Data customization analysis method, device, terminal and computer storage medium

Abstract

The application relates to a data customized analysis method, device, terminal and computer storage medium, and belongs to the technical field of statistical analysis, wherein the data customized analysis method comprises the following steps: in response to a form making operation of a user, selecting corresponding form components in a preset form component library, arranging the form components, and generating a data filling form template; constructing a data dictionary, associating the form components in the data filling form template with the data dictionary, establishing cascade rules of each form component in the data filling form template, and configuring check rules of corresponding fields of each form component in the data filling form template; receiving data entered by the user based on the data filling form, checking the data based on the cascade rules and the check rules, analyzing the data in the data filling form based on analysis requirements after the checking is completed, and obtaining a data analysis result. The application can accurately perform customized analysis on data.

Description

Technical Field

[0001] This invention relates to the field of statistical analysis technology, and in particular to a data customization analysis method, apparatus, terminal, and computer storage medium. Background Technology

[0002] In the field of information and communication, the importance of data is becoming increasingly prominent, and the management and application of information and communication data are becoming increasingly complex. Data entry, as the foundation for data transmission, directly affects the accuracy, effectiveness, and scientific nature of communication decision support.

[0003] Most existing data entry systems are based on fixed templates, requiring repetitive manual processing of communication data across multiple systems within the same organization, hindering customized statistical analysis. Information and communication data typically includes multi-source, heterogeneous data such as equipment operating status, network performance indicators, and user behavior records. Currently, data entry relies heavily on manual submission, resulting in low processing efficiency, inconsistent data formats, and difficulty in meeting personalized needs. However, historical communication data plays a crucial role in ensuring communication missions, characterized by its real-time nature, large volume, and diverse types. Therefore, how to efficiently and accurately collect and statistically analyze massive amounts of data to extract valuable information to support communication decision-making has become an urgent problem to be solved.

[0004] This demonstrates that existing technologies cannot perform precise, customized data analysis. Summary of the Invention

[0005] In view of this, it is necessary to provide a data customization analysis method, device, terminal, and computer storage medium to solve the problem that existing technologies cannot perform accurate customized data analysis.

[0006] To address the aforementioned problems, in a first aspect, the present invention provides a data customization analysis method, comprising: In response to the user's form creation operation, the system selects the corresponding form component from the preset form component library, lays out the form component, and generates a data entry form template. A data dictionary is constructed based on the industry characteristics of the data to be analyzed. The form components in the data entry form template are associated with the data dictionary. The data dictionary is used to limit the values ​​in the form components, establish the cascading rules of each form component in the data entry form template, configure the validation rules of the corresponding fields of each form component in the data entry form template, and generate the data entry form. It receives data entered by users based on data entry forms, fills the data into the corresponding fields of the data entry forms, validates the data based on cascading rules and validation rules, and analyzes the data in the data entry forms based on analysis requirements after validation to obtain data analysis results.

[0007] In one possible implementation, the form creation operation includes component selection, component layout, and attribute configuration. Responding to the user's form creation operation, the corresponding form component is selected from a pre-defined form component library, and the form component is laid out to generate a data entry form template, including: In response to the user's component selection action, select the corresponding form component from the preset component area; In response to user component layout operations, the layout of form components is adjusted in the preset component editing area; Configure the properties of form components in response to user property configuration actions.

[0008] In one possible implementation, a data dictionary is constructed based on the industry characteristics of the data to be analyzed, including: Dictionary identifiers are determined based on the terminology, indicators, processes, operating procedures, and technical standards of the industry to which the data to be analyzed belongs; The dictionary value corresponding to the dictionary identifier is determined based on the field value requirement of the dictionary identifier, and a data dictionary is constructed based on the dictionary identifier and the dictionary value.

[0009] In one possible implementation, cascading rules are established for each form component in the data entry form template, and validation rules for the corresponding fields of each form component in the data entry form template are configured, including: The cascading rules for each form component are constructed based on the cascading relationship between the dictionary identifiers of the data dictionaries associated with each form component in the data entry form template. The validation rules for each field in each form component are defined based on the attribute definitions of the corresponding fields in the data entry form template.

