Data collaboration processing system and method based on multi-service data

Abstract

This invention discloses a data collaborative processing system and method based on multi-business data. The system includes: a thematic data product management module for binding specified data sources to business themes and creating report templates for those themes using the specified data sources, grouping dimensions, and statistical dimensions; a dual-path distribution module for generating a copy of the report template that supports individual modification for each authorized user; distributing conditional rules for the business theme to all authorized users; these conditional rules restrict operations on the report template content; and a conditional rendering module for providing an interactive interface based on the report template copy and the conditional rules for the business theme; receiving report generation requests input by authorized users through the interactive interface and sending these requests to an asynchronous task engine module; and the asynchronous task engine module for generating multiple reports in parallel through asynchronous tasks. This invention avoids data cross-contamination and version conflicts, improving the accuracy of data acquisition.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a data collaborative processing system and method based on multi-business data. Background Technology

[0002] The current aviation industry data environment is highly complex: on the one hand, the diversification of business scenarios (such as sales, transportation, and allocation) requires data services to have precise isolation and flexibility; on the other hand, the hierarchical organizational structure (headquarters and subsidiaries) requires the system to achieve a balance between centralized control and distributed agile operation.

[0003] However, existing data extraction solutions mostly employ static data source binding and generic report generation models, leading to two major contradictions: (1) Rigid architecture leads to data accuracy crisis: Data from different business themes are strongly coupled at the bottom layer and cannot be logically isolated, resulting in cross-access and contamination of data, making it difficult to guarantee accuracy.

[0004] (2) The single distribution mechanism restricts operational efficiency: The single template distribution strategy cannot distinguish between "report structure" and "business rules", resulting in frequent version conflicts, delayed rule updates, and serious slowing down the decision-making process.

[0005] Therefore, the industry urgently needs a new generation of data extraction solutions that can simultaneously meet the requirements of "flexible adaptation", "precise isolation" and "efficient collaboration". Summary of the Invention

[0006] This invention provides a data collaborative processing system based on multi-business data to avoid data cross-contamination and version conflicts, and improve the accuracy of data acquisition. The system includes: a themed data product management module, a dual-path distribution module, a conditional rendering module, and an asynchronous task engine module. The thematic data product management module is used to: bind a specified data source to a business theme, receive the grouping and statistical dimensions of the business theme, and create a report template for the business theme using the specified data source, grouping and statistical dimensions; the grouping dimension is the row label of the report template, and the statistical dimension is used for numerical calculations; The dual-path distribution module is used to: identify multiple authorized users of the report template; generate a copy of the report template that supports personal modification for each authorized user; and distribute conditional rules for the business topic to all authorized users; the conditional rules are used to limit operations on the content of the report template. The conditional rendering module is used to: provide an interactive interface based on the conditional rules of the report template copy and the business theme; and receive the report generation request input by the authorized user based on the interactive interface and send the report generation request to the asynchronous task engine module. The asynchronous task engine module is used to receive report generation requests from multiple authorized users and generate multiple reports in parallel through asynchronous tasks.

[0007] This invention also provides a data collaborative processing method based on multi-service data to avoid data cross-contamination and version conflicts, and improve the accuracy of data acquisition. The method includes: Bind a specified data source to a business theme, receive the grouping and statistical dimensions of the business theme, and create a report template for the business theme using the specified data source, grouping and statistical dimensions; the grouping dimensions are the row labels of the report template, and the statistical dimensions are used for numerical calculations; Identify multiple authorized users for the report template; generate a copy of the report template that supports individual modifications for each authorized user; distribute conditional rules for the business topic to all authorized users; the conditional rules are used to limit operations on the content of the report template; Based on the report template copy and the conditional rules of the business topic, an interactive interface is provided; the report generation request input by the authorized user is received through the interactive interface; Multiple reports are generated in parallel using asynchronous tasks.

[0008] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described data collaborative processing method based on multi-service data.

[0009] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned data collaborative processing method based on multi-service data.

[0010] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described data collaborative processing method based on multi-service data.

[0011] In this embodiment of the invention, a themed data product management module binds specified data sources to business themes, fundamentally preventing cross-contamination of different business data and significantly improving data accuracy. The dual-path distribution module provides fine-grained distribution control, perfectly balancing flexibility and consistency, greatly reducing conflicts and repetitive workload caused by version inconsistencies. The conditional rendering module allows authorized users to initiate report generation requests based on report template copies and business theme conditional rules. The asynchronous task engine module ensures that large-scale data generation does not block user interaction, improving the overall stability and concurrent processing capabilities of the system. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 This is a schematic diagram of a data collaborative processing system based on multi-service data in an embodiment of the present invention; Figure 2 This is a specific example diagram of a data collaborative processing system based on multi-service data in an embodiment of the present invention; Figure 3 This is another specific example of a data collaborative processing system based on multi-service data in this invention. Figure 4 This is a flowchart illustrating the data collaborative processing method based on multi-service data in an embodiment of the present invention; Figure 5 This is a schematic diagram of a computer device in an embodiment of the present invention. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0014] The acquisition, storage, use, and processing of data in this application comply with relevant laws and regulations.

[0015] First, the technical terms involved in the embodiments of the present invention will be explained.

