Data analysis system, architecture method thereof, equipment, medium and program product

Abstract

The invention relates to a data analysis system, an architecture method thereof, equipment, a medium and a program product. The data analysis system comprises a controller module, a business model module, a data management module and a view module. And the controller module is configured to generate a control instruction in response to user operation, and coordinate and control information interaction between the business model module and the view module. And the business model module is connected with the controller module and is configured to respond to the control instruction to execute at least one data analysis processing business. And the data management module is connected with the business model module, and is configured to store and synchronize related data when the business model module executes the data analysis processing business based on the memory. And the view module is connected with the business model module and is configured to display the business process and related data when the business model module executes the data analysis processing business. The work efficiency of process window analysis can be improved.

Description

Technical Field

[0001] This disclosure relates to the field of semiconductor manufacturing technology, and in particular to a data analysis system and its architecture, method, apparatus, media, and program products. Background Technology

[0002] With the rapid development of advanced lithography technology research and development in China, a large amount of CD-SEM (Critical Dimension Scanning Electron Microscope) measurement data needs to be processed and analyzed. However, traditional manual processing methods are difficult to handle the generation of massive amounts of data such as line edge roughness (LER), line width roughness (LWR), and mask critical dimension uniformity map (CDU map), and cannot meet the large-scale business needs in real-world semiconductor manufacturing scenarios. Summary of the Invention

[0003] Therefore, it is necessary to provide a data analysis system and its architecture method, equipment, media and program products to address the above-mentioned technical problems, so as to improve the problems of high code coupling, unclear module structure, difficulty in code portability and poor software scalability in traditional software frameworks, thereby meeting the urgent needs of current business and improving the efficiency of process window analysis.

[0004] In a first aspect, embodiments of this disclosure provide a data analysis system, including: a controller module, a business model module, a data management module, and a view module. The controller module is configured to: generate control commands in response to user operations and coordinate and control the information interaction between the business model module and the view module. The business model module is connected to the controller module and is configured to: execute at least one data analysis and processing service in response to the control commands. The data management module is connected to the business model module and is configured to: store and synchronize relevant data during the execution of the data analysis and processing service by the business model module in memory. The view module is connected to the business model module and is configured to: display the business process and related data during the execution of the data analysis and processing service by the business model module.

[0005] In some embodiments of this disclosure, the business model module includes a license verification module. Correspondingly, the controller module is configured to generate a startup control command in response to a user operation. The view module is configured to display a license verification interface in response to the startup control command. The license verification module is configured to perform license verification in response to the startup control command, so that a data analysis and processing flow is initiated upon successful license verification, and the view module continues to display the license verification interface when the license verification fails.

[0006] In some embodiments of this disclosure, the business model module includes a parsing module. Correspondingly, the controller module is configured to generate a file retrieval command in response to a user operation. The parsing module is configured to retrieve a file to be parsed for data analysis processing in response to the file retrieval command, and parse the file to obtain a parsed file. The data management module is configured to store the parsed file in the memory to execute a data analysis processing flow based on the parsed file.

[0007] In some embodiments of this disclosure, the business model module includes: an audit module, an analysis module, and a data export module. Accordingly, the controller module is configured to: generate at least one of a data audit instruction, a data analysis instruction, or a data export instruction in response to a user operation. The audit module is configured to: perform data validity auditing, data deletion / modification, and data rollback in the data analysis processing business in response to the data audit instruction, and synchronize relevant data to the data management module. The analysis module is configured to: retrieve target data from the data management module for data analysis in response to the data analysis instruction, and synchronize relevant data to the data management module. The data export module is configured to: export target format data from the data management module in response to the data export instruction.

[0008] In some embodiments of this disclosure, the business model module further includes a backup module. Accordingly, the controller module is configured to generate a backup control command in response to a user operation. The backup module is configured to retrieve data to be backed up from the data management module and generate a backup file in response to the backup control command.

[0009] Secondly, embodiments of this disclosure provide an architecture method for a data analysis system, which may include the following steps.