[0010] In one possible implementation, the system receives data entered by the user based on a data entry form and fills the data into the corresponding fields of the data entry form, including: When the form field type is configured as a fixed value, the corresponding field value is entered directly; When a form field is configured for dynamic association, the field value is configured as either a data dictionary or dynamic data. If configured as a data dictionary, it is associated with an existing data dictionary; if configured as dynamic data, it interacts with a third-party system for data exchange. When a form field is configured for formula calculation, the calculation formula is edited based on the field in the form to calculate the value of the form field.

[0011] In one possible implementation, data is validated based on cascading rules and verification rules. After validation, the data in the data entry form is analyzed based on analysis requirements, including: Verify whether the values ​​of the corresponding fields of each form component in the data entry form meet the cascading rules and validation rules. If they do, analyze the data in the data entry form based on the analysis requirements. If they do not meet the requirements, output a validation prompt message.

[0012] In one possible implementation, the data in the data entry form is analyzed based on analytical requirements to obtain data analysis results, including: Determine the time dimension, spatial dimension, and type dimension of data analysis based on the analysis requirements; The data in the data entry form is analyzed from multiple dimensions, including time, space, and type, and the analysis results are visualized using graphical methods.

[0013] Secondly, the present invention also provides a data customization analysis device, comprising: The form building module is used to respond to the user's form creation operation, select the corresponding form component from the preset form component library, lay out the form component, and generate a data entry form template. The form association module is used to build a data dictionary based on the industry characteristics of the data to be analyzed, associate the form components in the data entry form template with the data dictionary, whereby the data dictionary is used to limit the values ​​in the form components, establish cascading rules for each form component in the data entry form template, configure the validation rules for the corresponding fields of each form component in the data entry form template, and generate the data entry form. The data entry and analysis module is used to receive data entered by users based on data entry forms, fill the data into the corresponding fields of the data entry forms, validate the data based on cascading rules and validation rules, and analyze the data in the data entry forms based on analysis requirements after validation to obtain data analysis results.

[0014] Thirdly, the present invention also provides a data analysis terminal, including a front-end interactive interface, a memory, and a processor, wherein, The front-end interactive interface is used to receive user operations and display data entry forms and data analysis results; Memory, used to store programs; A processor, coupled to memory, is used to execute programs stored in memory to implement the steps in the data customization analysis method of any of the above implementations.

[0015] Fourthly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, can implement the steps in the data customization analysis method of any of the above implementation methods.

[0016] The beneficial effects of this invention are as follows: The data customization analysis method provided by this invention, in response to the user's form creation operation, selects the corresponding form component from a preset form component library, lays out the form component, and generates a data entry form template; it can generate customized data entry form templates according to user operations, meeting the needs of different users; it constructs a data dictionary based on the industry characteristics of the data to be analyzed, and associates the form components in the data entry form template with the data dictionary, wherein the data dictionary is used to limit the values ​​in the form components, establish cascading rules for each form component in the data entry form template, configure the validation rules for the corresponding fields of each form component in the data entry form template, and generate a data entry form; it constructs data dictionaries for different types of data to be analyzed and associates the data dictionaries with the data entry form template, which can be applied to the filling of different types of data, and ensures the accuracy of data filling by constructing cascading rules and validation rules. By receiving data entered by users based on data entry forms and filling the corresponding fields in the forms, the data is validated based on cascading rules and validation rules. After validation, the data in the data entry forms is analyzed based on analysis requirements to obtain data analysis results. After validating the fields in each form component of the data entry form, the analysis is performed based on user analysis requirements, ensuring data accuracy while realizing customized data analysis. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0018] Figure 1 A flowchart illustrating a data customization analysis method provided in an embodiment of the present invention; Figure 2 A functional module diagram of a data customization analysis system provided for the implementation of this invention; Figure 3 A flowchart illustrating a form template construction method provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the form customization module provided in an embodiment of the present invention; Figure 5 A flowchart illustrating a data dictionary construction method provided in an embodiment of the present invention; Figure 6 A flowchart illustrating a verification method provided in an embodiment of the present invention; Figure 7 A flowchart illustrating a data analysis method provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of a data customization analysis device provided in an embodiment of the present invention; Figure 9 This is a schematic diagram of the structure of a data analysis terminal provided in an embodiment of the present invention. Detailed Implementation

[0019] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0020] In the description of the embodiments of the present invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0021] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] A specific embodiment of the present invention, such as Figure 1 As shown, a data customization analysis method is disclosed, including: S101, in response to the user's form creation operation, selects the corresponding form component from the preset form component library, lays out the form component, and generates a data entry form template.

