Transaction data processing method and device, equipment and storage medium

Abstract

The invention provides a transaction data processing method and device, equipment and a storage medium. Relates to the technical field of data processing. The method comprises the following steps: acquiring a transaction effect statistical request, generating a query instruction based on a preset specified condition, sending the query instruction to a data warehouse to enable the data warehouse to screen stored transaction data, and receiving all first transaction data meeting the specified condition returned by the data warehouse, and according to the transaction time and the transaction place of the first transaction data, determining a transaction channel corresponding to the first transaction data, and based on the transaction channel of each piece of first transaction data, carrying out classification and statistics on the first transaction data so as to obtain a transaction effect corresponding to each transaction channel. According to the method provided by the invention, the actual transaction channel of each piece of first transaction data can be clearly divided, and statistics of the effect corresponding to each transaction channel is facilitated, so that the statistical efficiency of the effect corresponding to each transaction channel is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a transaction data processing method, device, equipment and storage medium. Background Art

[0002] The transaction performance statistics of various banking businesses are usually based on the transaction channel dimension, which is usually divided into branch transaction channels and online transaction channels. As the platform operation capabilities of online transaction channels continue to improve, online transaction channels have become the product marketing shelves of banks.

[0003] Transactions completed through online marketing tools carry staff coding information and should actually be attributed to the effectiveness of branch transaction channels. However, according to the current method of statistically analyzing the effectiveness of transaction channels, they will be attributed to the transaction effectiveness of online transaction channels. As a result, it is impossible to accurately define whether the effectiveness of a single product transaction completed on the online transaction channel was completed independently by the user or with the intervention of staff. Manual secondary processing is required, resulting in low statistical efficiency for the effectiveness of each transaction channel. Summary of the invention

[0004] The present application provides a transaction data processing method, device, equipment and storage medium to improve the statistical efficiency of the effectiveness of each transaction channel.

[0005] In a first aspect, the present application provides a transaction data processing method, comprising:

[0006] Obtaining a transaction performance statistics request, wherein the transaction performance statistics request includes one or more preset specified conditions;

[0007] Generate a query instruction based on the preset specified conditions, and send the query instruction to the data warehouse, so that the data warehouse screens the stored transaction data to obtain first transaction data, wherein the first transaction data meets all the preset specified conditions, and the first transaction data includes transaction time and transaction location;

[0008] receiving all first transaction data returned by the data warehouse, and determining, according to the transaction time and transaction location of the first transaction data, a transaction channel corresponding to the first transaction data, wherein the transaction channel includes an outlet transaction channel and an online transaction channel;

[0009] Based on the transaction channels of each first transaction data, the first transaction data are classified and then counted to obtain the transaction results corresponding to each transaction channel, wherein the transaction results represent the transaction data volume.

[0010] In a possible design, before sending the query instruction to the data warehouse, the method further includes:

[0011] Transaction data is acquired and sent to the data warehouse, so that the data warehouse classifies the transaction data according to preset attributes and stores the transaction data according to the classification.

[0012] In a possible design, after receiving all the first transaction data returned by the data warehouse, the method further includes:

[0013] Verifying each first transaction data to determine whether the first transaction data meets the preset specified condition;

[0014] If the first transaction data does not meet the preset specified condition, the first transaction data is ignored.

[0015] In a possible design, determining the transaction channel corresponding to the first transaction data according to the transaction time and transaction location of the first transaction data includes:

[0016] Get the business hours of outlets;

[0017] Determining whether the transaction time of the first transaction data is within the business hours of the outlet;

[0018] If the transaction time of the first transaction data is within the business hours of the outlet, whether there is an outlet within a preset area with a preset distance as a radius and the transaction location of the transaction data as the center;

[0019] If there is an outlet in the preset area, determining that the transaction channel of the first transaction data is an outlet transaction channel;

[0020] If the transaction time of the first transaction data is not within the business hours of the outlet, or there is no outlet in the preset area, it is determined that the transaction channel of the first transaction data is an online transaction channel.