[0010] The architecture controller module generates control commands in response to user actions. These control commands are used to coordinate the information interaction between the control business model module and the view module.

[0011] The business model module is configured such that it executes at least one data analysis and processing business in response to the control command.

[0012] The architecture includes a data management module that stores and synchronizes relevant data from the business model module during data analysis and processing based on memory.

[0013] The architecture view module displays the business process and related data when the business model module performs the data analysis and processing business.

[0014] In some embodiments of this disclosure, the architecture of the business model module enables the business model module to execute at least one data analysis and processing business in response to the control command, including at least one of the following embodiments;

[0015] In one implementation method, the control instructions for the controller module include a start control instruction;

[0016] The architecture includes a license verification module that responds to the start control command to perform license verification. If the license verification is successful, the data analysis and processing flow will be initiated. If the license verification fails, the view module will continuously display the license verification interface.

[0017] In the second implementation method, the control instructions of the controller module include file retrieval instructions;

[0018] The architecture parsing module is configured to respond to the file retrieval instruction to retrieve the file to be parsed for data analysis and processing, and to parse the file to obtain the parsed file.

[0019] In the third implementation method, the control instructions of the controller module include data verification instructions;

[0020] The architecture audit module enables the audit module to respond to the data audit instruction by performing data validity audit, data deletion and modification, and data rollback in the data analysis and processing business, and to synchronize relevant data to the data management module;

[0021] In implementation method four, the control instructions of the controller module include data analysis instructions;

[0022] The architecture analysis module enables the analysis module to retrieve target data from the data management module for data analysis in response to the data analysis command, and synchronize relevant data to the data management module.

[0023] In implementation method five, the control instructions of the controller module include data export instructions;

[0024] The architecture includes a data export module that, in response to a data export command, exports data in a target format from the data management module.

[0025] In implementation method six, the control instructions of the controller module include backup control instructions;

[0026] The architecture includes a backup module that, in response to a backup control command, retrieves the data to be backed up from the data management module to generate a backup file.

[0027] Thirdly, embodiments of this disclosure also provide a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement method steps for at least one data analysis and processing service of the data analysis system described in any of the embodiments of the first aspect.

[0028] Fourthly, embodiments of this disclosure also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements method steps for at least one data analysis and processing service of the data analysis system described in any of the embodiments of the first aspect.

[0029] Fifthly, embodiments of this disclosure also provide a program product having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the method steps of at least one data analysis and processing business of the data analysis system described in any of the embodiments of the first aspect.

[0030] The embodiments disclosed herein may have, or at least have, the following advantages:

[0031] In this embodiment, the data analysis system is built on the Model-View-Controller (MVC) framework, with the data management module as the data center. It can effectively separate control, model, and interface through the controller module, business model module, and view module, realizing the modularization of software functions to facilitate module code reuse and software function expansion. Furthermore, the data management module can realize data interaction and data synchronization between modules in the business model module to ensure the consistency and reliability of shared data, thereby realizing automated data processing and analysis, especially automated analysis and processing of SEM measurement data, which greatly improves the work efficiency of process window analysis.

[0032] Details of one or more embodiments of this disclosure are set forth in the following drawings and description. Other features, objects, and advantages of this disclosure will become apparent from the specification, drawings, and claims. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments or conventional technologies of this disclosure, the accompanying drawings used in the description of the embodiments or conventional technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a framework diagram of a data analysis system provided in some embodiments;

[0035] Figure 2 This is a schematic diagram of the structure of a business model module provided in some embodiments;

[0036] Figure 3 This is a schematic diagram of the structure of another business model module provided in some embodiments;

[0037] Figure 4 This is a flowchart of a data analysis and processing service provided in some embodiments;

[0038] Figure 5 This is a data flow diagram of a data analysis and processing service provided in some embodiments;

[0039] Figure 6 This is a flowchart illustrating an architecture method for a data analysis system provided in some embodiments;

[0040] Figure 7 This is an internal structural diagram of a computer device provided in some embodiments. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this disclosure.