[0024] In this embodiment of the invention, users select and arrange components from a component library through visual operations to quickly generate form templates. Subsequently, a data dictionary deeply bound to the industry characteristics of the data to be analyzed is constructed. This dictionary not only defines the legal set of optional values ​​for components but also carries the cascading dependencies between components. Simultaneously, fine-grained validation rules are configured for each field. The resulting form essentially embeds the industry's knowledge system and data quality standards. When data is entered, cascading rules dynamically constrain user input, and validation rules intercept abnormal data in real time, greatly improving the accuracy of data collection. After data validation is completed, analysis can be directly performed on the high-quality collected data based on analytical needs. Because the entire process, from form definition and rule injection to analysis triggering, is connected by the same configuration link, the analytical dimensions and collected indicators can flexibly correspond, truly realizing customized analysis for the information and communication industry.

[0025] Specifically, the form component library includes various types of text boxes, numeric boxes, dropdown selection boxes, cascading selection boxes, date pickers, and file upload components. Users can drag and drop these components to adjust their size and position, generating grid-layout form templates. For example, network optimization engineers need to regularly collect operational data from various base stations, such as traffic, number of users, and alarm information, to analyze network load and fault distribution. However, the key metrics for different regions and projects frequently change, making traditional, fixed data collection forms unsuitable. In this method, engineers open a visual form design interface. On the left side of the interface is a pre-set form component library, which displays text boxes, numeric boxes, dropdown selection boxes, cascading selection boxes, date pickers, and file upload components. Engineers drag and drop components to the central canvas area according to the needs of the analysis task and arrange the components. For example, dragging a "Base Station Name" text box, a "City of Origin" cascading selection box, a "Base Station Type" dropdown selection box, a "Downlink Peak Traffic" numeric box, and a "Current Alarm Level" dropdown selection box. A well-structured data entry form template is generated through simple drag-and-drop, stretching, and alignment operations. This template is essentially a configuration set describing component types, attributes, locations, and identifiers, and can be saved in a structured data format for easy reuse and version management.

[0026] S102, construct a data dictionary based on the industry characteristics of the data to be analyzed, associate the form components in the data entry form template with the data dictionary, wherein the data dictionary is used to limit the values ​​in the form components, establish cascading rules for each form component in the data entry form template, configure the validation rules for the corresponding fields of each form component in the data entry form template, and generate the data entry form.

[0027] In the embodiments of the present invention, all fields involved in the information communication sub-domain and their corresponding standard codes, Chinese names, and data types are determined; legal value ranges, enumerated value sets, or reference relationships between data dictionaries are defined for each field; for fields with hierarchical subordinate relationships, their parent-child structures are stored in the data dictionary to support subsequent cascading rules. The fields with parent-child relationships in the data dictionary are bound to form components, and it is defined how the change of the value of the parent component filters and refreshes the optional value list of the child component. For example, after a value in the "Province" component is selected, the drop-down list of the "City" component only displays the cities under the selected province, and the constraint comes from the pre-stored administrative division hierarchy in the data dictionary.

[0028] For example, for the industry feature of wireless network optimization, the system presets or allows engineers to import data dictionaries with industry attributes. This dictionary is a complete set of data definitions, which includes but is not limited to the following entries: the unique field identifier "CELL_ID", Chinese name "cell number", data type "string"; the field "BS_TYPE", Chinese name "base station type", enumerated value set "macro base station, micro base station, pico base station, femto base station"; the field "ALARM_LEVEL", enumerated value set "critical, major, minor, prompt"; the parent-child hierarchical relationship of administrative divisions is stored between the fields "PROVINCE" and "CITY", and so on. The contents of these dictionaries accurately characterize the knowledge system in the field of communication network management.

[0029] After the binding of components and dictionary values is completed, cascading rules between form components are further established. The data basis of the cascading rules is exactly the hierarchical relationship predefined in the data dictionary. In this embodiment, an engineer configures a cascading rule: first select "device manufacturer", then the optional items of "device model" are automatically filtered according to the manufacturer dictionary, and only the model list of the manufacturer registered in the network management system is displayed. In this way, the cascading rules enforce the logical consistency between data at the user operation level, and eliminate cross-field mismatch errors.

