CN115422318A - Business data analysis method and device, storage medium and computer equipment - Google Patents
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Abstract
The application provides a business data analysis method, a business data analysis device, a storage medium and computer equipment. The method comprises the following steps: acquiring a data analysis instruction; determining a target grid and an analysis task according to the data analysis instruction; the target grid is at least one of the grids defined in the map page based on the map API interface, and each grid corresponds to a district scope; determining the type of data to be analyzed and a data processing rule corresponding to the analysis task according to the analysis task; determining a target district range according to the target grid; acquiring geographic coordinate information in a database, wherein the geographic coordinate information belongs to the range of the target district and is data of the type of the data to be analyzed as target data; and processing the target data according to the data processing rule to obtain a data analysis result. The method and the device can dynamically adjust the data range, expand the application range and meet the analysis requirements of banking business.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for analyzing business data, a storage medium, and a computer device.
Background
With the development of the internet industry and the popularization of mobile applications, software service manufacturers increasingly perform data analysis based on geographic location information, such as population data analysis based on administrative divisions, user behavior analysis, preference analysis and the like, and product recommendation based on geographic information positioning, such as take-out industry, group buying, community group buying and the like. However, the data analysis has low flexibility, the data range cannot be dynamically adjusted according to needs, and the use scene is solidified, so that the bank business analysis requirements are difficult to meet.
Disclosure of Invention
The embodiment of the application provides a business data analysis method, a business data analysis device, a storage medium and computer equipment, which can dynamically adjust the data range, enlarge the application range and meet the bank business analysis requirements.
In a first aspect, the present application provides a method for analyzing business data, where the method includes:
acquiring a data analysis instruction;
determining a target grid and an analysis task according to the data analysis instruction; the target grid is at least one of the grids defined in the map page based on the map API interface, and each grid corresponds to a district scope;
determining the type of data to be analyzed and a data processing rule corresponding to the analysis task according to the analysis task;
determining a target district range according to the target grid;
acquiring geographic coordinate information in a database, wherein the geographic coordinate information belongs to the range of the target district and is data of the type of the data to be analyzed as target data;
and processing the target data according to the data processing rule to obtain a data analysis result.
In one embodiment, defining a grid in a map page based on a map API interface includes:
responding to a grid creating instruction, and establishing a data transmission channel between the map page and a database through a map API (application programming interface);
determining a grid level and a grid name according to the grid creating instruction;
identifying boundary points marked by a user in the map page; wherein the number of the boundary points is not less than three;
determining a scope corresponding to the currently created grid based on a region enclosed and constructed by the marked boundary points;
generating geographic coordinate information of the district range according to the regional coordinates covered by the district range in the map page;
establishing an association relation between the geographic coordinate information of the district scope and the grid hierarchy and the grid name to generate grid data;
and storing the grid data to the database through the data transmission channel.
In one embodiment, the identifying the boundary point marked by the user in the map page further includes:
and if the lower-level grid is determined to be created in the selected existing grid level according to the grid creation instruction, limiting the selectable range of the boundary point in the map page within the scope corresponding to the selected existing grid level.
In one embodiment, if it is determined according to the mesh creation instruction that a lower mesh is created in the selected existing mesh hierarchy, executing the map API interface to define a mesh in a map page further includes:
and establishing a hierarchical association relationship between the currently generated grid data and the selected existing grid hierarchy.
In one embodiment, the grid hierarchy includes a bank organization hierarchy and a bank organization employee hierarchy.
In one embodiment, the acquiring geographic coordinate information in the database belongs to the target prefecture range, and the data of the type of the data to be analyzed is used as target data, including:
primarily screening the data in the database according to the type of the data to be analyzed to obtain the data to be analyzed;
identifying the geographic coordinate information of each piece of data in the data to be analyzed;
and comparing the geographic coordinate information covered by the target region scope with the geographic coordinate information of each piece of data in the data to be analyzed, and screening out the target data belonging to the target region scope.
In one embodiment, the method further comprises:
generating a data report based on the data analysis result;
and displaying the data report.