[0042] To facilitate understanding of this disclosure, a more complete description will now be given with reference to the accompanying drawings, in which preferred embodiments of the present disclosure are shown. However, this disclosure may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure.

[0044] It should be understood that when a module is considered to be "connected" to another module, it can be directly connected to the other module or connected through an intermediary module. Furthermore, in the following embodiments, "connection" should be understood as "electrical connection," "communication connection," etc., if there is an exchange of electrical signals or data between the connected objects.

[0045] It should be understood that the singular forms of “a,” “an,” and “the” can also include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising / including” or “having,” etc., specify the presence of the stated features, wholes, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts, or combinations thereof. Meanwhile, when used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0046] This disclosure provides a data analysis system and its architecture method, device, medium, and program product, which improves the problems of high code coupling, unclear module structure, difficulty in code portability, and poor software scalability in traditional software frameworks, thereby meeting the urgent needs of current business and improving the efficiency of process window analysis.

[0047] Please see Figure 1 The data analysis system provided in this disclosure includes: a controller module, a business model module, a data management module, and a view module.

[0048] The controller module is configured to generate control commands in response to user actions and coordinate information interaction (including program flow control) between the business model module and the view module.

[0049] The business model module is connected to the controller module and is configured to execute at least one data analysis and processing service in response to the control command. For example, the data analysis and processing service includes at least the following operations: processing and storing data, analyzing and reading data, and synchronously updating data.

[0050] In one example, the data analysis and processing business includes the analysis and processing of SEM measurement data.

[0051] The data management module is connected to the business model module and is configured to store and synchronize relevant data from the business model module during data analysis and processing based on memory. In other words, the data management module can synchronize operational data (including data synchronization, data rollback, and data deletion / modification) from various modules within the business model module. Furthermore, by storing data in memory instead of writing to disk, the data management module offers more convenient data operations and aligns better with the modular, loosely coupled, highly cohesive, and singularity-based design principles in software design.

[0052] The view module is connected to the business model module and is configured to display the business process and related data when the business model module performs data analysis and processing. In other words, the view module can display the data processing data from the business model module and provide specific feedback.

[0053] In this embodiment, the data analysis system is built on the Model-View-Controller (MVC) framework, with the data management module as the data center. It can effectively separate control, model, and interface through the controller module, business model module, and view module, realizing the modularization of software functions to facilitate module code reuse and software function expansion. Furthermore, the data management module can realize data interaction and data synchronization between modules in the business model module to ensure the consistency and reliability of shared data, thereby realizing automated data processing and analysis, especially automated analysis and processing of SEM measurement data, which greatly improves the work efficiency of process window analysis.

[0054] Please see Figure 2 and Figure 3 In some embodiments of this disclosure, the business model module includes a license verification module. Correspondingly, the controller module is configured to generate a startup control command in response to a user operation. The view module is configured to display a license verification interface in response to the startup control command. The license verification module is configured to perform license verification in response to the startup control command, so that a data analysis and processing flow is initiated upon successful license verification, and the view module continues to display the license verification interface when the license verification fails.

[0055] Here, the license settings can be selected to match your needs. Any image or password that can be used for authentication can be set as the corresponding license, but it is not limited to this.

[0056] This embodiment of the disclosure includes a license verification module within the business model module. After the user starts the data analysis software, the license verification module performs license verification via a start control command transmitted from the controller module. If the license verification is successful, the subsequent data analysis processing flow begins. If the license verification fails, the view module continuously displays the license verification interface (also known as the license input interface). This helps ensure the security of the data analysis software and maintain data confidentiality.

[0057] Please see Figure 2 and Figure 3In some embodiments of this disclosure, the business model module further includes a parsing module. Accordingly, the controller module is configured to generate a file retrieval command in response to a user operation. The parsing module is configured to retrieve a file to be parsed for data analysis processing in response to the file retrieval command, and parse the file to obtain a parsed file. The data management module is configured to store the parsed file in memory to execute a data analysis processing flow based on the parsed file.

[0058] For example, the files to be parsed include, but are not limited to, Msr (Measurement Studio Report) files. Msr files are report files generated by the machine software and are used to store test results and measurement data.

