Bill processing method and device based on operator and computer storage medium

Abstract

The invention provides an operator-based bill processing method, a bill processing device and a computer storage medium. The bill processing method comprises the steps of obtaining a plurality of pieces of bill data and a plurality of pieces of system order data; matching the matching field of each piece of bill data with the matching field of each piece of system order data according to a preset matching condition; marking the bill data and the system order data of which the preset number of matching fields are successfully matched as associated data; and extracting the bill time and the account period income record of the bill data in the associated data to a data table. Through the bill processing method, the income can be relatively accurately restored to each order, and the complete account period of the order can be seen, so that the user online rate of each customer, each goods and each channel can be speculated, the user group can be further analyzed, the productivity can be effectively improved, and the cost can be effectively reduced.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to an operator-based bill processing method, a bill processing device, and a computer storage medium. Background Art

[0002] In recent years, the communications market has become increasingly saturated, competition among operators has intensified, and revenue from traditional services such as voice and SMS has continued to decline. However, in the government and enterprise communications market, industrial digital services have flourished.

[0003] The communication operator's accounting system still has performance bottlenecks in processing massive data services. The accounts in the communication operator's accounting system contain tens of thousands of product numbers and a large number of communication bills. With the development of business, the number of accounts and personalized services in the communication operator's accounting system has increased year by year. The unified service provided by the system cannot meet the performance requirements of large account business support, and cannot effectively track system orders. As a result, when executing business scenarios such as account balance deduction, query, batch shutdown and resumption, it is easy to cause system timeouts and congestion, affecting customer billing services and customer perception. Summary of the invention

[0004] In order to solve the above technical problems, the present application proposes an operator-based bill processing method, a bill processing device and a computer storage medium.

[0005] In order to solve the above technical problems, the present application proposes a bill processing method based on an operator, and the bill processing method includes:

[0006] Obtain some billing data and some system order data;

[0007] Match the matching fields of each bill data with the matching fields of each system order data according to the preset matching conditions;

[0008] Mark the billing data and system order data whose preset number of matching fields are successfully matched as related data;

[0009] The billing time and billing period income of the billing data in the associated data are extracted and recorded in the data table.

[0010] After obtaining the plurality of bill data and the plurality of system order data, the bill processing method further comprises:

[0011] In response to the bill data being bill data without detailed information, obtaining an order dimension combination of all system order data;

[0012] Get the order proportion of each order dimension combination;

[0013] Allocate the total revenue of all bills without detailed bill data to each system order data according to the order proportion of each order dimension combination;

[0014] The revenue allocation result of each system order data is recorded in the data table.

[0015] The matching of each bill data's matching field with each system order data's matching field according to the preset matching condition includes:

[0016] The billing data in which the number of successfully matched fields is less than the preset number is marked as having no detailed billing data.

[0017] The billing data whose number of successfully matched fields is less than the preset number is marked as having no detailed billing data, including:

[0018] Performing error adjustment on the field information corresponding to any matching field in the billing data where the number of successfully matched matching fields is less than the preset number;

[0019] Re-matching the error-adjusted billing data with each system order data;

[0020] When the number of successfully matched fields after error adjustment is less than the preset number, the bill data is marked as having no detailed bill data.

[0021] Wherein, any one of the matching fields is the activation month;

[0022] The error adjustment of the field information corresponding to any one of the matching fields in the billing data, wherein the number of successfully matched matching fields is less than the preset number, comprises:

[0023] The activation month in the billing data in which the number of successfully matched fields is less than the preset number is increased or decreased by one month to obtain billing data after error adjustment.

[0024] Among them, the matching fields include: activation month, customer name, category, and / or settlement mobile phone number; the order dimensions include: activation month, customer name, category, and / or channel.

[0025] The obtaining of the order proportion of each order dimension combination includes:

[0026] Obtain the order quantity of each order dimension combination;

[0027] Based on the ratio of the order quantity of each order dimension combination to the total order quantity of all system order data, the order proportion of each order dimension combination is obtained;

[0028] The total revenue of all bills without detailed bill data is allocated to each system order data according to the order proportion of each order dimension combination, including:

[0029] Divide the total revenue of all bills without detailed bill data into each order dimension combination according to the order proportion of each order dimension combination, and obtain the bill revenue of each order dimension combination;

[0030] The bill revenue of each order dimension combination is evenly distributed to the system order data of each order dimension combination according to the order quantity of each order dimension combination, so as to associate the bill revenue of each system order data.