[0021] In one possible design, the method further includes:

[0022] Determining whether the first transaction data carries an identification of a relevant staff member;

[0023] If the first transaction data carries an identifier of a relevant staff member, determining that the transaction channel of the first transaction data is a branch transaction channel;

[0024] If the first transaction data does not carry the identification of the relevant staff member, it is determined that the transaction channel of the first transaction data is an online transaction channel.

[0025] In one possible design, the method further includes:

[0026] Acquire a report generation request sent by a report query system, wherein the report generation request includes a report template;

[0027] The transaction results corresponding to each transaction channel are input into the report template to obtain a report file corresponding to each transaction channel.

[0028] In a second aspect, the present application provides a transaction data processing device, comprising:

[0029] An acquisition module, used to acquire a transaction performance statistics request, wherein the transaction performance statistics request includes one or more preset specified conditions;

[0030] a sending module, configured to generate a query instruction based on the preset specified conditions, and send the query instruction to the data warehouse, so that the data warehouse screens the stored transaction data to obtain first transaction data, wherein the first transaction data meets all the preset specified conditions, and the first transaction data includes a transaction time and a transaction location;

[0031] a determination module, configured to receive all first transaction data returned by the data warehouse, and determine a transaction channel corresponding to the first transaction data according to a transaction time and a transaction location of the first transaction data, wherein the transaction channel includes a branch transaction channel and an online transaction channel;

[0032] The statistical module is used to classify and then count the first transaction data based on the transaction channels of each first transaction data to obtain the transaction results corresponding to each transaction channel, wherein the transaction results represent the transaction data volume.

[0033] In a third aspect, an embodiment of the present application provides an electronic device, comprising: at least one processor and a memory; the memory stores computer execution instructions; at least one processor executes the computer execution instructions stored in the memory, so that the at least one processor executes the transaction data processing method as described in the first aspect above and various possible designs of the first aspect.

[0034] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer execution instructions are stored. When a processor executes the computer execution instructions, the transaction data processing method as described in the first aspect and various possible designs of the first aspect are implemented.

[0035] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the transaction data processing method as described in the first aspect and various possible designs of the first aspect.

[0036] The transaction data processing method, device, equipment and storage medium provided by the present application, after filtering all the first transaction data through preset specified conditions, infers the transaction channel when the first transaction data occurs through the transaction time and transaction location of the first transaction data. The present application avoids the drawback of unilaterally classifying the transaction data using online marketing tools directly into online transaction channels, and determines the actual transaction channel of the first transaction data through the transaction time and transaction location, and can clearly classify the actual transaction channel of each first transaction data, so as to facilitate the statistics of the corresponding results of each transaction channel, thereby improving the statistical efficiency of the corresponding results of each transaction channel. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0038] Figure 1 The following is an application scenario diagram for examples;

[0039] Figure 2 The process of the transaction data processing method provided in the embodiment of the present application Figure 1 ;

[0040] Figure 3 The process of the transaction data processing method provided in the embodiment of the present application Figure 2 ;

[0041] Figure 4 Another application scenario diagram for example;

[0042] Figure 5 The process of the transaction data processing method provided in the embodiment of the present application Figure 3 ;

[0043] Figure 6 The process of the transaction data processing method provided in the embodiment of the present application Figure 4 ;

[0044] Figure 7 Another application scenario diagram is shown as an example;

[0045] Figure 8 The process of the transaction data processing method provided in the embodiment of the present application Figure 5 ;

[0046] Fig. 9 The process of the transaction data processing method provided in the embodiment of the present application Figure 6 ;

[0047] Fig.10 Another application scenario diagram is shown as an example;

[0048] Fig.11 A schematic diagram of the structure of a transaction data processing device provided in an embodiment of the present application;

[0049] Fig.12 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0050] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0051] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0052] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of information such as financial data or user data involved shall comply with the provisions of relevant laws and regulations and shall not violate public order and good morals.

[0053] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0054] With the evolution of the big data era and the continuous advancement of digital reforms, digital business ideas and methods have gradually been implemented and formed into tools in various companies, including customer views and transaction performance statistics systems.

