Data screening method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention provides a data screening method and device, equipment, a storage medium and a program product. The method comprises the steps of obtaining an initial query condition which is input by a user and comprises an initial label and a data range; performing data screening on the business report according to the initial label and the data range to generate a current query result; querying the business model and the label mapping table based on the data source of the current query result to generate an associated label; receiving a target query instruction in the current display interface; performing data screening on the target business report according to an association tag in the target query instruction to generate a next-level query result; the business model and the label mapping table are queried based on the data source of the next-level query result to generate a new associated label; and receiving a report generation instruction in any display interface, and summarizing and outputting a multi-level query report according to the obtained multi-level query results. According to the method, multi-stage search can be realized according to user input, and the audit service screening speed is increased.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and more specifically to a data screening method, a data screening device, a computer equipment, a computer-readable storage medium, and a computer program product. Background Technology

[0002] In the era of big data, auditing faces multiple challenges, including massive amounts of data and hidden business relationships. For example, it requires in-depth correlation analysis of massive amounts of unstructured data. Most existing data analysis tools on the market are limited to single-dimensional data filtering, relying on preset rules or tags and fixed query conditions for data analysis. They can only achieve single-level transaction screening, resulting in limited query flexibility. At the same time, current technologies require tracing multiple audit clues across multiple reports and business systems, often using manual methods to query and integrate data across systems. This is inefficient, prone to missing correlations, and lacks the ability to deeply explore correlations. Summary of the Invention

[0003] Therefore, it is necessary to provide a data screening method, a data screening device, a computer device, a computer-readable storage medium, and a computer program product to address the aforementioned technical problems.

[0004] To achieve the above objectives, in a first aspect, embodiments of the present invention provide a data screening method, the method comprising: obtaining initial query conditions input by a user; the initial query conditions including initial tags and data range; performing data screening on business reports according to the initial tags and data range to generate current query results; querying a business model and a tag mapping table based on the data source of the current query results to generate associated tags; displaying the current query results and the associated tags on a current display interface; responding to receiving a target query instruction in the current display interface; performing data screening on a target business report according to the associated tags in the target query instruction to generate a next-level query result; querying the business model and the tag mapping table based on the data source of the next-level query results to generate new associated tags; displaying the next-level query results and the new associated tags on a new display interface; and responding to receiving a report generation instruction in any display interface, summarizing and outputting a multi-level query report based on the obtained multi-level query results.

[0005] In one embodiment, the target query instruction carries a query identifier; the step of screening the target business report based on the association tag selected by the target query instruction and generating the next-level query result includes: determining the target business report based on the association tag selected by the target query instruction; generating an association key based on the mapping relationship between the query identifier and the target business report; generating a query statement based on the association key to screen the target business report and generate the next-level query result.

[0006] In one embodiment, the target query instruction carries a query identifier; the step of screening the target business report based on the associated tags selected by the query instruction and generating the next-level query result includes: parsing the associated tags to determine that the associated tags are composite tags composed of multiple tags; generating query tags and restriction rules based on the composite tags; determining the target business report based on the query tags; querying the condition fields corresponding to the restriction rules in the target business report; generating an association key based on the mapping relationship between the query identifier and the target business report; and generating a composite query statement to screen the target business report based on the association key, the condition fields, and the restriction rules.

[0007] In one embodiment, the business model construction step includes: obtaining an audit business entity list and defining the hierarchical relationship of multiple business entities in the business entity list; constructing a mapping relationship between each business entity in the business entity list and a data source in the database, and binding at least one business tag to each business entity; and generating a business model with the business entities as nodes based on the hierarchical relationship and the mapping relationship.

[0008] In one embodiment, the step of summarizing and outputting a multi-level query report based on the acquired multi-level query results includes: obtaining link information of the multi-level query results, wherein the link information includes at least time information, path information, and tag information; converting the link information and the multi-level query results into a business instance tree based on the hierarchical relationship of the business model; generating an association matrix based on the association degree of each business entity in the business instance tree; and generating a multi-level query report based on the association matrix and the business instance tree.