[0016] Declarative configuration interface: refers to a user interface that allows administrators to complete the creation of business data products, dimension definition and permission configuration through non-programming methods such as drag and drop, selection, etc., and is the key to achieving high business agility.

[0017] Row- and column-level access control refers to a fine-grained access control mechanism that applies row-level (record filtering) and column-level (field masking) permissions to the query result set based on user roles during data access.

[0018] Existing technology one is a method for achieving cross-domain and cross-organizational privacy data joint computation and generating data products under a data grid architecture. This includes multi-party domain initialization, constructing joint computation domains, cross-domain data joint computation, and joint data product release. However, this technology heavily relies on trusted execution environments and complex cryptographic techniques (such as homomorphic encryption and attribute base functions). Its implementation, deployment, and maintenance have extremely high technical barriers and costs, making it difficult to popularize in general enterprises. Multi-layered encryption and decryption processes and collaborative computation based on trusted execution environments introduce significant computational overhead and communication latency, making it difficult to meet the needs of business scenarios with high real-time requirements. While governance relies on "multi-party contracts," the decision-making process is cumbersome, even if standardized. When there are many participants, reaching consensus and updating rules is inefficient, easily leading to project failure due to poor coordination. This solution is specifically designed for cross-organizational privacy computation scenarios where "data is usable but not visible," thus its applicability is limited.

[0019] Existing technology two is based on OLAP (Online Analytical Processing) for report collection. Its core is a multidimensional model rapid construction module that allows users to automatically generate cubes by selecting business elements. Then, through drag-and-drop mapping, the dimensions and measures in the model are mapped to specific areas of the report. Finally, the system automatically converts this into an expression query, executes it, and populates the report with the results. However, this technology has limitations in the following four aspects: (1) At the level of architecture positioning: clinging to the mindset of technical tools and lacking the ability to productize and collaborate on data.

[0020] At its core, it is a technology-driven report generation tool, not a business-oriented data product platform, and therefore cannot achieve asset-based data management. Consequently, it inherently lacks cross-team data collaboration and distribution mechanisms, and cannot address organizational collaboration needs such as version management of report templates, controllable distribution, and real-time synchronization of business rules.

[0021] (2) Business agility level: rigid models and slow response.

[0022] The OLAP multidimensional model it relies on is predefined and static. Any change in business requirements (such as adding dimensions or metrics) requires modifying the underlying model and recalculating, resulting in long change cycles, failing to support flexible ad-hoc analysis, and severely slowing down business decision-making.

[0023] (3) Technical architecture level: Centralized design leads to performance and collaboration bottlenecks.

[0024] As a typical centralized architecture, all computing loads are concentrated in the central data warehouse, which can easily become a bottleneck for system performance.

[0025] At the same time, all reporting requests must be responded to by the central data team, which becomes a development bottleneck, unable to support the agile demands of distributed business, and restricts the efficiency of the overall data service.

[0026] (4) User and security aspects: poor experience and weak access control.

[0027] Poor user experience: The operation still revolves around professional technical concepts such as dimensions and metrics, and is not optimized for business users. It lacks intelligent interactive components and has a high technical threshold.

[0028] Weak access control: The lack of granular data access control at the row and column levels makes it difficult to meet the stringent requirements of enterprise-level data security and compliance management.

[0029] The embodiments of the present invention aim to solve the following core technical problems faced by existing data extraction and reporting systems under complex business and organizational structures: Business theme overlap and data accuracy issues: Solve the problem of cross-access and contamination of data from multiple business scenarios in the same system due to strong underlying coupling, which makes it impossible to achieve logical isolation, thereby ensuring the accuracy of core business data.

[0030] Addressing the lack of distribution control in organizational collaboration: Resolving technical deficiencies such as frequent report template version conflicts and delayed business rule synchronization in multi-level organizations such as headquarters and subsidiaries, and achieving a balance between unified management and distributed agile operation.

[0031] Addressing the issue of high complexity in interactions with business personnel: This section aims to resolve the problem where business personnel rely on developers due to the high technical barriers when configuring data extraction conditions, resulting in slow responses to business changes and improving business agility.

[0032] System performance bottlenecks: Solve the front-end interaction blockage and system response delay caused by generating large amounts of data reports, and ensure the stability and user experience of the system in high-concurrency, large-data-volume scenarios.

[0033] Figure 1 This is a schematic diagram of a data collaborative processing system based on multi-service data in an embodiment of the present invention, such as... Figure 1 As shown, the system 100 includes: a themed data product management module 101, a dual-path distribution module 102, a conditional rendering module 103, and an asynchronous task engine module 104; The thematic data product management module 101 is used to: bind a specified data source to a business theme, receive the grouping dimension and statistical dimension of the business theme, and create a report template for the business theme using the specified data source, grouping dimension and statistical dimension; the grouping dimension is the row label of the report template, and the statistical dimension is used for numerical calculation; The dual-path distribution module 102 is used to: identify multiple authorized users of the report template; generate a copy of the report template that supports personal modification for each authorized user; and distribute conditional rules of the business topic to all authorized users; the conditional rules are used to limit operations on the content of the report template. The conditional rendering module 103 is used to: provide an interactive interface based on the conditional rules of the report template copy and the business theme; receive the report generation request input by the authorized user based on the interactive interface, and send the report generation request to the asynchronous task engine module 104; The asynchronous task engine module 104 is used to: receive report generation requests from multiple authorized users and generate multiple reports in parallel through asynchronous tasks.