[0030] Subsequently, fine-grained validation rules are configured for the fields corresponding to each component in the form template. For example, the number box of "downlink peak traffic" is configured with a value range validation, which requires the filled value to be greater than or equal to zero and not exceed a preset physical upper limit; the text box of "base station name" is configured with non-null validation and regular format validation, to ensure that the naming follows the specification of "region abbreviation - site number"; "cell number" is configured with uniqueness validation, to ensure no duplicate entries in the same form. These validation rules are stored together as the metadata of the form template. So far, a data entry form integrating industry dictionary constraints, cascading dependency logic and strict validation rules is generated, and can be released to front-line collection personnel for use.

[0031] S103 receives data entered by the user based on the data entry form, fills the data into the corresponding fields of the data entry form, validates the data based on cascading rules and validation rules, and analyzes the data in the data entry form based on the analysis requirements after the validation is completed to obtain the data analysis results.

[0032] In this embodiment of the invention, each operation is immediately validated by the system's rules when a user selects or enters data in the form. If a user attempts to enter a word not included in the dictionary's enumeration values ​​in the "Base Station Type" dropdown, the component will fail to complete the input and provide a helpful prompt. If a user omits the "Base Station Name," the form will highlight the field and indicate that it must be filled in when the user clicks submit or switches to the next item. If a user mistakenly enters a negative number in "Downlink Peak Traffic," the system immediately intercepts it and displays the correct value range. The entire validation process is completed collaboratively by the front-end component and the back-end validation logic. Based on cascading rules and validation rules, dual filtering ensures that only completely legal, accurate, and consistent data streams can be imported into the back-end temporary dataset. This mechanism fundamentally solves the problem of inconsistent data quality during massive data collection.

[0033] Once all required data passes validation and is securely stored in the dataset associated with the form, analysis can be triggered directly. The analysis process is not a rigid, fixed report, but rather a customized process driven by analytical needs. In the form interface or the associated analysis portal, users can see a series of configurable analysis requirement options. These options are pre-configured analysis model identifiers based on communication optimization services, such as "average traffic statistics by base station type," "alarm severity level distribution by city," and "ranking of high-load macro base stations."

[0034] The data customization analysis method provided by this invention, such as Figure 2As shown, by responding to the user's form creation operation, the system selects the corresponding form component from the preset form component library, lays out the form component, and generates a data entry form template. Customizable data entry form templates can be generated based on user operations to meet the needs of different users. A data dictionary is constructed based on the industry characteristics of the data to be analyzed, and the form components in the data entry form template are associated with the data dictionary. The data dictionary is used to limit the values ​​in the form components and establish cascading rules for each form component in the data entry form template. Validation rules for the corresponding fields of each form component in the data entry form template are configured, and a data entry form is generated. Constructing data dictionaries for different types of data to be analyzed and associating the data dictionaries with the data entry form template allows for the submission of different types of data. Furthermore, by constructing cascading rules and validation rules, the accuracy of the data submission is ensured. By receiving data entered by users based on data entry forms and filling the corresponding fields in the forms, the data is validated based on cascading rules and validation rules. After validation, the data in the data entry forms is analyzed based on analysis requirements to obtain data analysis results. After validating the fields in each form component of the data entry form, the analysis is performed based on user analysis requirements, ensuring data accuracy while realizing customized data analysis.

[0035] In some possible embodiments of the present invention, such as Figure 3 As shown, the form creation operation includes component selection, component layout, and attribute configuration. Responding to the user's form creation operation, the system selects the corresponding form component from the preset form component library, lays out the form component, and generates a data entry form template, including: S301, in response to the user's component selection operation, select the corresponding form component in the preset component area; S302, in response to the user's component layout operation, adjust the layout of the form components in the preset component editing area; S303, Configure the properties of the form component in response to the user's property configuration operation.