In a second aspect, the present application provides a service data analysis apparatus, including:
the instruction acquisition module is used for acquiring a data analysis instruction;
the instruction analysis module is used for determining a target grid and an analysis task according to the data analysis instruction; the target grid is at least one of grids defined in a map page based on a map API interface, and each grid corresponds to a district scope;
the first determining module is used for determining the type of the data to be analyzed and a data processing rule corresponding to the analysis task according to the analysis task;
the second determining module is used for determining a target district scope according to the target grid;
the target data acquisition module is used for acquiring the geographic coordinate information in the database, belonging to the range of the target jurisdiction, and taking the data of the type of the data to be analyzed as target data;
and the data processing module is used for processing the target data according to the data processing rule to obtain a data analysis result.
In a third aspect, the present application provides a storage medium having stored therein computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the business data analysis method according to any one of the embodiments described above.
In a fourth aspect, the present application provides a computer device comprising: one or more processors, and a memory;
the memory has stored therein computer readable instructions which, when executed by the one or more processors, perform the steps of the business data analysis method according to any one of the embodiments described above.
According to the technical scheme, the embodiment of the application has the following advantages:
according to the business data analysis method, the business data analysis device, the storage medium and the computer equipment, after the data analysis instruction is obtained, the data analysis instruction is analyzed to determine the geographic position range which needs to be subjected to business data analysis currently, namely, at least one grid in the grids defined in a map page through a map API (application programming interface) is determined as a target grid, each grid corresponds to a jurisdiction range, the analysis task which needs to be executed currently is determined, the type of data to be analyzed and a data processing rule are determined according to the analysis task, the target data is obtained from a database based on the type of the data to be analyzed and the target jurisdiction range corresponding to the target grid, and the target data is processed according to the data processing rule to obtain a data analysis result. The method has the advantages that the grids which can be defined through the map page and the selectable data processing rules are utilized, the required data range and the processing logic can be dynamically adjusted according to needs, the selection can be carried out according to specific business analysis needs, the method is applicable to more diversified data analysis scenes, and the diversified use scenes with the banking business needs can be matched.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
FIG. 1 is a flow chart illustrating a business data analysis method according to an embodiment;
FIG. 2 is a flowchart illustrating the step of defining a grid in a map page based on a map API interface in one embodiment;
FIG. 3 is a block diagram of a business data analysis device according to an embodiment;
FIG. 4 is a diagram of the internal structure of a computer device in one embodiment.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
As shown in fig. 1, an embodiment of the present application provides a business data analysis method, where the method includes steps S101 to S106, where:
step S101, a data analysis instruction is obtained.
The data analysis instruction is an instruction which is input by a user and used for triggering a data analysis task, and the data analysis instruction comprises a target grid and an analysis task which are selected by the currently triggered data analysis task. Data analysis instructions are input through the interaction page, and in one embodiment, the data analysis instructions can be generated by selecting a target network and analyzing a task.
And S102, determining a target grid and an analysis task according to the data analysis instruction.
The target grid is at least one of the grids defined in the map page based on the map API, and each grid corresponds to a district scope. Jurisdictional coverage refers to the area covered by a defined grid.
And step S103, determining the type of the data to be analyzed and the data processing rule corresponding to the analysis task according to the analysis task.
The data type to be analyzed refers to a data type corresponding to data that needs to be processed by an analysis task, and the data type may be determined by classifying data sources according to different usage scenarios and according to requirements, for example, the data type may be customer information or standing population information of a certain parcel obtained through a legal authorization way. The data of different data types may have partial overlap, and the duplicate removal processing is not performed on the overlapped data of different data types.
The data processing rules may be selected from a pre-configured rule base or may be configured upon input of a data analysis instruction.
And step S104, determining a target district range according to the target grid.
Step S105, acquiring the geographic coordinate information in the database, wherein the geographic coordinate information belongs to the range of the target district, and the data is data of the type of the data to be analyzed and serves as target data.
The target data simultaneously meets the conditions that the data type is the data type to be analyzed and the geographic coordinate information belongs to the range of the target region, and the target data can be obtained by screening the data in the database through the determined range of the target region and the data type to be analyzed.