[0059] In this embodiment of the disclosure, a parsing module is set in the business model module. The parsing module can be used to convert file formats so that data interaction can be carried out in memory based on the data management module.

[0060] Please continue reading. Figure 2 and Figure 3 In some embodiments of this disclosure, the business model module further includes: an audit module, an analysis module, and a data export module. Accordingly, the controller module is configured to: generate at least one of a data audit instruction, a data analysis instruction, or a data export instruction in response to user operations. The audit module is configured to: perform data validity auditing, data deletion / modification, and data rollback in the data analysis processing business in response to the data audit instruction, and synchronize relevant data to the data management module. The analysis module is configured to: retrieve target data from the data management module for data analysis in response to the data analysis instruction, and synchronize relevant data to the data management module. The data export module is configured to: export target format data from the data management module in response to the data export instruction.

[0061] Therefore, this embodiment of the disclosure includes an audit module in the business model module, which can verify the validity of data, including image data. Furthermore, the audit module also has business functions for deleting, modifying, and rolling back data. After a user's operation, the modified or rolled-back data can be synchronized to the data management center. Here, data rollback refers to restoring data to its previous correct state to eliminate erroneous or non-compliant data operations, thereby ensuring data security. This ensures that other modules obtain the latest data when the user operates on them, thus guaranteeing the data consistency business requirements. This embodiment of the disclosure also includes an analysis module in the business model module, which can retrieve target data from the data management module for data analysis and synchronize related data to the data management module. The analysis module can be specifically configured to match data analysis and processing requirements to execute the necessary data analysis and processing business. This embodiment of the disclosure also includes a data export module in the business model module, which can export target format data from the data management module for user review and subsequent use.

[0062] Please see Figure 3 For example, the analysis module includes an FEM (Focus Energy Matrix) analysis module; where F (i.e., Focus) represents the depth of focus and E (i.e., Energy) represents the exposure energy.

[0063] FEM data can be understood as a set of data obtained during photoresist exposure by changing the depth of focus in one direction with a first fixed step size and the exposure energy in another direction with a second fixed step size. In actual photolithography processes, certain instabilities exist; for example, the exposure energy and depth of focus can fluctuate within the lithography machine. Therefore, within a certain range of exposure energy variation ΔE and depth of focus variation ΔF, the photolithography process must provide a acceptable CD value. This necessitates process window analysis of the FEM experimental data. This can be achieved by inputting complete FEM data, the target linewidth value, and the acceptable linewidth variation range (CD tolerance). The acceptable linewidth range is generally around ±10% of the target linewidth value, for example, ±8%.

[0064] In some examples, the FEM analysis module can perform at least one of FEM data analysis, color gradation analysis (including LER, LWR and CDUMap data analysis), or wafer map distribution data analysis.

[0065] Please see Figure 3For example, the analysis module also includes a PWED (Process Window Etch Depth) analysis module; where PW (Process Window) represents the process window and ED (Etch Depth) represents the etching depth.

[0066] As can be understood, the PWED analysis module is used to analyze PWED data. PWED data refers to the acceptable range of each process parameter and the target depth that can be achieved during the etching process.

[0067] Please continue reading. Figure 2 and Figure 3 In some embodiments of this disclosure, the business model module further includes a backup module. Accordingly, the controller module is configured to generate a backup control command in response to a user operation. The backup module is configured to retrieve data to be backed up from the data management module and generate a backup file in response to the backup control command.

[0068] This embodiment of the disclosure includes a backup module within the business model module. When a user requires backup, the backup module retrieves the data to be backed up from the data management module and generates a backup file. The backup file contains at least the data modified and updated during the data analysis and processing operations, and can be stored, for example, as an Msr file.

[0069] To more clearly illustrate the data analysis system in the above embodiments, Figure 4 A flowchart of a data analysis and processing business is shown. Figure 5 A data flow diagram for a data analysis and processing business is shown. The following examples are combined with... Figure 4 and Figure 5 The data analysis system was described in further detail.