[0055] Figure 1 This is an example application scenario diagram. Figure 1 As shown, the application scenarios of this application include a data application service system and a data warehouse, wherein the data warehouse is used to store transaction data completed through various channels. Transaction channels are generally divided into two categories: branch transaction channels and online transaction channels. The specific transaction channels of branch transaction channels include high counters, low counters, smart ATMs and self-service inquiry machines, etc. The specific transaction channels of online transaction channels include personal mobile banking, corporate mobile banking, personal telephone banking and international websites, etc. Figure 1Channel A, Channel B, Channel C, and finally Channel X can be specific transaction channels in branch transaction channels and online transaction channels. With the continuous improvement of the platform operation capabilities of online transaction channels, online transaction channels have become the product marketing shelves of banks.

[0056] Transactions completed through online marketing tools carry staff coding information and should actually be attributed to the effectiveness of branch transaction channels. However, according to the current method of statistically analyzing the effectiveness of transaction channels, they will be attributed to the transaction effectiveness of online transaction channels. As a result, it is impossible to accurately define whether the effectiveness of a single product transaction completed on the online transaction channel was completed independently by the user or with the intervention of staff. Manual secondary processing is required, resulting in low statistical efficiency for the effectiveness of each transaction channel.

[0057] In view of the above technical problems and example application scenarios, the present application proposes the following technical ideas: the method provided by the present application can be applied to a data application service system, the data application service system generates a query instruction based on the preset conditions specified in the transaction effectiveness statistics request by obtaining a transaction effectiveness statistics request, and sends the query instruction to the data warehouse, so that the data warehouse can filter the stored transaction data and receive all the first transaction data returned by the data warehouse. The data application service system determines whether the first transaction data corresponds to a branch transaction channel or an online transaction channel by analyzing the transaction time and transaction location of the first transaction data, and classifies and counts the first transaction data based on the transaction channel of each first transaction data to obtain the transaction effectiveness corresponding to each transaction channel. The present application avoids the drawback of directly classifying the transaction data using online marketing tools into online transaction channels. By judging the actual transaction channel of the first transaction data by the transaction time and transaction location, the actual transaction channel of each first transaction data can be clearly divided, which is convenient for counting the effectiveness corresponding to each transaction channel, thereby improving the statistical efficiency of the effectiveness corresponding to each transaction channel.

[0058] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0059] based on Figure 1 In the application scenario shown, the embodiment of the present application also provides a transaction data processing method. Figure 2 The process of the transaction data processing method provided in the embodiment of the present application Figure 1 ,like Figure 2 As shown, the transaction data processing method includes:

[0060] S201. Obtain a transaction performance statistics request, wherein the transaction performance statistics request includes one or more preset specified conditions.

[0061] The executor of this embodiment is a data application service system, which can be implemented through a computer program, such as application software, etc.; or, it can be implemented as a medium storing relevant computer programs, such as a USB flash drive, a cloud disk, etc.; or, it can be implemented through a physical device integrated or installed with relevant computer programs, such as a chip, etc.

[0062] Combined with the scenario example, the specified conditions can be product type, product transaction type and product transaction channel, etc. The specified conditions preset in the transaction effectiveness statistics request can be determined according to the actual situation. For example, the transaction effectiveness statistics request obtained in this embodiment includes two preset specified conditions of product type and transaction channel, where product types are divided into consumer products: such as food, clothing, home appliances, cosmetics, etc.; industrial products: such as machinery and equipment, industrial raw materials, chemical products, etc.; and medical supplies: such as medicines, medical devices, diagnostic reagents, etc. Transaction types can be roughly divided into commodity transactions, service transactions, financial transactions and intellectual property transactions, etc. The specific classification of product types and the specific classification of transaction types can be determined according to the actual situation.

[0063] S202. Generate a query instruction based on the preset specified conditions, and send the query instruction to the data warehouse, so that the data warehouse screens the stored transaction data to obtain first transaction data, wherein the first transaction data meets all the preset specified conditions, and the first transaction data includes transaction time and transaction location.

[0064] Combined with the scenario example, for example, the preset specified conditions in the transaction performance statistics request are: the product type is food, and the transaction type is commodity transaction, then the generated query instruction represents the query to obtain transaction data whose product type is food and whose transaction type is commodity transaction. The transaction data stored in the data warehouse includes multiple attributes, including product type, transaction type, transaction channel, transaction performance indicator, staff code, transaction time and transaction location, etc. The query instruction is sent to the data warehouse, and the data warehouse screens all the transaction data stored locally based on the attributes of the transaction data to obtain all the first transaction data that meet the product type of food and the transaction type of commodity transaction, and returns the first transaction data.

