Data query method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a data query method and device, equipment and a storage medium. The method comprises the steps that insurance data generated within a preset time period and at least one insurance merchant generating the insurance data are acquired; determining insurance data corresponding to each insurance merchant in the insurance data; associating the merchant attribute data of each insurance merchant with the insurance data corresponding to each insurance merchant to obtain to-be-queried data corresponding to each insurance merchant; the merchant attribute data at least comprises one of a merchant name, a merchant position and a merchant type; and determining target data from the to-be-queried data corresponding to any insurance merchant according to a received query request for any insurance merchant.

Description

Technical Field

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

[0002] For insurance companies, the store data of car dealers can reflect the operating conditions of the car dealerships, which directly affects the insurance company's premium assignment to car dealers and the recommendation for repair of insured vehicles. Therefore, timely query of the store data of car dealers provides strong support for the insurance company's car dealer business operations.

[0003] At present, the data query of car store usually first determines the condition combination to be queried, and then, through ETL (Extract Transform Load), developers write corresponding query programs according to the condition combination to be queried, and query the desired data from the database storing the full amount of insurance data according to the query program. Since data query is performed based on the condition combination of each requirement, and each condition combination of each requirement may involve different car store data, there are problems of repeated query and repeated statistical calculation for the data of the same car store, resulting in a waste of manpower and computing resources. Summary of the invention

[0004] The embodiments of the present disclosure provide a data query method, apparatus, device and storage medium to solve the problem in the related art of repeated query and waste of manpower and computing resources caused by performing data query based on the combination of conditions required each time.

[0005] In a first aspect, an embodiment of the present disclosure provides a data query method, the method comprising: Acquire insurance data generated within a preset time period, and at least one insurance merchant that generates the insurance data; Determine the insurance data corresponding to each of the insurance merchants in the insurance data; Associating the merchant attribute data of each of the insurance merchants with the insurance data corresponding to each of the insurance merchants to obtain the to-be-queried data corresponding to each of the insurance merchants; the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type; According to the received query request for any of the insurance merchants, target data is determined from the to-be-queried data corresponding to any of the insurance merchants.

[0006] In a second aspect, an embodiment of the present disclosure provides a data query device, the device comprising: An acquisition module, used to acquire insurance data generated within a preset time period, and at least one insurance merchant that generates the insurance data; A determination module, used to determine the insurance data corresponding to each of the insurance merchants in the insurance data; An association module is used to associate the merchant attribute data of each of the insurance merchants with the insurance data corresponding to each of the insurance merchants to obtain the to-be-queried data corresponding to each of the insurance merchants; the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type; The query module is used to determine target data from the to-be-queried data corresponding to any of the insurance merchants according to a received query request for any of the insurance merchants.

[0007] In a third aspect, an embodiment of the present disclosure provides a data query device, comprising: a processor; and a memory configured to store computer executable instructions, wherein the computer executable instructions, when executed, enable the processor to implement the steps of the method described in the first aspect above.

[0008] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store computer-executable instructions, and the computer-executable instructions, when executed by a processor, implement the steps of the method described in the first aspect above.

[0009] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, wherein the computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0010] At least one of the above technical solutions provided by the embodiments of the present invention can achieve the following technical effects: In an embodiment of the present invention, insurance data generated within a preset time period and at least one insurance merchant that generates the insurance data can be first obtained, and the insurance data corresponding to each insurance merchant in the insurance data can be determined. Then, the merchant attribute data of each insurance merchant can be associated with the insurance data corresponding to each insurance merchant to obtain the data to be queried corresponding to each insurance merchant, wherein the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type. After receiving a query request for any insurance merchant, the target data is determined from the data to be queried corresponding to any insurance merchant according to the received query request for any insurance merchant.