In one embodiment, the data in the database is preliminarily screened according to the type of the data to be analyzed to obtain the data to be analyzed; identifying geographic coordinate information of each piece of data in the data to be analyzed; and comparing the geographic coordinate information covered by the target region scope with the geographic coordinate information of each piece of data in the data to be analyzed, and screening out the target data belonging to the target region scope.
The data types can be identified through the fields, the data types to be analyzed are field values, and the data to be analyzed can be quickly selected by searching based on the field values.
And step S106, processing the target data according to the data processing rule to obtain a data analysis result.
And correspondingly processing the screened target data according to the selected data processing rule to obtain a data analysis result, for example, if the data analysis task is to analyze the service maturity in a certain grid, the data processing rule of the service maturity is that the number of the clients accounts for the number of the standing population, the target data comprises the client information in the range of the target district and the standing population information in the range of the target district, and the ratio of the number of the clients in the range of the target district to the number of the standing population is calculated to obtain the service maturity.
In this embodiment, after the data analysis instruction is obtained, the data analysis instruction is analyzed to determine a geographic position range where service data analysis is currently required, that is, at least one grid of grids defined in a map page through a map API interface is determined as a target grid, each grid corresponds to a jurisdiction range, and an analysis task that is currently required to be executed is determined, a data type to be analyzed and a data processing rule are determined according to the analysis task, target data is obtained from a database based on the data type to be analyzed and the target jurisdiction range corresponding to the target grid, and the target data is processed according to the data processing rule, so that a data analysis result is obtained. The method has the advantages that the grids which can be defined through the map page and the selectable data processing rules are utilized, the required data range and the processing logic can be dynamically adjusted according to needs, the selection can be carried out according to specific business analysis needs, the method is applicable to more diversified data analysis scenes, and the diversified use scenes with the bank business needs can be matched.
As shown in fig. 2, in one embodiment, defining a grid in a map page based on a map API interface includes steps S201 to S207, in which:
step S201, responding to the grid creating instruction, and establishing a data transmission channel between the map page and the database through a map API interface.
The map API is an API for embedding a map into a web page through JavaScript (or other language) to process the map and add contents to the map through various services. The grid creation instruction is a creation instruction input by a user when the grid needs to be defined.
Step S202, grid hierarchy and grid name are determined according to the grid creation instruction.
The multi-level grid may be set as needed, for example, the first-level grid is the highest level, taking banking as an example, the first-level grid may correspond to a head office, the second-level grid is a lower-level grid of the first-level grid, and may correspond to a branch office of a bank, and the third-level grid is a lower-level grid of the second-level grid, and may correspond to a staff member belonging to the branch office. The mesh hierarchy to be created currently may be selected when creating the mesh, and the mesh created currently is not named.
In one embodiment, the grid hierarchy includes a bank organization hierarchy and a bank organization employee hierarchy. One or more levels can be arranged below the bank organization level; one or more levels may also be set below the bank organization employee level.
In step S203, the boundary points marked by the user in the map page are identified.
The number of the boundary points is not less than three, so that the boundary points selected by a user can construct a closed area range.
And if the lower-level grid is determined to be created in the selected existing grid level according to the grid creation instruction, limiting the selectable range of the boundary point in the map page within the scope corresponding to the selected existing grid level.
If the lower-level grid is not created in the existing grid hierarchy, the selectable range of the boundary points in the map page is not limited. In some embodiments, there may be overlapping regions of jurisdictional ranges for grids of the same hierarchy. In other embodiments, the jurisdictional ranges of the same level of the grid cannot have overlapping regions.
And S204, determining the scope of the district corresponding to the currently created grid based on the area enclosed and constructed by the marked boundary points.
And S205, generating geographic coordinate information of the scope of the jurisdiction according to the area coordinate covered by the scope of the jurisdiction in a map page.
And determining the geographical coordinate information of each boundary point in the map based on the marked boundary points through a map API (application programming interface), and further determining the geographical coordinate information of the coverage area of the district area by combining the map.
Step S206, establishing an association relation between the geographic coordinate information of the district scope and the grid hierarchy and the grid name, and generating grid data.