[0065] S203. Receive all first transaction data returned by the data warehouse, and determine the transaction channel corresponding to the first transaction data according to the transaction time and transaction location of the first transaction data, wherein the transaction channel includes a branch transaction channel and an online transaction channel.

[0066] In combination with the scenario example, the transaction time in the first transaction data is the time corresponding to when the transaction occurs, which may be the time when the transaction is finally completed, and the transaction location is the location corresponding to when the transaction occurs, which may be the location of the transaction device used by the user when the transaction is completed.

[0067] S204. Based on the transaction channels of each first transaction data, the first transaction data are classified and counted to obtain the transaction results corresponding to each transaction channel, wherein the transaction results represent the transaction data volume.

[0068] Combined with the scenario example, the transaction effectiveness corresponding to the channel can be represented by the transaction volume completed through the channel. For example, there are 1,000 first transaction data obtained by screening, and 400 of them are branch transaction channels, and 600 of them are online transaction channels. It can be obtained that in the first transaction data with the product type of food and the transaction type of commodity transaction, the transaction effectiveness of the branch transaction channel is 40%, and the transaction effectiveness of the online transaction channel is 60%.

[0069] This example avoids the drawback of one-sidedly classifying transaction data using online marketing tools directly into online transaction channels. By judging the actual transaction channel of the first transaction data by the transaction time and transaction location, the actual transaction channel of each first transaction data can be clearly divided, which facilitates the statistics of the corresponding results of each transaction channel, thereby improving the statistical efficiency of the corresponding results of each transaction channel.

[0070] Optional, Figure 3 The process of the transaction data processing method provided in the embodiment of the present application Figure 2 ,like Figure 3 As shown, before sending the query instruction to the data warehouse, the method further includes:

[0071] S301. Acquire transaction data, and send the transaction data to the data warehouse, so that the data warehouse classifies the transaction data according to preset attributes, and stores the transaction data according to the classification.

[0072] Combined with the scene example, Figure 4 Another application scenario diagram is shown as an example. Figure 4As shown, the transaction data corresponding to different transaction channels are obtained, and the transaction data are transmitted to the storage module of the data warehouse. The data warehouse can classify the transaction data transmitted to the storage module according to the attributes carried in the transaction data. The attributes of the transaction data specifically include product type, transaction type, transaction channel, transaction performance indicator, staff code, transaction time and transaction location. For example, the transaction data is classified according to product type. For example, the transaction data is divided into five categories, and the transaction data belonging to the same category is stored in the same data block to obtain five data blocks, namely block A, block B, block C, block D and block E. The method of classifying and storing transaction data can also classify transaction data according to other attributes, and can be classified according to actual conditions. This example can improve the orderliness of transaction data storage by classifying and storing transaction data from various channels.

[0073] Optional, Figure 5 The process of the transaction data processing method provided in the embodiment of the present application Figure 3 ,like Figure 5 As shown, after receiving all the first transaction data returned by the data warehouse in S202, the method further includes:

[0074] S501. Verify each first transaction data to determine whether the first transaction data meets the preset specified condition.

[0075] Combined with the scenario example, each first transaction data returned by the data warehouse is verified, and the specific verification content is to determine whether the content represented by the attributes of the first transaction data meets the preset specified conditions. For example, the preset specified conditions in the transaction effectiveness statistics request are: the product type is food, and the transaction type is commodity transaction, then the content of the two attributes of product type and expected transaction type of each first transaction data is obtained. If the attribute of the product type in the first transaction data is food, and the attribute content of the transaction type is commodity transaction, then it can be determined that the first transaction data meets the preset specified conditions, indicating that the first transaction data has passed the verification. On the contrary, if the attribute of the product type in the first transaction data is not food, or the attribute content of the transaction type is not commodity transaction, then it can be determined that the first transaction data does not meet the preset specified conditions, indicating that the first transaction data has not passed the verification.