[0009] In one embodiment, the method further includes: receiving a tag definition request, the tag definition request carrying user-defined request parameters; performing syntax validation on the request parameters; if the syntax validation passes, standardizing the request parameters to generate field information and syntax information; storing the field information and the syntax information, and updating the mapping relationship of the tag mapping table according to the field information.

[0010] Secondly, this application also provides a data screening device, the device comprising: a condition acquisition module, configured to acquire initial query conditions input by a user; the initial query conditions include initial tags and a data range; a preliminary query module, configured to perform data screening on business reports based on the initial tags and the data range, generate current query results; and query a business model and a tag mapping table based on the data source of the current query results to generate associated tags; and display the current query results and the associated tags on the current display interface; a nested query module, configured to respond to receiving a target query instruction in the current display interface; perform data screening on a target business report based on the associated tags in the target query instruction, generate a next-level query result; and query the business model and the tag mapping table based on the data source of the next-level query result to generate new associated tags; and display the next-level query result and the new associated tags on a new display interface; and a report generation module, configured to respond to receiving a report generation instruction in any display interface, and summarize and output a multi-level query report based on the acquired multi-level query results.

[0011] Thirdly, embodiments of this application provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the methods described above.

[0012] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods described herein.

[0013] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the steps of any of the methods described above.

[0014] One of the above technical solutions has the following advantages or beneficial effects: It obtains the initial query conditions input by the user; the initial query conditions include initial tags and data range; it performs data screening on business reports based on the initial tags and data range to generate the current query results; it then queries the business model and tag mapping table based on the data source of the current query results to generate associated tags; it displays the current query results and associated tags on the current display interface; it responds to receiving a target query instruction from the current display interface; it performs data screening on the target business report based on the associated tags in the target query instruction to generate the next-level query results; it then queries the business model and tag mapping table based on the data source of the next-level query results to generate new associated tags; it displays the next-level query results and new associated tags on a new display interface; and it responds to receiving a report generation instruction from any display interface, summarizing and outputting a multi-level query report based on the obtained multi-level query results. This method allows users to freely customize query tags for multi-level searches according to their needs, uncovering hidden data relationships between transactions, and greatly improving the efficiency and flexibility of query auditing operations.

[0015] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a diagram illustrating the application environment of a data screening method in one embodiment; Figure 2 This is a flowchart illustrating a data screening method in one embodiment; Figure 3 This is a structural block diagram of a data screening device in one embodiment; Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0017] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0018] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with relevant laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0019] This application provides a data screening method that can be applied to, for example... Figure 1 In the application environment shown, mobile terminal 102 communicates with server 104 via a network, in a scenario such as... Figure 1 In the application environment shown, the mobile terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets and portable wearable devices; the server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0020] In one embodiment, such as Figure 2 As shown, a data screening method is provided, the method including: S202, Obtain the initial query conditions input by the user; the initial query conditions include the initial labels and the data range.

[0021] The initial query criteria refer to the set of data filtering conditions entered by the user when initiating a query task based on the audit objectives. These conditions may include initial tags, data ranges, and other restrictions. Initial tags are user-selected or user-defined tags used to filter data, corresponding to one or more fields in the database. The data range refers to one or more target data sets for executing the query task, which may be personnel information tables, audit project tables, operation logs, or other business reports related to audit transactions.

[0022] S204: Based on the initial tags and data range, perform data screening on the business report to generate the current query results; and based on the data source of the current query results, query the business model and tag mapping table to generate associated tags; and display the current query results and associated tags on the current display interface.