[0011] It can be seen from the above-mentioned embodiments of the invention that after obtaining the insurance data, the embodiments of the present invention can first determine the insurance merchant that generates the insurance data, and then determine the insurance data corresponding to each insurance merchant with the insurance merchant as the granularity, and further associate the merchant attribute data of the insurance merchant with the insurance data corresponding to the insurance merchant, so as to obtain more comprehensive data with the insurance merchant as the granularity to support data query for any insurance merchant. When a query request for any insurance merchant is received, the more comprehensive data corresponding to the insurance merchant can be directly obtained, and the target data corresponding to the query request can be obtained therefrom. Since the content to be queried can be accurately located with the insurance merchant as the dimension, the problem of repeated query and waste of manpower and computing resources caused by performing data query with the condition combination of each demand as the dimension in the related technology can be effectively solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate one or more embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative labor. Figure 1 One of the flow charts of a data query method provided by an embodiment of the present invention; Figure 2 A second flowchart of a data query method provided by an embodiment of the present invention; Figure 3 One of the scenario schematic diagrams of a data query method provided by an embodiment of the present invention; Figure 4 A second schematic diagram of a scenario of a data query method provided by an embodiment of the present invention; Figure 5 A third scenario diagram of a data query method provided by an embodiment of the present invention; Figure 6 A schematic diagram of the module composition of a data query device 600 provided in one embodiment of the present invention; Figure 7 A schematic diagram of the hardware structure of a data query device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0013] In order to make the technical parties in this technical field better understand the technical aspects of one or more embodiments of the present disclosure, and to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in combination with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0014] The technical solutions provided by various embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0015] See also Figure 1 , Figure 1 One of the flow charts of a data query method provided by an embodiment of the present invention is as follows: Figure 1 As shown, the method comprises the following steps: Step 102: Obtain insurance data generated within a preset time period and at least one insurance merchant that generates the insurance data.

[0016] Step 104: Determine the insurance data corresponding to each insurance merchant in the insurance data.

[0017] Step 106: associate the merchant attribute data of each insurance merchant with the insurance data corresponding to each insurance merchant to obtain the to-be-queried data corresponding to each insurance merchant; the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type.

[0018] Step 108: According to the received query request for any insurance merchant, target data is determined from the to-be-queried data corresponding to any insurance merchant.

[0019] In the embodiment of the present invention, insurance data generated within a preset time period and at least one insurance merchant that generated the insurance data may be acquired first.

[0020] In one example, when obtaining insurance data generated within a preset time period, you can obtain the insurance data generated in the previous month, or you can obtain all insurance data generated up to the beginning of this month, or you can obtain all insurance data generated from the last time you obtained insurance data to the current time you obtain insurance data. The preset time period can be set according to demand, and this example does not limit this.

[0021] When obtaining insurance data generated within a preset time period, the full amount of data can be obtained from the warehouse storing the data first, and then the data is extracted to the BL (Business List) layer to obtain the insurance data.

[0022] When obtaining the insurance merchant that generates the insurance data, it can be determined based on the insurance data, or it can be directly determined based on the insurance merchants that have been registered and are in business within the above-mentioned preset time period, and the embodiment of the present invention does not limit this.

[0023] After obtaining the insurance data and insurance merchants, the insurance data corresponding to each insurance merchant in the insurance data may be determined.

[0024] The insurance data can first be summarized according to preset indicators to obtain an indicator summary table, and the insurance data in the indicator summary table can be classified according to the type of business to obtain at least one business classification table. Then, the insurance data in the business classification table can be summarized according to the insurance merchants to obtain a merchant summary table, and the insurance data corresponding to each insurance merchant in the insurance data can be determined based on the merchant summary table.

[0025] In an example, see Figure 2 The insurance data obtained can be a list table at the policy granularity, for example, it can be a list table such as a policy information table, a vehicle dimension information table, a car insurance claim settlement table, and a car insurance premium earned table. These list tables can be summarized into a table at the S layer (i.e., the summary dimension) according to the preset indicator dimension to obtain an indicator summary table, and then they can be summarized into APP (Application) tables of different business types such as underwriting, claims, damage assessment, and repair according to the business type to obtain at least one business classification table, and finally the data in multiple APP tables are integrated into one table according to the merchant granularity to obtain a merchant summary table, so as to determine the insurance data corresponding to each insurance merchant according to the merchant summary table.

[0026] After the insurance data corresponding to each insurance merchant is determined, the merchant attribute data of each insurance merchant may be associated with the insurance data corresponding to each insurance merchant to obtain the to-be-queried data corresponding to each insurance merchant.