[0076] S502: If the first transaction data does not meet the preset specified condition, ignore the first transaction data.

[0077] In combination with the scenario example, for the first transaction data that meets the preset specified conditions, the step of determining the transaction channel corresponding to the first transaction data according to the transaction time and transaction location of the first transaction data, wherein the transaction channel includes a branch transaction channel and an online transaction channel. For the first transaction data that does not meet the preset specified conditions, the first transaction data is deleted. Based on the method provided in this example, the first transaction data that does not meet the preset specified conditions can be eliminated to make the obtained first transaction data more accurate, which can improve the statistical accuracy of the effectiveness corresponding to each transaction channel.

[0078] Optional, Figure 6 The process of the transaction data processing method provided in the embodiment of the present application Figure 4 ,like Figure 6 As shown, in S203, judging the transaction channel corresponding to the first transaction data according to the transaction time and transaction location of the first transaction data includes:

[0079] S601. Obtain the business hours of the outlets.

[0080] Combined with the scenario example, the business hours of the outlets can be adjusted according to the actual situation. For example, the obtained business hours of the outlets can be 8:00-17:00.

[0081] S602: Determine whether the transaction time of the first transaction data is within the business hours of the outlet.

[0082] Combined with the scene example, Figure 7 Another application scenario diagram is shown as an example. Figure 7 As shown, the application scenario of this example includes a positioning service system. Both the data application service system and the positioning service system have data processing modules. The data processing module in the data application service system obtains the transaction time and transaction location corresponding to the first transaction data from the attributes of the first transaction data. The data processing module in the data application service system sends the transaction time and transaction location in the first transaction data to the data processing module in the positioning service system, so that the data processing module in the positioning service system compares the transaction time corresponding to the first transaction data with the acquired business hours of the outlets.

[0083] S603: If the transaction time of the first transaction data is within the business hours of the outlet, determine whether there is an outlet within a preset area with a preset distance as a radius and the transaction location of the transaction data as the center.

[0084] Combined with the scenario example, if the transaction time corresponding to the first transaction data is 9:00, it can be determined that the transaction time of the first transaction data is within the business hours of the outlet. In this case, the transaction location corresponding to the first transaction data is obtained, and the preset radius can be selected as 100m. The search is performed within a range with a radius of 100m with the transaction location as the center to determine whether there is an outlet within the range.

[0085] S604: If there is an outlet in the preset area, determine that the transaction channel of the first transaction data is an outlet transaction channel.

[0086] Combined with the scenario example, if there is an outlet within the range, the positioning service system will return the outlets within the range to the data application service system. This means that the first transaction data was generated during the working hours of the outlet and near the outlet. The transaction channel of the first transaction data can be determined as the outlet transaction channel.

[0087] S605: If the transaction time of the first transaction data is not within the business hours of the outlet, or there is no outlet in the preset area, determine that the transaction channel of the first transaction data is an online transaction channel.

[0088] Combined with the scenario example, if the transaction time of the first transaction data is not during the business hours of the outlet, it means that the staff in the outlet did not participate when the first transaction data was generated, and the transaction channel of the first transaction data can be determined as an online transaction channel. Alternatively, if the transaction time of the first transaction data is during the business hours of the outlet, but there is no outlet within 100m of the transaction location of the first transaction data, it can also be said that the staff in the outlet did not participate when the first transaction data was generated, and the transaction channel of the first transaction data can be determined as an online transaction channel. Based on the method provided in this example, it is possible to determine whether the first transaction data involves the participation of staff based on the transaction location and transaction time carried in the first transaction data, which can improve the accuracy of determining the transaction channel corresponding to the first transaction data.

[0089] Optional, Figure 8 The process of the transaction data processing method provided in the embodiment of the present application Figure 5 ,like Figure 8 As shown, the method also includes:

[0090] S801. Determine whether the first transaction data carries the identification of relevant staff.