[0031] After extracting the billing time and billing period income of the billing data in the associated data and recording them in the data table, the bill processing method further includes:

[0032] The billing time and billing period income of the same system order data in the data table are aggregated to obtain the complete billing period and the total billing period income of the system order data.

[0033] In order to solve the above technical problems, the present application also proposes a bill processing device, which includes a memory and a processor coupled to the memory; wherein the memory is used to store program data, and the processor is used to execute the program data to implement the bill processing method as described above.

[0034] In order to solve the above technical problems, the present application also proposes a computer storage medium, which is used to store program data. When the program data is executed by a computer, it is used to implement the above bill processing method.

[0035] Compared with the prior art, the beneficial effects of the present application are as follows: the bill processing device obtains a number of bill data and a number of system order data; matches the matching fields of each bill data with the matching fields of each system order data according to the preset matching conditions; marks the bill data and system order data that have successfully matched the preset number of matching fields as associated data; extracts the billing time and account period income of the bill data in the associated data and records them in the data table. Through the above-mentioned bill processing method, the income can be relatively accurately restored to each order, and the complete account period of the order can be seen, so that the online user rate of each customer, each product, and each channel can be inferred, so that the user group can be further analyzed, which can effectively improve production capacity and reduce costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0037] in:

[0038] Figure 1 It is a flowchart of an embodiment of a bill processing method based on an operator provided in this application;

[0039] Figure 2 This is a schematic diagram of the overall process of the operator-based bill processing method provided by this application;

[0040] Figure 3 It is a flowchart of another embodiment of the operator-based bill processing method provided by the present application;

[0041] Figure 4 It is a flowchart of another embodiment of the operator-based bill processing method provided by the present application;

[0042] Figure 5 It is a structural diagram of an embodiment of a bill processing device provided by the present application;

[0043] Figure 6 It is a structural diagram of an embodiment of a computer storage medium provided by the present application. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0046] There are usually two modes of operator statements: one is a detailed statement, and the other is a non-detailed statement. Both statements have a common problem: they cannot match the system order.

[0047] If there is no detailed statement, there will only be data such as activation month or date, entity, category (operator product categories: SIM card, broadband, inventory), income amount, and income items.

[0048] If there is a detailed statement, compared to no detailed statement, there is an additional settlement mobile phone number, which can be accurately matched with the orders in the system.

[0049] This application below provides a specific bill processing method based on the operator for detailed statements. For details, please refer to Figure 1 and Figure 2 , Figure 1 is a flowchart of an embodiment of a bill processing method based on an operator provided in this application, Figure 2 It is a schematic diagram of the overall process of the operator-based bill processing method provided in this application.

[0050] The operator-based bill processing method of the present application is applied to a bill processing device, wherein the bill processing device of the present application can be a server, a terminal device, or a system in which a server and a terminal device cooperate with each other. Accordingly, the various parts included in the bill processing device, such as various units, sub-units, modules, and sub-modules, can all be set in the server, can all be set in the terminal device, or can be set in the server and the terminal device respectively.

[0051] Furthermore, the above-mentioned server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server is software, it can be implemented as multiple software or software modules, such as software or software modules used to provide distributed servers, or it can be implemented as a single software or software module, which is not specifically limited here.

[0052] like Figure 1 As shown, the specific steps are as follows:

[0053] Step S11: Obtain some billing data and some system order data.

[0054] In an embodiment of the present application, the bill processing device extracts a number of bill data and a number of system order data from a big data database. Correspondingly, the bill processing device provided by the present application includes a bill data module and a system order data module, which are respectively used to manage the above two data types.

[0055] Specifically, the bill processing device needs to clean the statement data of all customers in advance, and store the data in the big data database according to the fields of customer name, activation month, account period month, entity, category, settlement mobile phone number, income item, income amount, and statement type (with details or without details).

[0056] In addition, the bill processing device needs to clean the original order data in the system in advance, and store the data in the big data database according to the fields of order number, channel, order time, activation time, settlement mobile phone number, customer name, and category.