[0023] The current query results refer to the collection of data records returned after executing a query based on the currently valid query conditions. The business model refers to a predefined structure that relates the logical relationships between various types of business reports. The business model can be configured as a tree structure, with the business entities corresponding to the business reports as nodes in the tree structure. This allows users to determine the drill-down path for the current node when performing a query, providing reliable and dynamic query navigation. The data source of the current query results refers to the source of the data for the current query results. For example, if auditor Zhang San's data comes from the personnel information table, the corresponding business report node in the business model can be found based on this data source, allowing for further drill-down path reasoning.

[0024] A tag mapping table is a data table that stores the mapping relationship between tags and specific fields in various business reports. It can be used to establish the relationship between tags and database fields, and queries to be executed can be dynamically generated by querying this table. Associated tags are optional tags automatically generated and displayed to the user for deep drill-down queries. In this embodiment, the system queries the business model to determine possible next-node paths, and then presents the available tags on these paths to the user through the tag mapping table. This method improves the targeting of auditing work, reduces errors in human tag selection, and enhances decision-making quality.

[0025] S206, responding to receiving the target query instruction in the current display interface; screening the target business report for data based on the associated tags in the target query instruction, generating the next-level query results; querying the business model and tag mapping table based on the data source of the next-level query results to generate new associated tags; and displaying the next-level query results and the new associated tags on the new display interface.

[0026] The current display interface refers to the interactive interface presenting the data screening results. It can change according to the query results and may include a view of the current query results and related tags corresponding to the generated current query results. The target query command refers to a deep query command generated by the user in the current display interface by triggering related tags. This command may carry specific data identifiers selected by the user in the current query results. The target business report refers to the business report for which further queries will be performed based on the target query command. This business report is automatically parsed from the related tags in the target query command. The next-level query results refer to the collection of data records obtained after screening the target business report according to the target query command. In this embodiment, the user can select new related tags again in a new display interface to perform a query. The system continuously expands the search scope according to the user's selection until the search reaches a preset depth or the user outputs a report generation command. This method can integrate fragmented data and achieve in-depth mining of audit transactions.

[0027] S208, in response to receiving a report generation instruction from any display interface, summarizes and outputs a multi-level query report based on the obtained multi-level query results.

[0028] Report generation instructions refer to data integration instructions issued by users by triggering any option on the display interface. Multi-level query results refer to the collection of query results at all levels generated in the complete data screening process, which includes the data obtained from each level of query. Multi-level query reports refer to comprehensive documents generated after organizing, analyzing and formatting multi-level query results, which may include structured query results, business report relationships displayed in the form of an association matrix, timeline graphs of key events displayed in chronological order, etc.

[0029] This method initiates an initial screening based on user-inputted query conditions and intelligently guides users to select possible analysis methods by displaying related tags. It further receives target query commands from the display interface to achieve multiple, automated, deep drill-down queries, solving the problem of existing technologies being unable to perform deep correlation exploration. It supports users in tracing complex transaction chains, helping them improve the depth and accuracy of data screening. Furthermore, to eliminate human error caused by manual operations across reports, this method outputs multi-level query reports that integrate scattered, multi-round screening results into a structured report, ensuring consistency between report content and the screening chain, and improving the efficiency and quality of data analysis output.

[0030] In one embodiment, the method further includes: receiving a tag definition request, the tag definition request carrying user-defined request parameters; performing syntax validation on the request parameters; if the syntax validation passes, standardizing the request parameters to generate field information and syntax information; storing the field information and syntax information, and updating the mapping relationship of the tag mapping table according to the field information.

[0031] A tag definition request is a user-triggered instruction to create or modify a tag rule. It allows users to customize tags to meet diverse business scenarios. The request parameters are the data set specifically describing the tag rule, which may include tag name, target scope parameters, composite conditions, and target fields. In this embodiment, the front-end page supports users graphically defining tag rules or inputting composite tags. For example, the tag "Auditor" = `User table.Name field`, and "High-risk working papers" = "Version number > 5" and "Number of modifications > 10". The system performs syntax validation on the request parameters to check the completeness of required parameters, which can be tag names, target tables, rule logic, etc. It also verifies the existence of target scope parameters or target fields in the request parameters. If the syntax validation passes, the request parameters are standardized to generate a standardized format. Field information refers to the database table names or field names referenced in the extracted request parameters; syntax information refers to the syntax rules in the request parameters converted into an executable format. The standardized field information and syntax information are stored, and the record information in the tag mapping table is updated. The dynamic tag configuration mechanism allows users to define and combine screening rules independently and flexibly according to audit objectives, thus improving the dynamism and flexibility of the method.