And step S207, storing the grid data to the database through the data transmission channel.
In the embodiment, the grids can be flexibly created in a mode of marking boundary points in the map page according to the use scene, and the grids of different levels can be created as required, so that a basis is provided for flexibly adjusting the data range of the business data analysis.
In one embodiment, if it is determined according to the mesh creation instruction that a lower mesh is created in the selected existing mesh hierarchy, executing the map API interface to define a mesh in a map page further includes:
and establishing a hierarchical association relationship between the currently generated grid data and the selected existing grid hierarchy.
By establishing the incidence relation of the grids of the upper and lower layers, a user can conveniently and quickly find the required layer grid according to the layers when inputting a data analysis instruction.
In one embodiment, the method further comprises:
generating a data report based on the data analysis result;
and displaying the data report.
It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.
The service data analysis device provided in the embodiment of the present application is described below, and the service data analysis device described below and the service data analysis method described above may be referred to correspondingly.
As shown in fig. 3, an embodiment of the present application provides a service data analysis apparatus 300, including:
an instruction obtaining module 301, configured to obtain a data analysis instruction;
the instruction analysis module 302 is configured to determine a target grid and an analysis task according to the data analysis instruction; the target grid is at least one of the grids defined in the map page based on the map API interface, and each grid corresponds to a district scope;
a first determining module 303, configured to determine, according to the analysis task, a type of data to be analyzed and a data processing rule corresponding to the analysis task;
a second determining module 304, configured to determine a target jurisdiction range according to the target grid;
a target data obtaining module 305, configured to obtain that geographic coordinate information in a database belongs to the target jurisdiction range, and is data of the type of the data to be analyzed as target data;
and the data processing module 306 is configured to process the target data according to the data processing rule to obtain a data analysis result.
In one embodiment, the service data analysis device further includes: a grid definition module configured to perform the steps of:
responding to a grid creating instruction, and establishing a data transmission channel between the map page and a database through a map API (application programming interface);
determining a grid level and a grid name according to the grid creating instruction;
identifying boundary points marked by a user in the map page; wherein the number of the boundary points is not less than three;
determining a scope corresponding to the currently created grid based on a region enclosed and constructed by the marked boundary points;
generating geographic coordinate information of the district range according to the regional coordinates covered by the district range in the map page;
establishing an association relation between the geographic coordinate information of the district scope and the grid hierarchy and the grid name to generate grid data;
and storing the grid data to the database through the data transmission channel.
In one embodiment, the grid definition module is further configured to perform:
and if the lower-level grid is determined to be created in the selected existing grid level according to the grid creation instruction, limiting the selectable range of the boundary point in the map page within the scope corresponding to the selected existing grid level.
In one embodiment, the grid definition module is further configured to perform:
and if the lower level grid is determined to be created in the selected existing grid level according to the grid creation instruction, establishing a level association relationship between the currently generated grid data and the selected existing grid level.
In one embodiment, the target data acquisition module is configured to perform the steps of:
primarily screening the data in the database according to the type of the data to be analyzed to obtain the data to be analyzed;
identifying the geographic coordinate information of each piece of data in the data to be analyzed;
and comparing the geographic coordinate information covered by the target region scope with the geographic coordinate information of each piece of data in the data to be analyzed, and screening out the target data belonging to the target region scope.
In one embodiment, the service data analysis device further includes:
the report generation module is used for generating a data report based on the data analysis result;
and the display module is used for displaying the data report.
The division of each module in the service data analysis apparatus is merely for illustration, and in other embodiments, the service data analysis apparatus may be divided into different modules as needed to complete all or part of the functions of the service data analysis apparatus. All or part of each module in the business data analysis device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, the present application further provides a storage medium having computer-readable instructions stored therein, which when executed by one or more processors, cause the one or more processors to perform the steps of:
acquiring a data analysis instruction;
determining a target grid and an analysis task according to the data analysis instruction; the target grid is at least one of the grids defined in the map page based on the map API interface, and each grid corresponds to a district scope;
determining the type of data to be analyzed and a data processing rule corresponding to the analysis task according to the analysis task;
determining a target district range according to the target grid;
acquiring geographic coordinate information in a database, wherein the geographic coordinate information belongs to the range of the target jurisdiction and is data of the type of the data to be analyzed as target data;
and processing the target data according to the data processing rule to obtain a data analysis result.