[0091] In combination with the scenario example, in addition to determining the transaction channel of the first transaction data by the transaction time and transaction location corresponding to the first transaction data, the identification of the staff member can also be added to the first transaction data. For example, if the completion of the first transaction data involves the assistance, promotion or participation of staff member A, the identification corresponding to staff member A can be added to the attributes of the first transaction data when the first transaction data is generated. Therefore, by determining whether the first transaction data carries the identification of the relevant staff member, it can be determined whether the generation of the first transaction data involves the participation of the relevant staff member.

[0092] S802: If the first transaction data carries an identifier of a relevant staff member, determine that the transaction channel of the first transaction data is a branch transaction channel.

[0093] Combined with the scenario example, if the attributes of the first transaction data contain the identification of the relevant staff member, for example, the attributes of the first transaction data contain the identification of staff member A, it means that staff member A participated in the completion of the first transaction data, then it can be determined that the transaction channel of the first transaction data is a branch transaction channel.

[0094] S803: If the first transaction data does not carry the identification of the relevant staff member, determine that the transaction channel of the first transaction data is an online transaction channel.

[0095] Combined with the scenario example, if the attributes of the first transaction data do not contain any identification of any relevant staff, it means that any staff is involved in the completion of the first transaction data, and it can be determined that the transaction channel of the first transaction data is an online transaction channel.

[0096] Based on the method provided in this example, it is possible to determine whether there is staff involvement in the first transaction data by judging whether the first transaction data carries the identification of the relevant staff, thereby improving the accuracy of determining the transaction channel corresponding to the first transaction data.

[0097] Optional, Fig. 9 The process of the transaction data processing method provided in the embodiment of the present application Figure 6 ,like Fig. 9 As shown, the method also includes:

[0098] S901. Obtain a report generation request sent by a report query system, where the report generation request includes a report template.

[0099] Combined with the scene example, Fig.10 Another application scenario diagram is shown as an example. Fig.10As shown, the application scenario of this example includes a report query system, which sends a report query request to the data application service system, and the report query request includes one or more preset specified conditions and the template used for the report. The data application service system generates a query instruction based on one or more preset specified conditions and sends it to the data warehouse, so that the data warehouse returns the first transaction data that meets all the specified conditions. The data processing module of the data application service system sends the transaction time and transaction location of each first transaction data to the data processing module of the positioning service system, so that the data processing module of the positioning service system returns the result of whether each first transaction data occurs during the business hours of the outlet and whether there is an outlet within the preset range to the data processing module of the data application service system. The data processing module of the data application service system uses this to determine the transaction channel corresponding to each first transaction data.

[0100] S902. Input the transaction results corresponding to each transaction channel into the report template to obtain a report file corresponding to each transaction channel.

[0101] Combined with the scenario example, the data processing module of the data application service system, based on the transaction channel of each first transaction data enemy camp, splits and summarizes the transaction channels belonging to the outlet transaction channels and the online transaction channels, respectively, obtains the transaction results corresponding to the outlet transaction channels and the online transaction channels, and inputs the transaction results corresponding to the outlet transaction channels and the online transaction channels into the template used in the report, so as to obtain the report files corresponding to each transaction channel. For example, if the transaction results of the outlet transaction channel are 40% and the transaction results of the online transaction channel are 60%, then the relevant information of the transaction results of the outlet transaction channel being 40% is input into the template used in the report to obtain the report file corresponding to the outlet transaction channel. Similarly, the relevant information of the transaction results of the online transaction channel being 60% is input into the template used in the report to obtain the report file corresponding to the online transaction channel. Then the data processing module of the data application service system returns the report file corresponding to the outlet transaction channel and the report file corresponding to the online transaction channel to the report query system.

[0102] This embodiment avoids the drawback of one-sidedly classifying transaction data using online marketing tools directly into online transaction channels. By judging the actual transaction channel of the first transaction data by the transaction time and transaction location, the actual transaction channel of each first transaction data can be clearly divided, which facilitates the statistics of the corresponding results of each transaction channel, thereby improving the statistical efficiency of the corresponding results of each transaction channel.