[0034] The following describes in detail the data collaborative processing system and method based on multi-service data in the embodiments of the present invention.

[0035] Thematic Data Product Management Module 101 is mainly used for data source management and theme management.

[0036] Data source management refers to the centralized management of scattered and heterogeneous data sources (such as data warehouses and databases like Oracle and Greenplum) within an enterprise through a unified data access layer. It transforms the complex underlying physical table structures into logical datasets that are understandable to the business, encapsulates the differences between various data sources through standardized adapters, and provides unified metadata discovery and data access services. This fundamentally shields the diversity of data sources, providing an accurate, consistent, and high-performance data foundation for business themes, and ensuring the standardization and reliability of data sources throughout the system.

[0037] Topic management includes the creation, configuration, and maintenance of business data products (i.e., business topics). A business topic, or business data product, refers to a business logical unit that encapsulates a specific data source table, dimension set, and access permissions into an independently publishable, authorizable, and accessible unit, such as a channel analysis topic.

[0038] In one embodiment, the thematic data product management module 101 is specifically used for: Receive the business topic name and generate a blank report; The system receives the data source table name information through a declarative configuration interface, enabling the backend to: explore the table structure based on the data source table name information, generate and return a field tree; Display the field tree; Monitor user drag-and-drop operations, and based on these operations, select data dimensions from the field tree as grouping and statistical dimensions to embed into blank reports, generating report templates for business themes.

[0039] Grouping dimensions are fields used for data grouping, appearing as row labels in reports, such as carrier, ticketing date, and route. Statistical dimensions are fields used for numerical calculations and aggregation analysis, appearing as data columns in reports, such as sales revenue and load factor. They are strictly separated from grouping dimensions in definition and usage.

[0040] In one embodiment, the thematic data product management module 101 is further configured to: Save the report templates for the business theme to the data warehouse and record the metadata information of the report templates for that business theme; the metadata information includes one or any combination of report dimension information, field type, creator, and version number.

[0041] During implementation, administrators input the data source table name through a declarative configuration interface. The system calls an interface to automatically explore and return the table structure, generating a field tree. Drag-and-drop interaction is provided, allowing administrators to strictly divide fields according to business logic into "grouping dimensions" (such as carrier company, ticketing date, used for row labels) and "statistical dimensions" (such as sales revenue, occupancy rate, used for numerical calculations). The theme configuration information (including theme name, bound data source, and dimension set) is persistently stored in the business theme table of the data warehouse, completing the dynamic binding and isolation between the physical data source and the logical business theme. In this embodiment of the invention, dynamic theme binding, through configuration rather than coding, dynamically associates the backend physical data source with the frontend logical business theme, which is the foundation for the rapid construction and isolation of business data products.

[0042] When a report template is saved, its metadata (such as dimension order, field type, and creator) is recorded in the data warehouse. Template version management is supported; a version record is generated for each modification, facilitating traceability and rollback.

[0043] In this embodiment, the grouping dimension and the statistical dimension are mutually exclusive; the mutual exclusion means that the grouping dimension and the statistical dimension are prohibited from being used together.

[0044] During the business theme creation phase, a declarative configuration interface guides administrators to accurately model business semantics. Its core mechanism involves mandatory regional grouping and statistical dimensions, which are defined as mutually exclusive types at the data model level, prohibiting their mixing and ensuring the clarity and accuracy of the report structure.

[0045] In practice, the system supports configuring administrator identities for headquarters (head office) and authorized user identities for branches. After some administrators set up business themes, other authorized administrators can directly use the existing business themes. For example, after logging in, an administrator can choose to create a new business theme or directly use the business themes they are authorized to use.

[0046] Example: In the air transport theme, carrier, flight number, and operating date are defined as grouping dimensions (for row labels); ticket revenue and fuel surcharge are defined as statistical dimensions (for numerical aggregation). This mechanism ensures that business personnel cannot drag "ticket revenue" into row groupings or perform aggregation operations on "carrier" when designing reports. This eliminates data interpretation errors caused by conceptual confusion at the business logic definition level, ensuring the semantic accuracy of the reports.

[0047] In this embodiment of the invention, the theme-based data product management module does not simply establish a connection pool after accessing the dispersed core data sources within each airline. Instead, it strictly defines the access boundaries of data tables at the physical level through configuration, clearly specifying which business themes or multiple business themes each physical table can be bound to.

[0048] For example, the "Transportation Segment Product Table" in the data warehouse can be bound only to the "Segment Monthly Report Theme"; at the same time, the "Transportation Festival Carrying Table" can be bound only to the "Festival Revenue Theme".

[0049] In this way, when a user accesses the "Flight Segment Revenue" topic, the transportation segment product table and any of its fields will not appear in the user interface or query logic. The system fundamentally eliminates the possibility of cross-table access when generating SQL, achieving logical isolation of business data from the data source and precisely solving the core governance challenges of cross-access and contamination of data.

[0050] Furthermore, in this embodiment, each business topic is completely independent and can be deployed as a microservice. Each service has its own independent database or schema, and unified routing and authentication are performed through an API gateway. Independent deployment achieves ultimate data isolation and business agility.