[0057] The bill data module also classifies bill types to distinguish between detailed bills and non-detailed bills. This application directly uses the activation month, customer name, category, and settlement mobile phone number fields for data matching for detailed bills; and uses the apportionment method for data allocation for non-detailed bills. It should be noted that Figure 1 The bill processing method shown mainly performs matching processing on detailed bills.

[0058] On the one hand, the bill processing device can determine whether the bill data contains necessary data fields, such as activation month, customer name, category and settlement mobile phone number. If the bill data contains at least the required data fields, the bill data is marked as a detailed bill; if the bill data lacks at least one of the required data fields, the bill data is marked as a non-detailed bill. On the other hand, the bill processing device can further distinguish between detailed bills and non-detailed bills by field matching. It should be noted that the following steps S12 and S13 can also be regarded as precise matches for detailed bills, and their logic is basically the same.

[0059] Step S12: Match the matching fields of each bill data with the matching fields of each system order data according to the preset matching conditions.

[0060] In the embodiment of the present application, the bill processing device presets a matching condition. In a specific implementation, the matching condition may be that the four fields of activation month, customer name, category, and settlement mobile phone number must be exactly the same. In other implementations, other matching field types or other numbers of matching fields may be used to set matching conditions, which are not listed here one by one.

[0061] The bill processing device uses a matching algorithm and the above-mentioned preset matching conditions to compare the two data sets, namely each bill data and each system order data, to find all bill data and system order data that meet the matching conditions, namely, all the above-mentioned four matching fields are successfully matched, and enters step S13.

[0062] On the one hand, the bill processing device can mark the bill data that has not been successfully matched after traversing all system order data as a bill without details, preparing to proceed to the next step of processing; on the other hand, the bill processing device can also re-mark the detailed bill that has not been successfully matched after traversing all system order data as a bill without details, preparing to proceed to the next step of processing.

[0063] Step S13: Mark the billing data and system order data that have successfully matched a preset number of matching fields as associated data.

[0064] In the embodiment of the present application, the bill processing device marks the bill data and system order data that meet the matching conditions and are successfully matched as successfully matched associated data.

[0065] Step S14: extract the billing time and billing period income records of the billing data in the associated data and record them in the data table.

[0066] In the embodiment of the present application, the bill processing device extracts the bill period time, such as the bill period month, and the bill period income from the successfully matched associated data, and associates them with the system order data. The bill processing device formats the extracted bill data into a vertical table form and prepares to store it in the big data database.

[0067] In an embodiment of the present application, the bill processing device obtains a number of bill data and a number of system order data; matches the matching field of each bill data with the matching field of each system order data according to a preset matching condition; marks the bill data and system order data that have successfully matched a preset number of matching fields as associated data; extracts the billing time and account period income of the bill data in the associated data and records them in a data table. Through the above-mentioned bill processing method, the income can be relatively accurately restored to each order, and the complete account period of the order can be seen, so that the online user rate of each customer, each product, and each channel can be inferred, so that the user group can be further analyzed, which can effectively improve production capacity and reduce costs.

[0068] This application provides a specific operator-based bill processing method for bills without detailed information. For details, please refer to Figure 3 , Figure 3 It is a flowchart of another embodiment of the operator-based bill processing method provided in this application.

[0069] like Figure 3 As shown, the specific steps are as follows:

[0070] Step S21: In response to the bill data being bill data without detailed information, an order dimension combination of all system order data is obtained.

[0071] In the embodiment of the present application, the bill processing device distinguishes the bill data in the big data database from the bill data without detailed information through the bill data module, or Figure 1 Steps S12 and S13 shown re-mark some detailed billing data that do not pass the matching condition as non-detailed billing data.

[0072] The bill processing device obtains order dimensions of all undetailed billing data, including but not limited to four dimensions: activation month, customer name, category and channel, and performs statistics on all undetailed billing data based on the above order dimensions.

[0073] Among them, each non-detailed billing data includes at least one of the above-mentioned order dimensions, and each non-detailed billing data is divided into corresponding order dimension combinations according to different order dimension types and order dimension quantities, including but not limited to: "activation month", "activation month + category", "customer name, category + channel", etc.

[0074] Step S22: Obtain the order proportion of each order dimension combination.