[0032] In one embodiment, the business model construction step includes: obtaining an audit business entity list and defining the hierarchical relationship between multiple business entities in the business entity list; constructing a mapping relationship between each business entity in the business entity list and a data source in the database, and binding at least one business tag to each business entity; and generating a business model with the business entities as nodes based on the hierarchical relationship and the mapping relationship.

[0033] A business entity refers to a business object with clear meaning and attributes in an audit process, which may include audit projects, auditors, working paper versions, operation logs, etc. A business entity list is a collection of business entities. Hierarchical relationships refer to the inclusion or sequential relationships between business entities, such as structural relationships, business process relationships, version relationships, etc. Mapping relationships refer to the correspondence between business entities and physical database structures; each business entity can correspond to a table or view in the database. Tags are semantic markers describing business entities; for example, an auditor entity can be bound to tags such as "project leader" or "external expert." This method creates a business-oriented audit business model, helping users operate based on familiar business entities and establishing standardized mapping specifications from business entities to data tables, providing paths for subsequent automated queries.

[0034] In one embodiment, the target query instruction carries a query identifier; the step of screening the target business report based on the association tag selected by the target query instruction and generating the next-level query result includes: determining the target business report based on the association tag selected by the target query instruction; generating an association key based on the mapping relationship between the query identifier and the target business report; generating a query statement based on the association key to screen the target business report and generate the next-level query result.

[0035] The query identifier refers to the unique identifier of one or more data records selected by the user in the current query results. The association key refers to the field that connects the business report and the target business report to establish a mapping relationship. In this embodiment, the target business report to be drilled down is determined according to the node position corresponding to the association tag in the business model. Then, the association key between the business report and the target business report is determined according to the query identifier. A query statement is generated based on the association key for screening. In a specific embodiment, the user selects "Audit Team Member = Zhang San" and clicks the association tag "Audit Findings Working Papers". The system determines the target business report as "Working Papers Table" according to the tag "Audit Findings Working Papers". According to the user table corresponding to "Zhang San", the association key of the working paper table is determined to be "User Table.User_ID = Working Papers Table.Author_ID". Then, an SQL statement is dynamically generated to obtain all working paper records with Author_ID of Zhang San as the next level query result. This method combines the business model and the tag mapping table to understand the association tags of the business, find the query path, and construct complex cross-table query statements, realizing automated joint analysis of cross-report data.

[0036] In one embodiment, the target query instruction carries a query identifier; the step of screening the target business report based on the associated tags selected in the query instruction and generating the next-level query results includes: parsing the associated tags to determine that the associated tags are composite tags composed of multiple tags; generating query tags and restriction rules based on the composite tags; determining the target business report based on the query tags; querying the condition fields corresponding to the restriction rules in the target business report; generating an association key based on the mapping relationship between the query identifier and the target business report; and generating a composite query statement based on the association key, condition fields, and restriction rules to screen the target business report.

[0037] A composite tag is a tag entity that combines one or more basic tags with logical operators to express complex business rules. It can include basic tags, logical operators, and business semantics. A query tag is an entity tag within a composite tag that indicates the query target, such as a draft, user, or invoice. A constraint rule is a combination of conditions within the composite tag used to filter the business entity pointed to by the query tag. In this embodiment, after parsing the associated tags, the system divides them into query tags pointing to the next business entity and constraint rules. Based on the node position of the query tag in the business model, the system determines the target business report to drill down to. Simultaneously, it parses the constraint rules to identify the condition fields they contain, such as: version number > 5, modification count > 10. The version number corresponds to `draft_table.Version`, and the modification count corresponds to `draft_table.Modification_Count`. During the generation of the composite query statement, the associated key, condition fields, and constraint rules are integrated. In a specific embodiment, this method encapsulates complex business logic into composite tags, supporting AND, OR, NOT, and their arbitrary combinations to construct business screening rules, thus improving the flexibility of data screening.