[0027] The merchant attribute data of each insurance merchant may be obtained. In one example, the merchant attribute data may include at least one of the following: merchant name, merchant location, merchant type. The merchant type may be determined according to the merchant's main business type, such as 4S store, second-hand network, repair shop, etc., which is not limited in this example.

[0028] In an example, the merchant attribute data of each insurance merchant and the target indicator in the insurance data corresponding to each insurance merchant can be determined according to a preset indicator combination, and the indicator combination value can be determined according to the value of the target indicator. At this time, after the merchant attribute data of each insurance merchant is associated with the insurance data corresponding to each insurance merchant, they can be summarized into a large wide table of insurance merchants, which contains, in addition to the original attribute data and insurance data, calculated combined indicator data corresponding to the preset indicator combination.

[0029] Considering that when associating the merchant attribute data of each insurance merchant with the insurance data corresponding to each insurance merchant, the GBase database is usually used for association, and GBase provides both computing and query capabilities. If there are many computing tasks, GBase resource consumption is large, which will affect the query and use of the required indicators. Therefore, the indicator combination data calculated according to different dimensional combinations will be synchronized to the Oracle library to support query operations of each combination.

[0030] After obtaining the to-be-queried data corresponding to each of the insurance merchants, the to-be-queried data corresponding to each of the insurance merchants can be displayed through the front-end interface according to the preset display type. In one example, the preset display type may include dimensions such as business source, whether it is a family car, and service manager type.

[0031] When a query request for any insurance merchant is received, the target data can be determined from the data to be queried corresponding to any insurance merchant according to the query request received for any insurance merchant, and the displayable data for the current user can be determined from the data to be queried corresponding to each insurance merchant according to the viewing authority of the current user, and the displayable data can be displayed through the front-end interface according to the preset display type.

[0032] In one example, the front-end interface can display the insurance merchant information within the current user's viewing permission range. The user can select dimensions such as business source, whether it is a family car, and service manager type through visual selection. The user's viewing permission can be set to: users of provinces, cities, and county branches can only view the data of insurance merchants belonging to the provinces, cities, and county branches. In addition, the indicators that users have viewing permissions can be limited according to the user's level.

[0033] In this example, to prevent the query time from being too long due to excessive data, the user can be limited to select at least one or some indicators in the filter box before the data is displayed. For example, the data can be displayed only after the user selects at least one of the following: province, recommended repair code, sub-channel type, whether it is a family car, project name, whether the premium for the current year is zero, and whether the assessed loss amount for the current year is zero.

[0034] In one example, if Figure 3 and Figure 4As shown, the front-end interface can divide the indicators selected during visualization into four categories according to the business type: underwriting, claims, damage assessment, and repair. Users can select the required related indicators in a personalized manner, either individually or in full. The fields in the large wide table will be matched according to the indicators selected by the user, and then a query SQL will be generated to extract the corresponding indicators and display them. Fields that are not selected will not be displayed. If the display indicators are not filtered, the fields in the large wide table will not be matched, and only the pre-configured basic information of the insurance merchant will be displayed.

[0035] In one embodiment of the present invention, stores within a limited range can be imported in batches to achieve automatic extraction of individual insurance merchant data and summary data. The present invention can replace the manual writing of SQL script code to extract data, and control parameter transmission through the Java front end to achieve different dimensions of data combination, automatically generate SQL files, and achieve automatic data extraction and summary.

[0036] For example, after the user clicks the [Import] button, they can batch import merchants within a limited range, import push codes and store them in a specified table, generate a file number with year, month, day, hour, minute and second, import the unique file number and store range into the specified table, and then query various indicators of the imported stores based on the association between the unique file number and the merchant wide table.

[0037] In this example, the query results not only display the data of a single insurance merchant, but also automatically calculate a corresponding summary data of all insurance merchants to help users understand the overall situation.

[0038] In the embodiment of the present invention, when there is too much data to query, it takes a long time to extract the data. In this case, a queue extraction can be set. The query information can be recorded in the download list query table, and monitoring warnings can be set. When an error is reported during the query task, the operation and maintenance personnel can be notified by SMS in time to respond quickly. In addition, the operation log of each query task can be recorded to ensure that the problem can be located and solved in time.