[0070] After the user starts the data analysis software, the view module displays the license verification interface. The license verification module performs license verification so that the data analysis processing flow can be started after the license verification is successful. If the license verification fails, the view module will continue to display the license verification interface.

[0071] When the data analysis and processing flow is initiated, if the file to be analyzed is a file to be parsed, the parsing module will retrieve the file to be parsed for data analysis and processing, and obtain the parsed file. Accordingly, the data management module stores the parsed file in memory.

[0072] Secondly, to match users' data analysis and processing needs, the audit module responds to the controller module's data audit instructions by performing data validity checks, data deletion / modification, and data rollback within the data analysis and processing business, and can synchronize relevant data to the data management module. The data audited by the audit module includes, but is not limited to, image data, such as SEM image data. The data deletion / modification that the audit module can perform includes, but is not limited to, CD values ​​and image status.

[0073] Based on this, the analysis module responds to the data analysis commands from the controller module by retrieving target data from the data management module for data analysis, and can synchronize relevant data to the data management module. For example, the FEM analysis module can perform at least one of FEM data analysis, color level analysis (including LER, LWR, and CDU Map data analysis), or wafer map distribution data analysis; the PWED analysis module is used to analyze PWED data; and the FEM analysis module can also provide data modification services for modifying CD values ​​and image status. After the user opens other modules, the relevant data synchronized in the data management module can be synchronized to the display interface of the view module, so that the user can perform data analysis operations on the latest data, ensuring data consistency and reliability when the user operates the business.

[0074] Then, in response to the data export command from the controller module, the data export module exports data in the target format from the data management module. The target format data includes, but is not limited to, Mentor Graphics format gauging files, Brion format gauging files, CD values ​​of each measurement point (MP point) in the Msr file, data analysis charts of the selected MP points, and wafer map distribution of the selected MP points.

[0075] Subsequently, when a user requests a backup, the backup module, responding to the backup control command from the controller module, retrieves the data to be backed up from the data management module and generates a backup file. The backup file contains at least the data modified and updated during the data analysis and processing operations, and can be stored as an Msr file.

[0076] Therefore, in the overall data analysis and processing workflow of the data analysis system, centering on the data management module ensures that all data display, analysis, modification, querying, and rollback operations within the business model module revolve around the data management module. Furthermore, data deletion and modification operations performed by each module in the business model module are promptly synchronized to the data management module, allowing any module connected to the data management module to obtain the latest data, effectively guaranteeing the data sharing and consistency requirements of the data analysis software. Moreover, the data management module also enables data rollback, allowing data to be restored to a previous correct state to eliminate erroneous or non-compliant data operations, thus effectively ensuring the software's data security.

[0077] In summary, the embodiments of this disclosure fully leverage the advantages of automated analysis in computer software. After designing and developing a data analysis system based on the MVC framework, control, model, and interface can be effectively separated through controller modules, business model modules, and view modules. This modularization of software functions facilitates code reuse and software expansion, effectively improving the problems of high code coupling, unclear module structure, difficult code portability, and poor software scalability in traditional software frameworks. Furthermore, addressing the needs of data analysis and processing, the embodiments of this disclosure propose a comprehensive data interaction method centered on a data management module and permeating all modules within the business model module. This effectively integrates functional modules such as file parsing, data review, data export, FEM data analysis, and PWED data analysis, thereby meeting the urgent needs of current business operations and improving the efficiency of process window analysis.

[0078] In the data analysis systems provided in the above embodiments, the term "module" and the like used in this specification can be used to refer to computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution. For example, a "module" can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. For example, a "module" can be executed from various computer-readable media on which various data structures are stored. Furthermore, in the above embodiments provided in this disclosure, it should be understood that the disclosed "modules" can be implemented in other ways. For example, the modules described above are merely illustrative. For example, the division of modules is merely a logical functional division, and in actual implementation, there may be other division methods, such as multiple modules can be combined or integrated into another module, or some features can be ignored or not executed. The described interconnections can be through some interfaces, indirect coupling or communication connections between modules, and can be electrical, mechanical, or other forms. Modules described separately may or may not be physically separated. Some or all of the modules can be selected to achieve the purpose of the embodiments of this disclosure according to actual needs.