[0051] Dual-path distribution module 102 is responsible for the distribution and synchronization of report templates and business conditions within the organization, and includes a dual-path distribution engine: Report copy distribution path: When a report template is distributed, an independent, data-isolated copy of the template is generated for each authorized user in the underlying table, allowing for individual modification. Modifications made by an authorized user to their report template copy do not affect the report template copies of other authorized users; that is, modifications made by an authorized user to their copy only affect themselves.

[0052] Conditional rule shared distribution path: When distributing filtering conditions, a shared reference relationship is established between all authorized users and the same condition object in the distribution table. When the condition content is updated, it takes effect in real time and globally for all authorized users, without the need for individual notifications or operations.

[0053] This invention, through a dual-path distribution module, solves the collaborative governance challenge between the headquarters of an airline company and its regional sales offices. Report copy distribution: Report structure templates are distributed. The system generates an independently editable copy for each authorized user, supporting personalized modifications. Conditional rule sharing distribution: Business filtering conditional rules are distributed, and all authorized users share and reference the same rule object.

[0054] Taking transportation data as an example, business personnel define the grouping dimensions such as the date of operation, route type, departure airport code of the flight segment, arrival airport code of the flight segment, aircraft number, operating branch, affiliated branch, and flight number, as well as the statistical dimensions such as passenger-shared revenue and fuel surcharge, into the "202x Monthly Transportation Revenue Report" template at the business level.

[0055] Report copy distribution: Distribute this template to subsidiaries or other colleagues. For example, analysts in the xx regional branch can add the "flight route filter within xx region" condition to their personal copy. This modification is only visible to the individual and does not affect the headquarters source template.

[0056] Conditional rule sharing and distribution: The rule "machine number is not equal to B1000, processing month is equal to 202xxx, and the delivery date is between 202x0x01 and 202x0x30" is distributed to all users as a shared condition. When headquarters changes the excluded machine number to 'B2000', all users will automatically apply the new rule, achieving second-level consistency in business reporting.

[0057] In one embodiment, the dual-path distribution module 102 is specifically used to: when the report template of a business topic is updated, overwrite the updated authorized user's copy of the report template.

[0058] For example, after the source template is updated, the administrator can use the incremental merging redistribution operation to update the headquarters content while intelligently retaining some non-conflicting personalized modifications in user copies, that is, selectively overwriting user copies. This perfectly resolves the contradiction between unified control and distributed agility, and achieves unified updates.

[0059] Compared to existing static distribution mechanisms, this invention can distinguish between distributing "report structures" and distributing "business rules," and employs distinctly different data persistence and synchronization strategies. This achieves both unified management and control, simultaneously meeting the personalized analysis needs of business units and the minute-level global synchronization requirements of core business rules.

[0060] In one embodiment, to reduce release risks and ensure smooth updates, the dual-path distribution module 102 is specifically used to: adopt canary release to distribute the conditional rules of the business topic to all authorized users, realize smooth traffic switching, and ensure service stability.

[0061] In one embodiment, the data collaborative processing system based on multi-service data in this embodiment of the invention may further include: a unified access control module; the unified access control module is used to: assign data access permissions to all users according to the organizational department to which the user belongs.

[0062] Figure 2 This diagram illustrates a specific example of a data collaborative processing system based on multi-service data, as described in this embodiment of the invention. It showcases the organizational architecture of the system. Figure 2 As shown, the system can be divided into a data layer, a business logic layer, and an application layer. The data layer is used to receive and store datasets and manage data sources. The business logic layer is used for topic management and condition management. It provides topic data through topic management and business filtering conditions through condition management. The application layer generates reports by a report engine, including report templates generated by administrators and personalized reports generated by authorized users. Finally, the final report is output.

[0063] The unified access control module, through a unified data access entry point, is responsible for performing fine-grained access checks before and after query execution. Upon receiving a user's data access request, it first verifies the user's access permissions to the target business topic. During the data query phase, row-level permission filtering conditions are dynamically injected based on the user's role (e.g., only data from this business region can be queried). During the query result return phase, column-level permission filtering is implemented to block fields that the user is not authorized to access.

[0064] In this embodiment, the conditional rendering module 103 is used to: provide an interactive interface based on the conditional rules of the report template copy and the business theme; receive the report generation request input by the authorized user based on the interactive interface, and send the report generation request to the asynchronous task engine module 104.

[0065] In one embodiment, the conditional rendering module 103 is specifically used for: Based on the interactive interface, the system receives query condition fields input by authorized users and dynamically renders and displays matching input controls according to the query condition fields. The system receives data requests based on input controls and performs a report preview.

[0066] During implementation, the conditional rendering module is responsible for providing an intelligent interactive interface when users set query conditions. It dynamically selects and renders the most matching input control based on the metadata type of the condition field: for date types, it renders a calendar control; for enumeration types, it loads options from the filter condition table and renders a dropdown selection box; for numeric types, it renders a numeric range input box. It supports switching between intelligent mode (automatic rendering) and native mode (direct SQL input), balancing ease of use for business purposes with technical flexibility.

[0067] In one embodiment, the interactive interface provided by the conditional rendering module 103 also supports users in setting up scheduled report generation tasks. For example, the report generation request includes a request to generate reports instantly and a request to generate reports on a scheduled basis. The scheduled report generation request provides configuration functions, including: scheduled report generation, scheduled sending frequency, and email address.