In one embodiment, the computer readable instructions when executed by the processor further implement the steps of:
responding to a grid creating instruction, and establishing a data transmission channel between the map page and a database through a map API (application programming interface);
determining a grid level and a grid name according to the grid creating instruction;
identifying boundary points marked by a user in the map page; wherein the number of the boundary points is not less than three;
determining the scope corresponding to the currently created grid based on the area enclosed and constructed by the marked boundary points;
generating geographical coordinate information of the scope according to the area coordinates covered by the scope of the scope in the map page;
establishing an association relation between the geographic coordinate information of the district scope and the grid hierarchy and the grid name to generate grid data;
and storing the grid data to the database through the data transmission channel.
In one embodiment, the computer readable instructions when executed by the processor further implement the steps of:
and if the lower-level grid is determined to be created in the selected existing grid level according to the grid creation instruction, limiting the selectable range of the boundary point in the map page within the scope corresponding to the selected existing grid level.
In one embodiment, the computer readable instructions when executed by the processor further implement the steps of:
and establishing a hierarchical association relationship between the currently generated grid data and the selected existing grid hierarchy.
In one embodiment, the computer readable instructions when executed by the processor further implement the steps of:
primarily screening the data in the database according to the type of the data to be analyzed to obtain the data to be analyzed;
identifying the geographic coordinate information of each piece of data in the data to be analyzed;
and comparing the geographic coordinate information covered by the target region scope with the geographic coordinate information of each piece of data in the data to be analyzed, and screening out the target data belonging to the target region scope.
In one embodiment, the computer readable instructions when executed by the processor further implement the steps of:
generating a data report based on the data analysis result;
and displaying the data report.
In one embodiment, the present application further provides a computer device having computer-readable instructions stored therein, which when executed by the one or more processors, perform the steps of:
acquiring a data analysis instruction;
determining a target grid and an analysis task according to the data analysis instruction; the target grid is at least one of the grids defined in the map page based on the map API interface, and each grid corresponds to a district scope;
determining the type of data to be analyzed and a data processing rule corresponding to the analysis task according to the analysis task;
determining a target district range according to the target grid;
acquiring geographic coordinate information in a database, wherein the geographic coordinate information belongs to the range of the target district and is data of the type of the data to be analyzed as target data;
and processing the target data according to the data processing rule to obtain a data analysis result.
In one embodiment, the processor, when executing the computer readable instructions, further performs the steps of:
responding to a grid creating instruction, and establishing a data transmission channel between the map page and a database through a map API (application programming interface);
determining a grid level and a grid name according to the grid creating instruction;
identifying boundary points marked by a user in the map page; wherein the number of the boundary points is not less than three;
determining a scope corresponding to the currently created grid based on a region enclosed and constructed by the marked boundary points;
generating geographic coordinate information of the district range according to the regional coordinates covered by the district range in the map page;
establishing an association relation between the geographic coordinate information of the district scope and the grid hierarchy and the grid name to generate grid data;
and storing the grid data to the database through the data transmission channel.
In one embodiment, the processor when executing the computer readable instructions further performs the steps of:
and if the lower-level grid is determined to be created in the selected existing grid level according to the grid creation instruction, limiting the selectable range of the boundary point in the map page within the scope corresponding to the selected existing grid level.
In one embodiment, the processor, when executing the computer readable instructions, further performs the steps of:
and establishing a hierarchical association relationship between the currently generated grid data and the selected existing grid hierarchy.
In one embodiment, the processor, when executing the computer readable instructions, further performs the steps of:
primarily screening the data in the database according to the type of the data to be analyzed to obtain the data to be analyzed;
identifying the geographic coordinate information of each piece of data in the data to be analyzed;
and comparing the geographic coordinate information covered by the target region scope with the geographic coordinate information of each piece of data in the data to be analyzed, and screening out the target data belonging to the target region scope.