[0079] Based on the same inventive concept, this disclosure also provides an architectural method for implementing the data analysis system described above. The solution provided by this method is similar to the implementation scheme described in the data analysis system above. Therefore, the specific limitations in the one or more data analysis system architectural method embodiments provided below can be found in the relevant limitations of the data analysis system described above, and will not be repeated here.

[0080] Please see Figure 6 The architecture method of the data analysis system provided in some embodiments of this disclosure may include the following steps S100~S400.

[0081] S100, the architecture controller module, enables the controller module to generate control commands in response to user operations. These control commands are used to coordinate the information interaction between the control business model module and the view module.

[0082] S200, Architectural business model module, causing the business model module to execute at least one data analysis and processing business in response to the control command.

[0083] S300 is an architecture data management module that enables the data management module to store and synchronize relevant data with the business model module when performing data analysis and processing business based on memory storage.

[0084] S400, the architecture view module, enables the view module to display the business processes and related data when the business model module performs data analysis and processing.

[0085] In some embodiments of this disclosure, different modules in the business model module are matched, and the business model module is structured in step S200 so that the business model module performs at least one data analysis and processing business in response to the control command. This may include at least one of the following embodiments.

[0086] In the first implementation, the control instructions of the controller module include a start control instruction. Accordingly, in step S200, a license verification module is configured to perform license verification in response to the start control instruction. If the license verification is successful, the data analysis and processing flow is initiated; if the license verification fails, the view module continues to display the license verification interface.

[0087] In the second implementation method, the control instructions of the controller module include file retrieval instructions. Accordingly, in step S200, a parsing module is configured to respond to the file retrieval instructions, retrieve the file to be parsed for data analysis and processing, and parse the file to obtain a parsed file.

[0088] In the third implementation method, the control instructions of the controller module include data audit instructions. Accordingly, in step S200, an audit module is constructed, which responds to the data audit instructions by performing data validity audits, data deletions and modifications, and data rollbacks in the data analysis and processing business, and synchronizes relevant data to the data management module.

[0089] In the fourth implementation method, the control commands of the controller module include data analysis commands. Accordingly, in step S200, an analysis module is configured so that, in response to the data analysis commands, the analysis module retrieves target data from the data management module for data analysis and synchronizes relevant data to the data management module.

[0090] For example, the analysis modules include the FEM analysis module and the PWED analysis module.

[0091] In implementation method five, the control instructions of the controller module include data export instructions. Accordingly, in step S200, a data export module is configured so that the data export module exports target format data from the data management module in response to the data export instructions.

[0092] In implementation method six, the control instructions of the controller module include backup control instructions. Accordingly, in step S200, a backup module is configured, which, in response to the backup control instructions, retrieves the data to be backed up from the data management module to generate a backup file.

[0093] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0094] In some embodiments, this disclosure also provides 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 at least one data analysis and processing service method step of the data analysis system involved in the above embodiments.

[0095] For example, the computer device may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown.

[0096] The computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface 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 interface. The processor provides computational 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 interface is 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 at least one data analysis and processing method step of the data analysis system described above. 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.

[0097] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the computer device to which the present disclosure is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0098] In some embodiments, this disclosure also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the method steps of at least one data analysis and processing service of the data analysis system involved in the above embodiments.

[0099] In some embodiments, this disclosure also provides a program product having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the method steps of at least one data analysis and processing business of the data analysis system involved in the above embodiments.

[0100] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this disclosure can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this disclosure may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this disclosure may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0101] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0102] The embodiments described above are merely illustrative of several implementations of this disclosure, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent disclosure. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this disclosure, and these all fall within the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be determined by the appended claims.

Claims

1. A data analysis system, characterized in that, include: The module comprises a controller module, a business model module, a data management module, and a view module; among which, The controller module is configured to: generate control commands in response to user operations, and coordinate and control the information interaction between the business model module and the view module; The business model module is connected to the controller module and is configured to execute at least one data analysis and processing business in response to the control command. The data management module is connected to the business model module and is configured to: store and synchronize relevant data when the business model module executes the data analysis and processing business based on memory; The view module is connected to the business model module and is configured to display the business process and related data when the business model module performs the data analysis and processing business.