[0039] In one example, if Figure 5 As shown, after the data query is completed, the corresponding Excel file can be generated according to the query results, and the user is prompted to download on the list download interface, and permission control is set. The logged-in user can only view the list file of the data he extracted.

[0040] In an embodiment of the present invention, insurance data generated within a preset time period and at least one insurance merchant that generates the insurance data can be first obtained, and the insurance data corresponding to each insurance merchant in the insurance data can be determined. Then, the merchant attribute data of each insurance merchant can be associated with the insurance data corresponding to each insurance merchant to obtain the data to be queried corresponding to each insurance merchant, wherein the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type. After receiving a query request for any insurance merchant, the target data is determined from the data to be queried corresponding to any insurance merchant according to the received query request for any insurance merchant.

[0041] It can be seen from the above-mentioned embodiments of the invention that after obtaining the insurance data, the embodiments of the present invention can first determine the insurance merchant that generates the insurance data, and then determine the insurance data corresponding to each insurance merchant with the insurance merchant as the granularity, and further associate the merchant attribute data of the insurance merchant with the insurance data corresponding to the insurance merchant, so as to obtain more comprehensive data with the insurance merchant as the granularity to support data query for any insurance merchant. When a query request for any insurance merchant is received, the more comprehensive data corresponding to the insurance merchant can be directly obtained, and the target data corresponding to the query request can be obtained therefrom. Since the content to be queried can be accurately located with the insurance merchant as the dimension, the problem of repeated query and waste of manpower and computing resources caused by performing data query with the condition combination of each demand as the dimension in the related technology can be effectively solved.

[0042] Corresponding to the above data query method, an embodiment of the present invention further provides a data query device, Figure 6 A schematic diagram of the module composition of a data query device 600 provided in an embodiment of the present invention is shown in FIG. Figure 6 As shown, the data query device 600 includes: An acquisition module 601 is used to acquire insurance data generated within a preset time period and at least one insurance merchant that generates the insurance data; A determination module 602 is used to determine the insurance data corresponding to each of the insurance merchants in the insurance data; The association module 603 is used to associate the merchant attribute data of each of the insurance merchants with the insurance data corresponding to each of the insurance merchants to obtain the to-be-queried data corresponding to each of the insurance merchants; the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type; The query module 604 is used to determine target data from the to-be-queried data corresponding to any of the insurance merchants according to the received query request for any of the insurance merchants.

[0043] Optionally, the determining module 602 is used to: According to the preset indicators, the insurance data is summarized to obtain an indicator summary table; Classifying the insurance data in the indicator summary table according to the type of business to which it belongs, to obtain at least one business classification table; According to the insurance merchants, the insurance data in the business classification table are summarized to obtain a merchant summary table; The insurance data corresponding to each of the insurance merchants in the insurance data is determined according to the merchant summary table.

[0044] Optionally, the association module 603 is used to: According to a preset indicator combination, the merchant attribute data of each of the insurance merchants and the target indicator in the insurance data corresponding to each of the insurance merchants are determined, and according to the value of the target indicator, the indicator combination value is determined.

[0045] Optionally, the device further comprises ( Figure 6 not shown): The first display module 605 is used to display the data to be queried corresponding to each insurance merchant through a front-end interface according to a preset display type after obtaining the data to be queried corresponding to each insurance merchant.

[0046] Optionally, the first display module 605 is used for: According to the viewing authority of the current user, determine the displayable data for the current user from the to-be-queried data corresponding to each of the insurance merchants; The displayable data is displayed through a front-end interface according to a preset display type.

[0047] Optionally, the device further comprises ( Figure 6 not shown): The second display module 606 is used to display the data to be displayed in the target data corresponding to the query data type through the front-end interface after the target data is determined from the data to be queried corresponding to any of the insurance merchants.

[0048] In an embodiment of the present invention, insurance data generated within a preset time period and at least one insurance merchant that generates the insurance data can be first obtained, and the insurance data corresponding to each insurance merchant in the insurance data can be determined. Then, the merchant attribute data of each insurance merchant can be associated with the insurance data corresponding to each insurance merchant to obtain the data to be queried corresponding to each insurance merchant, wherein the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type. After receiving a query request for any insurance merchant, the target data is determined from the data to be queried corresponding to any insurance merchant according to the received query request for any insurance merchant.