In one embodiment, the processor when executing the computer readable instructions further performs the steps of:
generating a data report based on the data analysis result;
and displaying the data report.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 4. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a business data analysis method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), magnetic Random Access Memory (MRAM), ferroelectric Random Access Memory (FRAM), phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), for example. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specified otherwise.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, the embodiments may be combined as needed, and the same and similar parts may be referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for analyzing business data, the method comprising:
acquiring a data analysis instruction;
determining a target grid and an analysis task according to the data analysis instruction; the target grid is at least one of the grids defined in the map page based on the map API interface, and each grid corresponds to a district scope;
determining the type of data to be analyzed and a data processing rule corresponding to the analysis task according to the analysis task;
determining a target district range according to the target grid;
acquiring geographic coordinate information in a database, wherein the geographic coordinate information belongs to the range of the target district and is data of the type of the data to be analyzed as target data;
and processing the target data according to the data processing rule to obtain a data analysis result.
2. The business data analysis method of claim 1, wherein defining a grid in a map page based on a map API interface comprises:
responding to a grid creating instruction, and establishing a data transmission channel between the map page and a database through a map API (application programming interface);
determining a grid level and a grid name according to the grid creating instruction;
identifying boundary points marked by a user in the map page; wherein the number of the boundary points is not less than three;
determining a scope corresponding to the currently created grid based on a region enclosed and constructed by the marked boundary points;
generating geographic coordinate information of the district range according to the regional coordinates covered by the district range in the map page;
establishing an association relation between the geographic coordinate information of the district scope and the grid hierarchy and the grid name to generate grid data;
and storing the grid data to the database through the data transmission channel.
3. The business data analysis method of claim 2, wherein the identifying boundary points marked by the user in the map page further comprises:
and if the lower-level grid is determined to be created in the selected existing grid level according to the grid creation instruction, limiting the selectable range of the boundary point in the map page within the scope corresponding to the selected existing grid level.
4. The business data analyzing method of claim 3, wherein if it is determined according to the mesh creation command that a lower mesh is created in the selected existing mesh hierarchy, performing the map API interface to define a mesh in a map page, further comprises:
and establishing a hierarchical association relationship between the currently generated grid data and the selected existing grid hierarchy.
5. The business data analysis method of claim 3, wherein the grid hierarchy comprises a banking institution hierarchy and a banking institution employee hierarchy.
6. The business data analysis method according to claim 1, wherein the acquiring geographic coordinate information in the database belongs to the target jurisdiction range, and data of the type of the data to be analyzed is used as target data, and the method comprises:
primarily screening the data in the database according to the type of the data to be analyzed to obtain the data to be analyzed;
identifying the geographic coordinate information of each piece of data in the data to be analyzed;
and comparing the geographic coordinate information covered by the target region scope with the geographic coordinate information of each piece of data in the data to be analyzed, and screening out the target data belonging to the target region scope.
7. The traffic data analysis method according to claim 1, wherein the method further comprises:
generating a data report based on the data analysis result;
and displaying the data report.
8. A service data analysis apparatus, comprising:
the instruction acquisition module is used for acquiring a data analysis instruction;
the instruction analysis module is used for determining a target grid and an analysis task according to the data analysis instruction; the target grid is at least one of grids defined in a map page based on a map API interface, and each grid corresponds to a district scope;
the first determining module is used for determining the type of data to be analyzed and a data processing rule corresponding to the analysis task according to the analysis task;
the second determining module is used for determining a target district range according to the target grid;
the target data acquisition module is used for acquiring the geographic coordinate information in the database, belonging to the range of the target jurisdiction, and taking the data of the type of the data to be analyzed as target data;
and the data processing module is used for processing the target data according to the data processing rule to obtain a data analysis result.
9. A storage medium, characterized by: the storage medium has stored therein computer-readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the business data analysis method of any one of claims 1 to 7.
10. A computer device, comprising: one or more processors, and a memory;
the memory has stored therein computer-readable instructions which, when executed by the one or more processors, perform the steps of the business data analysis method of any one of claims 1 to 7.
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