[0075] In the embodiment of the present application, the bill processing device obtains the number of orders for each order dimension combination counted and divided in step S21, for example, the number of orders belonging to "activation month + category" is 20. Assuming that the total number of orders for all orders is 100, the proportion of orders for the "activation month + category" order dimension combination is 20%.

[0076] Step S23: Allocate the total revenue of all bills without detailed bill data to each system order data according to the order proportion of each order dimension combination.

[0077] In the embodiment of the present application, the bill processing device divides the total revenue of all bills without detailed bill data into each order dimension combination according to the order proportion of each order dimension combination, and obtains the bill revenue of each order dimension combination. For example, if the total revenue of all bills without detailed bill data is 50,000, then the bill revenue of all order data of the "activation month + category" order dimension combination in the above example is 10,000.

[0078] The bill processing device evenly distributes the bill revenue of each order dimension combination to the system order data of each order dimension combination according to the order quantity of each order dimension combination, so as to associate the bill revenue of each system order data. For example, if the order quantity of the "activation month + category" order dimension combination is 20, the bill revenue of each system order data allocated to the "activation month + category" order dimension combination is 500.

[0079] In the embodiment of the present application, the bill processing device distributes the apportioned income to each matchable order, ensuring that the sum of the income of all orders is equal to the total income of the undetailed bill.

[0080] Step S24: Record the revenue allocation result of each system order data into the data table.

[0081] In this application, data is recorded in the form of a vertical table, with fields such as order number, activation month, TN month (TN is 0 in the activation month and 1 in the next month), amount, and whether there is a detailed list.

[0082] Furthermore, the bill processing device of the present application first performs detailed bill processing and then performs non-detailed bill processing, and stores the corresponding order restoration data in the vertical table respectively, distinguishing them by whether there are detailed fields.

[0083] Finally, the bill processing device aggregates the detailed data recorded in the vertical table, associates the original order data, takes the original order customer name, category, activation month, and amount, summarizes the data, and generates an aggregate table. The bill processing device ensures that the data format is unified and each record contains a type field to distinguish the source of the data.

[0084] The bill processing device stores the merged data in a big data database, usually using big data processing tools such as Starrocks. The bill processing device inserts the data into the corresponding database table by field through the database connection interface to ensure the integrity and accuracy of the data storage.

[0085] Furthermore, in step 12, it is mentioned that the bill processing device can mark the bill data that has not been successfully matched after traversing all system order data as a non-detailed bill, ready to enter the next step of processing. In order to improve the distinction between detailed bills and non-detailed bills, the present application also provides a secondary cleaning of detailed bill data.

[0086] Please refer to Figure 4 , Figure 4 It is a flowchart of another embodiment of the operator-based bill processing method provided in this application.

[0087] like Figure 4 As shown, the specific steps are as follows:

[0088] Step S31: Error adjustment is performed on the field information corresponding to any matching field in the billing data in which the number of successfully matched matching fields is less than a preset number.

[0089] In the embodiment of the present application, the bill processing device performs error adjustment on the field information corresponding to any one of the matching fields in the bill data whose number of successfully matched matching fields is less than the preset number. The error adjustment method may be to make a slight change to the field information of any one of the matching fields, so that the matching process can improve the fault tolerance and improve the accuracy of distinguishing between detailed bills and non-detailed bills.

[0090] For example, any of the above matching fields can be the activation month. During this cleaning process, the bill processing device will make a month adjustment to the activation month by one month before and after, that is, generate billing data after error adjustment, and the field data of other matching fields will not change. The bill processing device will match again based on the original activation month + 1 month and the original activation month - 1 month, customer name, category and settlement mobile phone number. If a match is found, the bill data will be marked as detailed billing data, and the activation month will be corrected for the system data. If it still does not match, it will be put into the non-detailed reconciliation data for processing again.

[0091] Step S32: Rematch the error-adjusted billing data with each system order data.

[0092] Step S33: When the number of matching fields that are successfully matched after error adjustment is less than a preset number, the bill data is marked as having no detailed bill data.

[0093] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0094] In order to implement the above-mentioned bill processing method, this application also proposes a bill processing device, please refer to Figure 5 , Figure 5 It is a structural diagram of an embodiment of a bill processing device provided by the present application.

[0095] The bill processing device 400 of this embodiment includes a processor 41 , a memory 42 , an input / output device 43 , and a bus 44 .