[0049] It can be seen from the above-mentioned embodiments of the invention that after obtaining the insurance data, the embodiments of the present invention can first determine the insurance merchant that generates the insurance data, and then determine the insurance data corresponding to each insurance merchant with the insurance merchant as the granularity, and further associate the merchant attribute data of the insurance merchant with the insurance data corresponding to the insurance merchant, so as to obtain more comprehensive data with the insurance merchant as the granularity to support data query for any insurance merchant. When a query request for any insurance merchant is received, the more comprehensive data corresponding to the insurance merchant can be directly obtained, and the target data corresponding to the query request can be obtained therefrom. Since the content to be queried can be accurately located with the insurance merchant as the dimension, the problem of repeated query and waste of manpower and computing resources caused by performing data query with the condition combination of each demand as the dimension in the related technology can be effectively solved.

[0050] Corresponding to the above data query method, an embodiment of the present invention further provides a data query device, Figure 7 A schematic diagram of the hardware structure of a data query device provided by one embodiment of the present invention.

[0051] The data query device may be a terminal device or a server for querying data provided in the above embodiment.

[0052] The data query device may have relatively large differences due to different configurations or performances, and may include one or more processors 701 and memory 702, and the memory 702 may store one or more storage applications or data. Among them, the memory 702 may be a short-term storage or a persistent storage. The application stored in the memory 702 may include one or more modules (not shown in the figure), and each module may include a series of computer executable instructions in the data query device. Furthermore, the processor 701 may be configured to communicate with the memory 702, and execute a series of computer executable instructions in the memory 702 on the data query device. The data query device may also include one or more power supplies 703, one or more wired or wireless network interfaces 704, one or more input and output interfaces 705, and one or more keyboards 706.

[0053] Specifically in this embodiment, the data query device includes a memory and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may include one or more modules, and each module may include a series of computer executable instructions in the data query device, and is configured to be executed by one or more processors.

[0054] In an embodiment of the present invention, insurance data generated within a preset time period and at least one insurance merchant that generates the insurance data can be first obtained, and the insurance data corresponding to each insurance merchant in the insurance data can be determined. Then, the merchant attribute data of each insurance merchant can be associated with the insurance data corresponding to each insurance merchant to obtain the data to be queried corresponding to each insurance merchant, wherein the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type. After receiving a query request for any insurance merchant, the target data is determined from the data to be queried corresponding to any insurance merchant according to the received query request for any insurance merchant.

[0055] It can be seen from the above-mentioned embodiments of the invention that after obtaining the insurance data, the embodiments of the present invention can first determine the insurance merchant that generates the insurance data, and then determine the insurance data corresponding to each insurance merchant with the insurance merchant as the granularity, and further associate the merchant attribute data of the insurance merchant with the insurance data corresponding to the insurance merchant, so as to obtain more comprehensive data with the insurance merchant as the granularity to support data query for any insurance merchant. When a query request for any insurance merchant is received, the more comprehensive data corresponding to the insurance merchant can be directly obtained, and the target data corresponding to the query request can be obtained therefrom. Since the content to be queried can be accurately located with the insurance merchant as the dimension, the problem of repeated query and waste of manpower and computing resources caused by performing data query with the condition combination of each demand as the dimension in the related technology can be effectively solved.

[0056] Another embodiment of the present disclosure further provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store computer-executable instructions, and the computer-executable instructions implement the above process when executed by a processor.

[0057] The storage medium in the embodiment of the present disclosure can implement each process of the above-mentioned data query method embodiment and achieve the same effect and function, which will not be repeated here.

[0058] Another embodiment of the present disclosure further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the above process is implemented.

[0059] The computer program product in the embodiment of the present disclosure can implement each process of the above-mentioned data query method embodiment and achieve the same effect and function, which will not be repeated here.