[0068] The asynchronous task engine module 104 is further configured to: receive requests from multiple authorized users for immediate report generation and requests for scheduled report generation, and generate multiple reports in parallel through asynchronous tasks. Specifically, it triggers requests for scheduled report generation based on the scheduled sending frequency, and sends the scheduled reports to the email addresses specified by the authorized users.

[0069] The asynchronous task engine module 104 is responsible for receiving, scheduling, and executing large-scale report generation tasks, ensuring the system's front-end response performance. In this embodiment, the asynchronous task engine is not a general-purpose computing resource scheduler. When executing a task, it first loads the metadata of the "business topic" associated with the task and dynamically injects row- and column-level data permission filters based on user roles during the query generation phase. This means that from its inception, it carries the semantics of business isolation and access control, ensuring that the results of asynchronous generation still strictly adhere to the enterprise's data governance rules—a feature not found in purely technical task schedulers. Its core value lies in ensuring that massive data queries are executed efficiently while strictly adhering to pre-existing data governance and collaboration rules.

[0070] In one embodiment, the asynchronous task engine module 104 is further configured to: A task state machine is used to manage the task lifecycle of each authorized user's report generation request; the task state machine divides the task status into new, running, successful, and failed.

[0071] Taking transportation revenue as an example, the execution process is as follows: 1. Business context parsing and loading: Upon receiving a task request, the engine first parses its core identifier—the business topic ID. Based on this ID, the asynchronous task engine loads the complete configuration from the topical data product management module. Physical data source: Locates the specified transportation fact table in the data warehouse.

[0072] Business Dimension Set: Loads user-defined grouping dimensions (operation date, route type, origin / arrival airport code, aircraft number, carrier branch, affiliated branch, flight number) and statistical dimensions (passenger revenue sharing, fuel surcharge, etc.) in this report. The system ensures that these two are logically strictly separated and not used interchangeably.

[0073] User permission context: Get the role of the requesting user (e.g., analyst of xx regional branch).

[0074] 2. Dynamic injection of permissions and rules: In the most critical stage of dynamically concatenating physical query SQL, the engine performs two deep business couplings: 1) Row-level data permission injection: Call the unified permission service to automatically inject hidden filtering conditions into the WHERE clause of the SQL based on the user role (e.g., data analyst of the branch office in xx region), fundamentally ensuring that they cannot query the data of the branch office in xx region, and strictly guarding the data boundaries.

[0075] 2) Shared Business Conditions: Before report generation, users can clearly see and directly select the required conditions on the front-end interface. Here, users can customize conditions or select shared conditions distributed by higher-level collaborating departments, such as: Aircraft Number != 'B1000' AND Processing Month = 202xxx AND Carrying Date BETWEEN 202x0x01 AND 202x0x30. The user-selected set of conditions is previewed instantly and is fully visible on the interface. When the user confirms report generation, the asynchronous task engine directly and transparently converts these explicitly selected business rules into WHERE conditions in the SQL query. The collaboration and reuse of business rules is a user-visible and controllable process, ensuring the transparency and reliability of business logic. Furthermore, any updates to business rules will automatically and globally take effect here.

[0076] 3. Concurrent execution of multiple tasks: One of the core functions of the asynchronous engine in this invention is to support the parallel generation of multiple independent report tasks. For example, when users from multiple branch offices in different regions submit their respective regional transportation monthly report generation requests almost simultaneously, or when the same user submits multiple months' report tasks in batches, the system will place these tasks in an asynchronous queue and have them scheduled and executed in parallel by the engine. Each task runs independently within its own business theme and permission context, without interfering with each other. This granular parallel task processing mode enables the system to efficiently handle concurrent requests during peak business periods, upgrading the traditional sequential queuing generation mode to batch concurrent generation, greatly improving the overall data output efficiency of the organization.

[0077] 4. End-to-end status management and business auditing: State machine driven: Task states (new, waiting for scheduling, running, merging results, generating files, success / failure) are persisted in real time.

[0078] Upon successful completion of the task, the system not only uploads the generated "Monthly Transportation Revenue Report for 202x.xlsx" to storage, but more importantly, it permanently binds and records this file with the complete business context in the database, including: the theme used, the report template version, the injected permission filtering conditions, the application's sharing rule version, the user's identity, and the creation time. This ensures that every output report can be fully traced and audited.

[0079] Figure 3 This is another specific example diagram of a data collaborative processing system based on multi-service data in an embodiment of the present invention, as shown below. Figure 3 The diagram illustrates the overall implementation process of the system. After a user logs in, the system first verifies their topic access permissions and loads a list of available business topics. Once the user selects a business topic, the system dynamically connects to the underlying data source corresponding to that topic. Then, the system routes requests based on operation type: If defining a report, the system loads lists of grouping and statistical dimensions for the user to combine. After selecting a dimension combination, the user saves the template. This template can be used to distribute report copies, generating an independent copy for each authorized user and recording the distribution relationship. If generating a report, the system loads a list of saved reports and a condition configuration interface. After the user selects a report from the saved list, the system enters the intelligent condition configuration interface. Based on the field type, the system dynamically renders the corresponding input controls (such as calendar, dropdown list, and value range). After the user completes the condition input, the system receives data requests based on the input controls, enabling functions such as report preview, instant generation, and scheduled generation. The task is then handled by an asynchronous task engine in the background to generate the final report.