2. The data analysis system according to claim 1, characterized in that, in, The business model module includes: a license verification module; wherein... The controller module is configured to generate a start control command in response to a user operation; The view module is configured to display a license verification interface in response to the startup control command; The license verification module is configured to: perform license verification in response to the start control command, so as to start the data analysis and processing flow after the license verification is successful, and to make the view module continuously display the license verification interface when the license verification fails.

3. The data analysis system according to claim 1, characterized in that, The business model module includes: a parsing module; wherein... The controller module is configured to generate a file retrieval command in response to a user operation. The parsing module is configured to: in response to the file retrieval instruction, retrieve the file to be parsed for data analysis and processing, and parse the file to be parsed to obtain a parsed file; The data management module is configured to store the parsed file in the memory to perform a data analysis and processing flow based on the parsed file.

4. The data analysis system according to claim 1, characterized in that, The business model module includes: an audit module, an analysis module, and a data export module; wherein... The controller module is configured to generate at least one of a data audit instruction, a data analysis instruction, or a data export instruction in response to a user operation. The audit module is configured to: respond to the data audit instruction by performing data validity audit, data deletion and modification, and data rollback in the data analysis and processing business, and synchronize relevant data to the data management module; The analysis module is configured to: retrieve target data from the data management module for data analysis in response to the data analysis command, and synchronize relevant data to the data management module; The data export module is configured to export target format data from the data management module in response to the data export command.

5. The data analysis system according to any one of claims 1 to 4, characterized in that, The business model module further includes: a backup module; wherein... The controller module is configured to generate backup control commands in response to user operations; The backup module is configured to: in response to the backup control command, retrieve the data to be backed up from the data management module and generate a backup file.

6. An architectural method for a data analysis system, characterized in that, include: An architecture controller module is configured to generate control commands in response to user operations. The control commands are used to coordinate the information interaction between the control business model module and the view module; The business model module is configured such that it executes at least one data analysis and processing business in response to the control command. The architecture includes a data management module that stores and synchronizes relevant data from the business model module during data analysis and processing based on memory. The architecture view module displays the business process and related data when the business model module performs the data analysis and processing business.

7. The architecture method of the data analysis system according to claim 6, characterized in that, The architecture of the business model module enables the business model module to execute at least one data analysis and processing business in response to the control command, including at least one of the following embodiments; In one implementation method, the control instructions for the controller module include a start control instruction; The architecture includes a license verification module that responds to the start control command to perform license verification. If the license verification is successful, the data analysis and processing flow will be initiated. If the license verification fails, the view module will continuously display the license verification interface. In the second implementation method, the control instructions of the controller module include file retrieval instructions; The architecture parsing module is configured to respond to the file retrieval instruction to retrieve the file to be parsed for data analysis and processing, and to parse the file to obtain the parsed file. In the third implementation method, the control instructions of the controller module include data verification instructions; The architecture audit module enables the audit module to respond to the data audit instruction by performing data validity audit, data deletion and modification, and data rollback in the data analysis and processing business, and to synchronize relevant data to the data management module; In implementation method four, the control instructions of the controller module include data analysis instructions; The architecture analysis module enables the analysis module to retrieve target data from the data management module for data analysis in response to the data analysis command, and synchronize relevant data to the data management module. In implementation method five, the control instructions of the controller module include data export instructions; The architecture includes a data export module that, in response to a data export command, exports data in a target format from the data management module. In implementation method six, the control instructions of the controller module include backup control instructions; The architecture includes a backup module that, in response to a backup control command, retrieves the data to be backed up from the data management module to generate a backup file.

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 at least one data analysis and processing business method step of the data analysis system according to any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method steps of at least one data analysis and processing business of the data analysis system according to any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the method steps of at least one data analysis and processing business of the data analysis system according to any one of claims 1 to 5.

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