[0060] In various embodiments of the present disclosure, the computer-readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0061] In the 1990s, it was very clear whether the improvement of a technology was hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or software improvement (improvement of the method flow). However, with the development of technology, many improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming themselves, without having to ask chip manufacturers to design and make dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0062] The controller may be implemented in any suitable manner, for example, the controller may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, and the memory controller may also be implemented as part of the control logic of the memory. It is also known to those skilled in the art that, in addition to implementing the controller in a purely computer-readable program code manner, the controller may be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a controller may be considered as a hardware component, and the devices for implementing various functions included therein may also be considered as structures within the hardware component. Or even, the devices for implementing various functions may be considered as both software modules for implementing the method and structures within the hardware component.

[0063] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0064] For the convenience of description, the above devices are described in terms of functions and are divided into various units. Of course, when implementing the embodiments of the present disclosure, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0065] It should be understood by those skilled in the art that one or more embodiments of the present disclosure may be provided as a method, system or computer program product. Therefore, one or more embodiments of the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, one or more embodiments of the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0066] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0067] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0068] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0069] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0070] One or more embodiments of the present disclosure may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. One or more embodiments of the present disclosure may also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0071] Each embodiment in the present disclosure is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0072] The above description is only an embodiment of the present disclosure and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the scope of the claims of the present disclosure.

Claims

1. A data query method, characterized in that: The method comprises: Acquire insurance data generated within a preset time period, and at least one insurance merchant that generates the insurance data; Determine the insurance data corresponding to each of the insurance merchants in the insurance data; Associating the merchant attribute data of each of the insurance merchants with the insurance data corresponding to each of the insurance merchants to obtain the to-be-queried data corresponding to each of the insurance merchants; the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type; According to the received query request for any of the insurance merchants, target data is determined from the to-be-queried data corresponding to any of the insurance merchants.

2. The method according to claim 1, characterized in that The determining of the insurance data corresponding to each of the insurance merchants in the insurance data includes: According to the preset indicators, the insurance data is summarized to obtain an indicator summary table; Classifying the insurance data in the indicator summary table according to the type of business to which it belongs, to obtain at least one business classification table; Summarize the insurance data in the business classification table according to the insurance merchants to which they belong, and obtain a merchant summary table; The insurance data corresponding to each of the insurance merchants in the insurance data is determined according to the merchant summary table.

3. The method according to claim 1, characterized in that The associating the merchant attribute data of each of the insurance merchants with the insurance data corresponding to each of the insurance merchants includes: According to a preset indicator combination, the merchant attribute data of each of the insurance merchants and the target indicator in the insurance data corresponding to each of the insurance merchants are determined, and according to the value of the target indicator, the indicator combination value is determined.

4. The method according to claim 1, characterized in that: After obtaining the to-be-queried data corresponding to each of the insurance merchants, the method further includes: According to the preset display type, the data to be queried corresponding to each of the insurance merchants is displayed through the front-end interface.

5. The method according to claim 4, characterized in that The display of the to-be-queried data corresponding to each of the insurance merchants through the front-end interface according to the preset display type includes: According to the viewing authority of the current user, determine the displayable data for the current user from the to-be-queried data corresponding to each of the insurance merchants; The displayable data is displayed through the front-end interface according to the preset display type.

6. The method according to claim 4, characterized in that The query request includes at least one query data type. After determining the target data from the to-be-queried data corresponding to any of the insurance merchants, the method further includes: The data to be displayed in the target data corresponding to the query data type is displayed through the front-end interface.

7. A data query device, characterized in that: The device comprises: An acquisition module, used to acquire insurance data generated within a preset time period, and at least one insurance merchant that generates the insurance data; A determination module, used to determine the insurance data corresponding to each of the insurance merchants in the insurance data; An association module is used to associate the merchant attribute data of each of the insurance merchants with the insurance data corresponding to each of the insurance merchants to obtain the to-be-queried data corresponding to each of the insurance merchants; the merchant attribute data includes at least one of the following: merchant name, merchant location, merchant type; The query module is used to determine target data from the to-be-queried data corresponding to any of the insurance merchants according to a received query request for any of the insurance merchants.

8. A data query device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the method according to any one of claims 1 to 6 when executed by the processor.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store computer-executable instructions, and when the computer-executable instructions are executed by a processor, the steps of the method described in any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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