[0080] Two specific embodiments are given below to illustrate the implementation method based on the system.

[0081] Example 1: Agile creation and controlled distribution of sales business theme reports.

[0082] Scenario Name: Rapid Launch of Airline Sales Performance Themes and Personalized Applications for Branch Offices; Roles involved: System Administrator, Headquarters Sales Director, Branch Office Sales Manager; Addressing business pain points: slow response to new business needs, conflicts between headquarters templates and branch office personalized needs, and inconsistent data versions.

[0083] The core functionalities demonstrated are: dynamic business theme construction and report copy distribution.

[0084] Implementation steps: 1. Dynamic business theme construction: Administrators can enter the sales data table name in the interface, call the API, and generate a field tree without developing new code or modifying the database table structure. The system automatically explores its field structure.

[0085] 2. Customization of business dimensions: Administrators can drag and drop to set grouping and statistical dimensions, and save them as the "Sales Performance Theme". The configuration information is persisted to the relevant tables in the data warehouse, completing the dynamic binding and isolation between the data source and the business theme.

[0086] 3. Report Definition: The headquarters sales director logs in, selects "Sales Performance Theme," checks the above dimensions, and saves it as "Headquarters Sales Report." The report definition (dimensional combination only, not data) is saved to the REPORT table in the data warehouse, generating the source template.

[0087] 4. Controllable distribution of report copies: The director distributes the "Headquarters Sales Report" to the sales manager of branch office xx. The system generates a separate copy for the sales manager of branch office xx in the REPORT table. The templates for the director and the manager are separated at the data level, and the distribution record is saved to the data warehouse.

[0088] 5. Personalization modifications: A sales manager at branch office xx added a "Customer Rating" dimension to their copy, generating a "Detailed View of xx Region". This modification only affected the manager's copy; the source template at headquarters remained intact, achieving a balance between flexibility and consistency.

[0089] Example 2: Accurate and efficient end-to-end report generation.

[0090] Scenario Continuation: Continuing from the previous example, the users of branch office xx need to generate a third-quarter sales report.

[0091] 1. Precise data preparation (dynamic business subject isolation and access control): User Login: Based on the user's "xx branch sales" role, the system automatically limits the business topics that the user can access to to "sales performance topics", thus preventing cross-topic data access from the source.

[0092] Select Template: Users see copies of the "Sales Performance Reports of Each Branch" distributed from headquarters. This reflects the "report distribution" mechanism, ensuring flexibility while maintaining a unified template.

[0093] 2. Intelligent interactive configuration (intelligent mapping of field types): Setting conditions: Users add conditions. When "Ticket Issuance Date" is selected, the system intelligently renders a calendar control, allowing users to intuitively select BETWEEN '202x-07-01' AND '202x-09-30' without manually writing SQL, lowering the technical threshold and avoiding formatting errors.

[0094] The value of this step lies in transforming professional query criteria into form operations familiar to business personnel, which stems directly from the system's innovative intelligent rendering.

[0095] 3. Flexible report generation options (scheduled task scheduling): Users can choose to generate reports instantly or on a schedule when configuring report generation parameters. When choosing scheduled generation, the system provides additional options for the scheduling frequency and an email input field. After the scheduled task is saved, the system will create a corresponding scheduling task, automatically execute the report generation process at the specified time, and send the report to the designated recipient via email.

[0096] 4. Highly efficient and reliable task execution (asynchronous task engine): Click to generate: When a user submits a request, the system does not freeze the front-end interface. Instead, it immediately creates an asynchronous task, marks it as "new," and quickly returns a message to the user: "Task has been submitted, please wait for processing."

[0097] Background processing: The asynchronous task engine takes over the subsequent work: retrieves report dimensions and user conditions from the data warehouse; locates the uniquely bound data source table based on the user's "sales theme" and constructs a precise SQL query; executes the query and generates a file in the specified format (Excel / CSV); automatically uploads the file to the FTP server and updates the task status to "success"; when the user sees the status change to "success" in the task list, they can click to download and obtain the final report.

[0098] Decoupling user interaction from heavy backend computing ensures system response speed and stability in processing large volumes of data.

[0099] In this embodiment of the invention, report templates and conditional rules can be serialized into XML / JSON configuration files, which can then be distributed via file sharing or a version control system. Each node independently parses the configuration file and performs data queries.

[0100] In this embodiment of the invention, the dynamic theme construction mechanism enables rapid adaptation to business scenarios through table structure querying, dimension classification, and theme binding processes; thematic data product management encapsulates multiple physically independent or logically isolated data sources of an enterprise into multiple independent business data products, with each business data product serving as an atomic unit for data access and permission control; a dual-path distribution engine differentiates between report copy distribution and conditional rule sharing distribution, balancing flexibility and consistency requirements; intelligent field type mapping automatically selects input controls based on metadata, reducing the technical threshold for business personnel; asynchronous task state management drives large-scale data processing through a state machine, ensuring system response performance; and a unified permission gateway receives user data access requests and dynamically implements multi-level permission verification at the business data product level, data row level, and data column level based on the user's organizational role.

[0101] The embodiments of the present invention have the following technical effects: True data isolation is achieved: by dynamically binding the subject to the data source, cross-contamination of different business data is eliminated from the source, and data accuracy is significantly improved.