[0038] In one embodiment, the step of summarizing and outputting a multi-level query report based on the acquired multi-level query results includes: obtaining link information of the multi-level query results, the link information including at least time information, path information and tag information; converting the link information and multi-level query results into a business instance tree based on the hierarchical relationship of the business model; generating an association matrix based on the association degree of each business entity in the business instance tree; and generating a multi-level query report based on the association matrix and the business instance tree.

[0039] Responding to user-triggered report generation commands on any display interface, the system automatically records the chain information of all operations during the user data exploration process. This includes the execution timestamp of each query step, operation interval, the sequence of nodes traversed during the data screening process, the tags and parameter values ​​in each step, etc. Based on the predefined hierarchical relationship of the business model, all data is assembled, and the association strength is calculated according to the relationship between each business entity in the business instance tree to generate an association matrix. In this association matrix, the rows can be business entity instances, and the columns can be the association strength values ​​of business entities. In addition, time information can be extracted from the business instance tree to group all query events to generate a timeline graph. All the above analysis results are then populated into a multi-level query report. This analysis step integrates the fragmented data discovered during the interactive screening process into a structured association matrix, a visual graph, and a comprehensive audit report, which can improve the automation and output efficiency of user data screening.

[0040] In one embodiment, such as Figure 3 As shown, this application also provides a data screening device 300, comprising: The condition acquisition module 301 is used to acquire the initial query conditions input by the user; the initial query conditions include initial labels and data range; The preliminary query module 302 performs data screening on the business report based on the initial tags and data range, generates the current query results, and queries the business model and tag mapping table based on the data source of the current query results to generate associated tags; and displays the current query results and associated tags on the current display interface. The nested query module 303 is used to respond to the target query command received in the current display interface; to screen the target business report according to the associated tags in the target query command, and generate the next level query results; and to query the business model and tag mapping table based on the data source of the next level query results to generate new associated tags; and to display the next level query results and the new associated tags in the new display interface. The report generation module 304 is used to respond to a report generation instruction received from any display interface and to summarize and output a multi-level query report based on the obtained multi-level query results.

[0041] In one embodiment, the target query instruction carries a query identifier; the nested query module 303 includes a data screening module, which is used to determine the target business report based on the associated tag selected by the target query instruction; generate an association key based on the mapping relationship between the query identifier and the target business report; generate a query statement based on the association key to screen the target business report and generate the next level query result.

[0042] In one embodiment, the target query instruction carries a query identifier; the nested query module 303 includes a composite screening module, used to parse the associated tags, determine that the associated tags are composite tags composed of multiple tags; generate query tags and restriction rules based on the composite tags; determine the target business report based on the query tags; and query the condition fields corresponding to the restriction rules in the target business report; generate an association key based on the mapping relationship between the query identifier and the target business report; and generate a composite query statement based on the association key, condition fields, and restriction rules to screen the target business report.

[0043] In one embodiment, the apparatus includes a model building module for obtaining an audit business entity list and defining the hierarchical relationship between multiple business entities in the business entity list; constructing a mapping relationship between each business entity in the business entity list and a data source in the database, and binding at least one business tag to each business entity; and generating a business model with business entities as nodes based on the hierarchical relationship and the mapping relationship.

[0044] In one embodiment, the report generation module 304 is specifically used to obtain the link information of the multi-level query results, which includes at least time information, path information and tag information; convert the link information and multi-level query results into a business instance tree based on the hierarchical relationship of the business model; generate an association matrix according to the association degree of each business entity in the business instance tree; and generate a multi-level query report based on the association matrix and the business instance tree.