[0096] The processor 41 , the memory 42 , and the input / output device 43 are respectively connected to the bus 44 . The memory 42 stores program data, and the processor 41 is used to execute the program data to implement the bill processing method described in the above embodiment.

[0097] In the embodiment of the present application, the processor 41 may also be referred to as a CPU (Central Processing Unit). The processor 41 may be an integrated circuit chip having the ability to process signals. The processor 41 may also be a general-purpose processor, 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, or discrete hardware components. A general-purpose processor may be a microprocessor or the processor 41 may also be any conventional processor, etc.

[0098] This application also provides a computer storage medium, please continue to refer to Figure 6 , Figure 6 It is a structural diagram of an embodiment of a computer storage medium provided in the present application. The computer storage medium 600 stores a computer program 61. When the computer program 61 is executed by a processor, it is used to implement the bill processing method of the above embodiment.

[0099] When the embodiments of the present application are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk.

[0100] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A bill processing method based on an operator, characterized in that: The bill processing method includes: Obtain some billing data and some system order data; Match the matching fields of each bill data with the matching fields of each system order data according to the preset matching conditions; Mark the billing data and system order data whose preset number of matching fields are successfully matched as related data; The billing time and billing period income of the billing data in the associated data are extracted and recorded in the data table.

2. The bill processing method according to claim 1, characterized in that: After obtaining the plurality of bill data and the plurality of system order data, the bill processing method further includes: In response to the bill data being bill data without detailed information, obtaining an order dimension combination of all system order data; Get the order proportion of each order dimension combination; Allocate the total revenue of all bills without detailed bill data to each system order data according to the order proportion of each order dimension combination; The revenue allocation result of each system order data is recorded in the data table.

3. The bill processing method according to claim 2, characterized in that: The matching fields of each bill data and each system order data are matched according to the preset matching conditions, including: The billing data in which the number of successfully matched fields is less than the preset number is marked as having no detailed billing data.

4. The bill processing method according to claim 3, characterized in that: The billing data in which the number of successfully matched fields is less than the preset number is marked as having no detailed billing data, including: Performing error adjustment on the field information corresponding to any matching field in the billing data where the number of successfully matched matching fields is less than the preset number; Re-matching the error-adjusted billing data with each system order data; When the number of successfully matched fields after error adjustment is less than the preset number, the bill data is marked as having no detailed bill data.

5. The bill processing method according to claim 4, characterized in that: Any one of the matching fields is the activation month; The error adjustment of the field information corresponding to any one of the matching fields in the billing data, wherein the number of successfully matched matching fields is less than the preset number, comprises: The activation month in the billing data in which the number of successfully matched fields is less than the preset number is increased or decreased by one month to obtain billing data after error adjustment.

6. The bill processing method according to claim 2, characterized in that: The matching fields include: activation month, customer name, category, and / or settlement mobile phone number; the order dimensions include: activation month, customer name, category, and / or channel.

7. The bill processing method according to claim 2, characterized in that: The obtaining of the order proportion of each order dimension combination includes: Obtain the order quantity of each order dimension combination; Based on the ratio of the order quantity of each order dimension combination to the total order quantity of all system order data, the order proportion of each order dimension combination is obtained; The total revenue of all bills without detailed bill data is allocated to each system order data according to the order proportion of each order dimension combination, including: Divide the total revenue of all bills without detailed bill data into each order dimension combination according to the order proportion of each order dimension combination, and obtain the bill revenue of each order dimension combination; The bill revenue of each order dimension combination is evenly distributed to the system order data of each order dimension combination according to the order quantity of each order dimension combination, so as to associate the bill revenue of each system order data.

8. The bill processing method according to claim 1, characterized in that: After extracting the billing time and billing period income of the billing data in the associated data and recording them in the data table, the bill processing method further includes: The billing time and billing period income of the same system order data in the data table are aggregated to obtain the complete billing period and the total billing period income of the system order data.

9. A bill processing device, characterized in that: The bill processing device includes a memory and a processor coupled to the memory; The memory is used to store program data, and the processor is used to execute the program data to implement the bill processing method according to any one of claims 1 to 8.

10. A computer storage medium, characterized in that: The computer storage medium is used to store program data, and when the program data is executed by a computer, it is used to implement the bill processing method according to any one of claims 1 to 8.

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