[0102] It provides fine-grained distribution control: the dual-path distribution engine perfectly balances flexibility and consistency, greatly reducing conflicts and repetitive work caused by version inconsistencies.

[0103] Improved business agility: New business themes can be quickly deployed through configuration, eliminating the need to develop dedicated systems or modify the underlying data warehouse structure, thus significantly improving the speed of response to business changes.

[0104] The user experience has been optimized and the barrier to entry has been lowered: intelligent rendering of field types allows business users to easily complete complex data filtering without a technical background, while retaining advanced interfaces for technical personnel.

[0105] The asynchronous task engine ensures that the generation of large amounts of data does not block user interaction, thereby improving the overall stability and concurrent processing capabilities of the system.

[0106] This invention provides flexible automated report generation capabilities through scheduled tasks. Users only need to configure the scheduling frequency and receiving email address once, and the system can automatically generate and distribute reports according to a preset cycle, significantly reducing manual operation costs. This module seamlessly integrates with existing asynchronous task engines, reusing report generation capabilities, and adds email notification functionality, forming a complete automated report workflow.

[0107] This invention also provides a data collaborative processing method based on multi-service data, as described in the following embodiments. Since the principle behind this method is similar to that of the data collaborative processing system based on multi-service data, its implementation can refer to the implementation of the data collaborative processing system based on multi-service data; repeated details will not be elaborated further.

[0108] Figure 4 This is a flowchart illustrating the data collaborative processing method based on multi-service data in an embodiment of the present invention, as shown below. Figure 4 As shown, this method is applied to a data collaborative processing system based on multi-service data, and the method includes: Step 401: Bind the specified data source to the business theme, receive the grouping dimension and statistical dimension of the business theme, and create a report template for the business theme using the specified data source, grouping dimension and statistical dimension; the grouping dimension is the row label of the report template, and the statistical dimension is used for numerical calculation. Step 402: Identify multiple authorized users of the report template; generate a copy of the report template that supports individual modification for each authorized user; distribute the conditional rules of the business topic to all authorized users; the conditional rules are used to limit operations on the content of the report template; Step 403: Based on the report template copy and the conditional rules of the business theme, provide an interactive interface; receive the report generation request input by the authorized user based on the interactive interface; Step 404: Generate multiple reports in parallel using asynchronous tasks.

[0109] In one embodiment, a specified data source is bound to a business topic, the grouping dimension and statistical dimension of the business topic are received, and a report template for the business topic is created using the specified data source, grouping dimension, and statistical dimension, including: Receive the business topic name and generate a blank report; The system receives the data source table name information through a declarative configuration interface, enabling the backend to: explore the table structure based on the data source table name information, generate and return a field tree; Display the field tree; Monitor user drag-and-drop operations, and based on these operations, select data dimensions from the field tree as grouping and statistical dimensions to embed into blank reports, generating report templates for business themes.

[0110] In one embodiment, the grouping dimension and the statistical dimension are mutually exclusive; the mutual exclusion means that the grouping dimension and the statistical dimension are prohibited from being used together.

[0111] In one embodiment, after creating a report template for a business theme using specified data sources, grouping dimensions, and statistical dimensions, the method further includes: Save the report templates for the business theme to the data warehouse and record the metadata information of the report templates for that business theme; the metadata information includes one or any combination of report dimension information, field type, creator, and version number.

[0112] In one embodiment, modifications made by an authorized user to a copy of a report template do not affect the copy of the report template made by other authorized users.

[0113] In one embodiment, when the report template for a business topic is updated, the updated copy of the report template for the authorized user is overwritten.

[0114] In one embodiment, a canary release is used to distribute the conditional rules of the business topic to all authorized users.

[0115] In one embodiment, the method further includes: assigning data access permissions to all users based on the organizational department to which the user belongs.

[0116] In one embodiment, receiving a report generation request input by an authorized user via an interactive interface includes: Based on the interactive interface, the system receives query condition fields input by authorized users and dynamically renders and displays matching input controls according to the query condition fields. The system receives data requests based on input controls and performs a report preview.

[0117] In one embodiment, the method further includes: using a task state machine to manage the task lifecycle of each authorized user's report generation request; the task state machine divides the task status into new, running, successful, and failed.

[0118] Figure 5 This is a schematic diagram of a computer device in an embodiment of the present invention, such as... Figure 5 As shown, this embodiment of the invention also provides a computer device 500, including a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501. When the processor 501 executes the computer program 503, it implements the above-mentioned data collaborative processing method based on multi-service data.

[0119] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned data collaborative processing method based on multi-service data.

[0120] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described data collaborative processing method based on multi-service data.

[0121] This invention implements fine-grained data access control based on topic encapsulation. Data product release steps: Respond to the administrator's configuration instructions, dynamically bind the backend data table with the frontend business theme to form a thematic data product with independent access permissions.

[0122] Collaborative authorization steps: Based on the enterprise's organizational structure, grant access permissions to one or more of the aforementioned themed data products to users with different roles, and configure their data row and column filtering rules within the product.

[0123] Differentiated distribution steps: In response to the distribution instruction, perform duplicate distribution of the report template and shared distribution of the business condition rules.