[0045] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0046] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0047] This invention provides a processor for running a program, wherein the program executes a data screening method during runtime.

[0048] In one embodiment, a computer device is provided, which may be a mobile terminal, and the internal structure diagram of the computer device may be as follows: Figure 4As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a data screening method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0049] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0050] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects.

[0051] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0052] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0053] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A data screening method, characterized in that, include: Obtain the initial query conditions input by the user; The initial query conditions include initial labels and data range; The business report is screened based on the initial tags and data range to generate the current query results; and the business model and tag mapping table are queried based on the data source of the current query results to generate associated tags. Display the current query results and the associated tags on the current display interface; In response to receiving the target query command in the currently displayed interface; The target business report is screened based on the associated tags in the target query instruction to generate the next-level query results; the business model and the tag mapping table are queried based on the data source of the next-level query results to generate new associated tags; the next-level query results and the new associated tags are displayed on a new display interface. In response to a report generation command received from any display interface, it summarizes and outputs a multi-level query report based on the obtained multi-level query results.

2. The method according to claim 1, characterized in that, The target query instruction carries a query identifier; The step of screening the target business report based on the associated tags selected by the target query instruction and generating the next level query results includes: The target business report is determined based on the associated tags selected by the target query instruction; Generate an association key based on the mapping relationship between the identifier to be queried and the target business report; Based on the association key, a query statement is generated to screen the target business report and generate the next-level query results.

3. The method according to claim 1, characterized in that, The target query instruction carries a query identifier; the step of screening the target business report based on the associated tags selected by the query instruction and generating the next-level query results includes: The associated tags are parsed to determine that the associated tags are composite tags composed of multiple tags; Generate query tags and restriction rules based on the composite tags; The target business report is determined based on the query tags; and the condition fields corresponding to the restriction rules in the target business report are queried. Generate an association key based on the mapping relationship between the identifier to be queried and the target business report; Based on the association key, the condition field, and the restriction rules, a compound query statement is generated to screen the target business report.

4. The method according to claim 1, characterized in that, The steps for constructing the business model include: Obtain the list of audit business entities and define the hierarchical relationship among multiple business entities in the list; Construct a mapping relationship between each business entity in the business entity list and the data source in the database, and bind at least one business tag to each business entity; A business model with the business entity as the node is generated based on the hierarchical relationship and the mapping relationship.

5. The method according to claim 4, characterized in that, The step of summarizing and outputting a multi-level query report based on the obtained multi-level query results includes: Obtain the link information of the multi-level query results, wherein the link information includes at least time information, path information, and tag information; Based on the hierarchical relationship of the business model, the link information and the multi-level query results are converted into a business instance tree; An association matrix is ​​generated based on the association degree of each business entity in the business instance tree; A multi-level query report is generated based on the association matrix and the business instance tree.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: Receive a tag definition request, the tag definition request carrying user-defined request parameters; Perform syntax validation on the request parameters; If the syntax validation passes, the request parameters are standardized to generate field information and syntax information; The field information and the syntax information are stored, and the mapping relationship of the tag mapping table is updated according to the field information.

7. A data screening device, characterized in that, The device includes: The condition acquisition module is used to acquire the initial query conditions input by the user; the initial query conditions include initial tags and data range; The preliminary query module performs data screening on the business report based on the initial tags and data range, generates the current query results, and queries the business model and tag mapping table based on the data source of the current query results to generate associated tags; and displays the current query results and the associated tags on the current display interface. The nested query module is used to respond to receiving a target query instruction in the current display interface; to perform data screening on the target business report according to the associated tags in the target query instruction, and generate the next-level query result; and to query the business model and the tag mapping table based on the data source of the next-level query result to generate new associated tags; and to display the next-level query result and the new associated tags in a new display interface. The report generation module is used to respond to report generation instructions received from any display interface, and to summarize and output multi-level query reports based on the obtained multi-level query results.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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