[0103] Fig.11 A schematic diagram of the structure of a transaction data processing device provided in an embodiment of the present application, such as Fig.11As shown, the transaction data processing device includes: an acquisition module 111, a sending module 112, a judgment module 113 and a statistical module 114;

[0104] The acquisition module 111 is used to acquire a transaction performance statistics request, wherein the transaction performance statistics request includes one or more preset specified conditions;

[0105] A sending module 112, configured to generate a query instruction based on the preset specified conditions, and send the query instruction to the data warehouse, so that the data warehouse screens the stored transaction data to obtain first transaction data, wherein the first transaction data meets all the preset specified conditions, and the first transaction data includes transaction time and transaction location;

[0106] A determination module 113 is configured to receive all first transaction data returned by the data warehouse, and determine a transaction channel corresponding to the first transaction data according to the transaction time and transaction location of the first transaction data, wherein the transaction channel includes a branch transaction channel and an online transaction channel;

[0107] The statistical module 114 is used to classify and count the first transaction data based on the transaction channels of each first transaction data to obtain the transaction results corresponding to each transaction channel, wherein the transaction results represent the transaction data volume.

[0108] Optionally, the sending module 112 is further used to obtain transaction data and send the transaction data to the data warehouse;

[0109] The sending module 112 is further used to classify the transaction data according to preset attributes and store the transaction data according to the classification.

[0110] Optionally, the judgment module 113 is further configured to verify each first transaction data to determine whether the first transaction data meets the preset specified condition;

[0111] The judgment module 113 is further configured to ignore the first transaction data if the first transaction data does not meet the preset specified condition.

[0112] Optionally, the judgment module 113 is specifically used to obtain the business hours of the outlets;

[0113] The judgment module 113 is further configured to judge whether the transaction time of the first transaction data is within the business hours of the outlet;

[0114] The judgment module 113 is further configured to determine whether there is an outlet within a preset area with a preset distance as a radius and a transaction location of the transaction data as the center if the transaction time of the first transaction data is within the business hours of the outlet;

[0115] The judgment module 113 is further configured to determine that the transaction channel of the first transaction data is a branch transaction channel if there is a branch in the preset area;

[0116] The judgment module 113 is further specifically configured to determine that the transaction channel of the first transaction data is an online transaction channel if the transaction time of the first transaction data is not within the business hours of the outlet, or there is no outlet in the preset area.

[0117] Optionally, the judging module 113 is further configured to judge whether the first transaction data carries an identification of a relevant staff member;

[0118] The judgment module 113 is further configured to determine that the transaction channel of the first transaction data is a branch transaction channel if the first transaction data carries an identifier of a relevant staff member;

[0119] The judgment module 113 is further configured to determine that the transaction channel of the first transaction data is an online transaction channel if the first transaction data does not carry the identification of the relevant staff member.

[0120] Optionally, the sending module 112 is further configured to obtain a report generation request sent by the report query system, wherein the report generation request includes a report template;

[0121] The sending module 112 is further used to input the transaction results corresponding to each transaction channel into the report template to obtain a report file corresponding to each transaction channel.

[0122] The transaction data processing device provided in the embodiment of the present application can be used to execute the technical solution of the transaction data processing method in the above embodiment. Its implementation principle and technical effect are similar and will not be repeated here.

[0123] It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. And these modules can all be implemented in the form of software called by processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware. For example, the statistical module 114 can be a separately established processing element, or it can be integrated in a chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and called and executed by a processing element of the above device. The function of the above statistical module 114. The implementation of other modules is similar. In addition, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module above can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

[0124] Fig.12 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig.12 As shown, the electronic device may include: a transceiver 121 , a processor 122 , and a memory 123 .

[0125] The processor 122 executes the computer execution instructions stored in the memory, so that the processor 122 executes the scheme in the above embodiment. The processor 122 can be a general-purpose processor, including a central processing unit CPU, a network processor (network processor, NP), etc.; it can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0126] The memory 123 is connected to the processor 122 via a system bus and completes communication between them. The memory 123 is used to store computer program instructions.

[0127] The transceiver 121 may be used to obtain tasks to be executed and configuration information of the tasks to be executed.

[0128] The system bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The system bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The transceiver is used to realize the communication between the database access device and other computers (such as clients, read-write libraries, and read-only libraries). The memory may include random access memory (RAM) and may also include non-volatile memory.

[0129] The electronic device provided in the embodiment of the present application may be the terminal device of the above embodiment.