[0124] Request filtering steps: In response to the user's data extraction request, filter conditions based on user roles and row / column level permissions are injected twice, during the data query stage and the result return stage.

[0125] In dual-path distribution, the duplicate distribution of report templates supports overriding redistribution after the source template is modified, while the shared distribution of business condition rules supports real-time, silent global effect without user awareness or operation.

[0126] The business condition rules for distribution are released in a canary manner, that is, the new rules are first distributed to a group of designated users or units for testing, and then released to the entire organization after it is confirmed to be correct.

[0127] It provides a declarative configuration interface, allowing administrators to define the grouping and statistical dimensions of a topic by dragging and dropping, and strictly isolate the two in terms of interaction logic, prohibiting them from being mixed.

[0128] Based on the metadata type of the data field, the matching input control is dynamically rendered when the user sets the query conditions.

[0129] This invention enables new business data products to be configured and launched within 2 hours, allowing for rapid response to market changes. It reduces the time for critical business rules to synchronize and take effect across the entire domain from days to minutes, thereby improving decision-making efficiency and accuracy. While ensuring unified control of core data and rules by headquarters, it grants business units data autonomy within authorized scope, reducing maintenance frequency caused by data version conflicts by over 90%.

[0130] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied 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.

[0131] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0132] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0133] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0134] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A data collaborative processing system based on multi-service data, characterized in that, include: The module includes a themed data product management module, a dual-path distribution module, a conditional rendering module, and an asynchronous task engine module; The thematic data product management module is used to: bind a specified data source to a business theme, receive the grouping and statistical dimensions of the business theme, and create a report template for the business theme using the specified data source, grouping and statistical dimensions; the grouping dimension is the row label of the report template, and the statistical dimension is used for numerical calculations; The dual-path distribution module is used to: identify multiple authorized users of the report template; and generate a copy of the report template that supports individual modifications for each authorized user. Conditional rules for distributing business topics to all authorized users; these conditional rules are used to limit operations on report template content. The conditional rendering module is used to: provide an interactive interface based on the conditional rules of the report template copy and the business theme; and receive the report generation request input by the authorized user based on the interactive interface and send the report generation request to the asynchronous task engine module. The asynchronous task engine module is used to receive report generation requests from multiple authorized users and generate multiple reports in parallel through asynchronous tasks.

2. The data collaborative processing system based on multi-service data as described in claim 1, characterized in that, The thematic data product management module is specifically used for: Receive the business topic name and generate a blank report; The system receives the data source table name information through a declarative configuration interface, enabling the backend to: explore the table structure based on the data source table name information, generate and return a field tree; Display the field tree; Monitor user drag-and-drop operations, and based on these operations, select data dimensions from the field tree as grouping and statistical dimensions to embed into blank reports, generating report templates for business themes.

3. The data collaborative processing system based on multi-service data as described in claim 1, characterized in that, The grouping dimension and the statistical dimension are mutually exclusive; the mutual exclusion means that the grouping dimension and the statistical dimension are prohibited from being used together.

4. The data collaborative processing system based on multi-service data as described in claim 1, characterized in that, The thematic data product management module is also used for: Save the report templates for the business theme to the data warehouse and record the metadata information of the report templates for that business theme; the metadata information includes one or any combination of report dimension information, field type, creator, and version number.

5. The data collaborative processing system based on multi-service data as described in claim 1, characterized in that, Modifications made by an authorized user to a copy of a report template do not affect the copy of the report template for other authorized users.

6. The data collaborative processing system based on multi-service data as described in claim 1, characterized in that, The dual-path distribution module is specifically used for: When a business theme's report template is updated, the updated version of the report template for authorized users is overwritten.

7. The data collaborative processing system based on multi-service data as described in claim 1, characterized in that, The dual-path distribution module is specifically used for: The conditional rules for distributing business topics to all authorized users are implemented using a canary release approach.

8. The data collaborative processing system based on multi-service data as described in claim 1, characterized in that, Also includes: Unified access control module; The unified access control module is used to assign data access permissions to all users based on their organizational department.

9. The data collaborative processing system based on multi-service data as described in claim 1, characterized in that, The conditional rendering module is specifically used for: Based on the interactive interface, the system receives query condition fields input by authorized users and dynamically renders and displays matching input controls according to the query condition fields. The system receives data requests based on input controls and performs a report preview.

10. The data collaborative processing system based on multi-service data as described in claim 1, characterized in that, The asynchronous task engine module is also used for: A task state machine is used to manage the task lifecycle of each authorized user's report generation request; the task state machine divides the task status into new, running, successful, and failed.

11. A data collaborative processing method based on multi-service data, characterized in that, The method includes: Bind a specified data source to a business theme, receive the grouping and statistical dimensions of the business theme, and create a report template for the business theme using the specified data source, grouping and statistical dimensions; the grouping dimensions are the row labels of the report template, and the statistical dimensions are used for numerical calculations; Identify multiple authorized users for the report template; generate a copy of the report template that supports individual modifications for each authorized user; distribute conditional rules for the business topic to all authorized users; the conditional rules are used to limit operations on the content of the report template; Based on the report template copy and the conditional rules of the business topic, an interactive interface is provided; the report generation request input by the authorized user is received through the interactive interface; Multiple reports are generated in parallel using asynchronous tasks.

12. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of claim 11.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of claim 11.

14. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of claim 11.

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