundaries in the data expression system are clarified through the basic layer data model, the common data storage space, and the polymorphic layer, ensuring the independence and low coupling of the code, and improving the maintainability and reusability of the entire system.

[0094] It should be understood that the device provided in the embodiments of this specification is used to execute the above-mentioned data expression method, so the same effects as the above implementation method can be achieved.

[0095] In the case of adopting an integrated unit, the device may include a processing module and a storage module. Among them, when the device is applied to a computer device, the processing module can be used to control and manage the actions of the computer device. The storage module can be used to support the computer device in executing relevant program codes, etc.

[0096] Among them, the processing module can be a processor or a controller, which can implement or execute various exemplary logical blocks, modules, and circuits described in combination with the disclosure of this application. The processor can also be a combination that realizes computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module can be a memory.

[0097] In addition, the device provided in the embodiments of this specification can specifically be a chip, a component, or a module. The chip may include a connected processor and a memory; among them, the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute a data expression method provided in the above embodiments.

[0098] The embodiments of this specification also provide a computer-readable storage medium, in which computer program code is stored. When the computer program code runs on a computer, the computer is caused to execute the above-related method steps to implement a data expression method provided in the above embodiments.

[0099] This embodiment also provides a computer program product. When the computer program product runs on a computer, the computer is caused to execute the above-related steps to implement a data expression method provided in the above embodiments.

[0100] Among them, the device, computer-readable storage medium, computer program product or chip provided in this embodiment are all used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be elaborated here.

[0101] Through the description of the above embodiments, those skilled in the art can understand that for the convenience and simplicity of description, only the above division of each functional module is used as an example. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.

[0102] In the embodiments provided in this application, it should be understood that the disclosed device and method can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0103] The above content is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A data expression method, the method comprising: Responding to a transaction expression request of a first transaction, determining a common intermediate field and a personalized intermediate field of the first transaction, where the common intermediate field is determined based on a matching of a first requirement field of the first transaction and a second requirement field of a second transaction, and the second transaction is the remaining transactions in the transaction system other than the first transaction; Obtaining, based on the common intermediate field, common data corresponding to the first transaction in a common data storage space, where the common data storage space is used to store common data corresponding to the common intermediate field between the first transaction and the second transaction; Obtaining, based on the personalized intermediate field, personalized data corresponding to the first transaction from pre-obtained source transaction data; Performing data processing on the common data and the personalized data based on the transaction expression requirement of the first transaction to obtain transaction data of the first transaction; Encapsulating the transaction data based on the transaction expression mode of the first transaction to obtain expression data of the first transaction.

2. The method according to claim 1, before responding to the transaction expression request of the first transaction and determining the common intermediate field and the personalized intermediate field of the first transaction, further comprising: Determining a first requirement field of the first transaction based on the transaction expression requirement of the first transaction; Performing cross-comparison on the first requirement field and a second requirement field of a second transaction to determine a common intermediate field in the first requirement field and the second requirement field, and a personalized intermediate field in the first requirement field; Obtaining a common source field corresponding to the common intermediate field, and a common processing logic corresponding to the common source field; Determining, based on the common source data corresponding to the common source field and the common processing logic, common data corresponding to the common intermediate field.

3. The method according to claim 2, the obtaining the common source field corresponding to the common intermediate field, and the common processing logic corresponding to the common source field, includes: Performing data lineage tracing on the common intermediate field to obtain a source field corresponding to the common intermediate field, and an initial processing logic corresponding to the source field; Performing uniform processing on the source field and the initial processing logic respectively to obtain a common source field corresponding to the source field, and a common processing logic corresponding to the initial processing logic.

4. The method according to claim 2, after performing cross-comparison on the first requirement field and the second requirement field of the second transaction to determine the common intermediate field in the first requirement field and the second requirement field, and the personalized intermediate field in the first requirement field, further comprising: Obtaining source transaction data generated by the transaction system.

5. The method according to claim 4, the determining, based on the common source data corresponding to the common source field and the common processing logic, common data corresponding to the common intermediate field, includes: Obtaining, based on the common source field, common source data corresponding to the common source field in the source transaction data; Data processing is performed on the common source data based on the common processing logic to obtain the common data corresponding to the common intermediate field.

6. The method according to claim 2, the method further comprising: Determining a first level where the common source field is located and a second level where the common intermediate field is located based on the common processing logic; Storing the common source data corresponding to the common source field in the first level and storing the common data corresponding to the common intermediate field in the second level.

7. The method according to claim 2, after cross-comparing the first requirement field with the second requirement field of the second transaction to determine the common intermediate field in the first requirement field and the second requirement field, and the individual intermediate field in the first requirement field, further comprising: Obtaining the individual source field corresponding to the individual intermediate field, and the individual processing logic corresponding to the individual source field.

8. The method according to claim 7, the obtaining the individual data corresponding to the first transaction from the pre-obtained source transaction data based on the individual intermediate field includes: Obtaining the individual source data corresponding to the individual source field from the pre-obtained source transaction data based on the individual source field corresponding to the individual intermediate field; Performing data processing on the individual source data based on the individual processing logic to obtain the individual data corresponding to the first transaction.

9. A data expression device, the device comprising: An intermediate field determination unit, configured to, in response to a transaction expression request of a first transaction, determine a common intermediate field and an individual intermediate field of the first transaction, where the common intermediate field is determined by matching the first requirement field of the first transaction with the second requirement field of a second transaction, and the second transaction is the remaining transactions in the transaction system except the first transaction; A common data acquisition unit, configured to acquire the common data corresponding to the first transaction from a common data storage space based on the common intermediate field, where the common data storage space is used to store the common data corresponding to the common intermediate field between the first transaction and the second transaction; An individual data acquisition unit, configured to acquire the individual data corresponding to the first transaction from the pre-obtained source transaction data based on the individual intermediate field; A transaction data acquisition unit, configured to perform data processing on the common data and the individual data based on the transaction expression requirement of the first transaction to obtain the transaction data of the first transaction; A data expression unit, configured to encapsulate the transaction data based on the transaction expression mode of the first transaction to obtain the expression data of the first transaction.

10. A computer device, comprising: A processor and a memory; Wherein the memory stores a computer program, and the computer program is adapted to be loaded and executed by the processor to perform the steps of the method according to any one of claims 1 to 8.

11. A storage medium, the storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

12. A computer program product, comprising: A computer program which, when executed by a processor of a computer device, causes the processor to perform the steps of the method according to any one of claims 1 to 8.

Images