[0130] An embodiment of the present application also provides a chip for running instructions, which is used to execute the technical solution of the transaction data processing method in the above embodiment.

[0131] The embodiment of the present application also provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed on a computer, the computer executes the technical solution of the transaction data processing method of the above embodiment.

[0132] An embodiment of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When at least one processor executes the computer program, it can implement the technical solution of the transaction data processing method in the above embodiment.

[0133] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0134] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.

[0135] In addition, each functional module in each embodiment of the present application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The above-mentioned module-composed unit can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0136] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the methods of various embodiments of the present application.

[0137] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.

[0138] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, etc.

[0139] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0140] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0141] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic control unit or a main control device.

[0142] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0143] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A transaction data processing method, characterized in that: The method comprises: Obtaining a transaction performance statistics request, wherein the transaction performance statistics request includes one or more preset specified conditions; Generate a query instruction based on the preset specified conditions, and send the query instruction to the data warehouse, so that the data warehouse screens the stored transaction data to obtain first transaction data, wherein the first transaction data meets all the preset specified conditions, and the first transaction data includes transaction time and transaction location; receiving all first transaction data returned by the data warehouse, and determining, according to the transaction time and transaction location of the first transaction data, a transaction channel corresponding to the first transaction data, wherein the transaction channel includes an outlet transaction channel and an online transaction channel; Based on the transaction channels of each first transaction data, the first transaction data are classified and then counted to obtain the transaction results corresponding to each transaction channel, wherein the transaction results represent the transaction data volume.

2. The method according to claim 1, characterized in that Before sending the query instruction to the data warehouse, the method further includes: Transaction data is acquired and sent to the data warehouse, so that the data warehouse classifies the transaction data according to preset attributes and stores the transaction data according to the classification.

3. The method according to claim 1, characterized in that After receiving all the first transaction data returned by the data warehouse, the method further includes: Verifying each first transaction data to determine whether the first transaction data meets the preset specified condition; If the first transaction data does not meet the preset specified condition, the first transaction data is ignored.

4. The method according to claim 1, characterized in that The determining, according to the transaction time and transaction location of the first transaction data, a transaction channel corresponding to the first transaction data includes: Get the business hours of outlets; Determining whether the transaction time of the first transaction data is within the business hours of the outlet; If the transaction time of the first transaction data is within the business hours of the outlet, whether there is an outlet within a preset area with a preset distance as a radius and the transaction location of the transaction data as the center; If there is an outlet in the preset area, determining that the transaction channel of the first transaction data is an outlet transaction channel; If the transaction time of the first transaction data is not within the business hours of the outlet, or there is no outlet in the preset area, it is determined that the transaction channel of the first transaction data is an online transaction channel.

5. The method according to claim 1, characterized in that The method further comprises: Determining whether the first transaction data carries an identification of a relevant staff member; If the first transaction data carries an identifier of a relevant staff member, determining that the transaction channel of the first transaction data is a branch transaction channel; If the first transaction data does not carry the identification of the relevant staff member, it is determined that the transaction channel of the first transaction data is an online transaction channel.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: Obtaining a report generation request, wherein the report generation request includes a report template; The transaction results corresponding to each transaction channel are input into the report template to obtain a report file corresponding to each transaction channel.

7. A transaction data processing device, characterized in that: include: An acquisition module, used to acquire a transaction performance statistics request, wherein the transaction performance statistics request includes one or more preset specified conditions; a sending module, configured to generate a query instruction based on the preset specified conditions, and send the query instruction to the data warehouse, so that the data warehouse screens the stored transaction data to obtain first transaction data, wherein the first transaction data meets all the preset specified conditions, and the first transaction data includes a transaction time and a transaction location; a determination module, configured to receive all first transaction data returned by the data warehouse, and determine a transaction channel corresponding to the first transaction data according to a transaction time and a transaction location of the first transaction data, wherein the transaction channel includes a branch transaction channel and an online transaction channel; The statistical module is used to classify and then count the first transaction data based on the transaction channels of each first transaction data to obtain the transaction results corresponding to each transaction channel, wherein the transaction results represent the transaction data volume.

8. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when being executed by a processor.

Images