[0036] In embodiments of the present invention, such as Figure 4As shown, the form customization module can be divided into the following layers: User Interface Layer: Provides the interactive interface for the form designer and runtime, responsible for receiving user operation instructions; Business Logic Layer: Handles the logical rules of form configuration, data validation, and interaction with other systems; Data Access Layer: Responsible for interaction with the database, storing and retrieving form configuration data; Data Storage Layer: Stores form templates, field definitions, and other information. During form creation, a component area, a form editing area, and a component attribute configuration area are provided. The component area provides built-in layouts, basic input methods, and special controls such as images and signatures; the form editing area allows users to add, delete, or adjust the order of fields by dragging and dropping; components can be used and copied multiple times to complete the design of form fields and styles; the attribute configuration area allows users to customize the colors, fonts, backgrounds, and other styles of fields, and supports advanced functions such as conditional display, calculation formulas, and data validation.

[0037] Specifically, a graphical form design interface is provided, logically divided into a component area, a component editing area, and a property configuration area. The component area displays all available components from a pre-defined form component library in the form of a list or icons. These components are the basic units that constitute the information communication data collection interface. When a user begins creating a form, they first perform a component selection operation. This operation can be done by clicking to select a component and dragging it to the editing area, or by double-clicking a component to automatically add it to the editing area. The system continuously listens for user interaction events in the component area. Once a valid component selection operation is detected, the selected form component is instantiated at the corresponding position in the component editing area.

[0038] Subsequently, the user performs component layout operations on the components added to the editing area. This operation allows the user to change the canvas coordinates of the components, the grid width they occupy, and the relative order between components. The system responds to the user's dragging, edge stretching, or alignment actions, adjusting the layout style of the components in the editing area in real time, and ensuring that the entire form template follows a preset grid system to guarantee a clean and standardized generated page. Through alternating component selection and layout operations, users can quickly assemble a structured interface that meets the data collection needs of the information and communication field, much like building with blocks.

[0039] After arranging the components, users proceed to configure their attributes. This typically involves selecting a component in the editing area and then setting its detailed properties in a separate attribute configuration area. Configurable attributes include, but are not limited to, component title labels, field identifiers, placeholder text, mandatory field toggles, default values, or default options. The system responds to each user's attribute configuration action by synchronously updating the data model of the form component to ensure its presentation and behavior fully conform to the analyst's definition.

[0040] In some possible embodiments of the present invention, such as Figure 5 As shown, a data dictionary is constructed based on the industry characteristics of the data to be analyzed, including: S501, Dictionary identifiers are determined based on the terminology, indicators, processes, operating procedures, and technical standards of the industry to which the data to be analyzed belongs; S502, determine the dictionary value corresponding to the dictionary identifier based on the field value requirements corresponding to the dictionary identifier, and construct a data dictionary based on the dictionary identifier and dictionary value.

[0041] In this embodiment of the invention, since different departments or personnel use different terms to describe the same concept when filling out forms, which leads to a decline in data quality, the system supports the establishment of a dataset dictionary, which can serve as the source of value configuration for components in form customization. This reduces the inaccuracy of manually entered data from different units, effectively reduces human error, improves data quality, reduces development costs, and promotes data sharing. By entering dictionary identifiers and dictionary values, a unified and complete data dictionary is formed.

[0042] An information and communication data dictionary is a standardized collection of all terms, indicators, and processes involved in information and communication work. It includes not only explanations of basic concepts but also operational procedures and technical standards, ensuring coverage of all information and communication-related fields, forming a complete knowledge system with accurate terminology definitions, clear operational procedures, and unified standards.

[0043] By constructing a data dictionary of organizations, communication methods, and equipment types used in the information and communication field, a foundation for resource data collection is formed; by integrating resource data, a data dictionary of equipment types and other data is further established, thus building a foundation for information and communication data collection.

[0044] In some possible embodiments of the present invention, such as Figure 6 As shown, establish cascading rules for each form component in the data entry form template, and configure validation rules for the corresponding fields of each form component in the data entry form template, including: S601, Construct cascading rules for each form component based on the cascading relationship between the dictionary identifiers of the data dictionaries associated with each form component in the data entry form template; S602 defines the validation rules for the fields corresponding to each form component based on the attribute definitions of each form component in the data entry form template.

[0045] In this embodiment of the invention, in the aforementioned steps, each form component is associated with a specific data dictionary through configuration, and each data dictionary has a globally unique dictionary identifier. In the design of the data dictionary system, clear cascading dependencies can be predefined between different dictionary identifiers. This relationship is essentially a knowledge representation of the hierarchical structure of entities within the information and communication domain. For example, the identifiers "Equipment Manufacturer Dictionary" and "Equipment Model Dictionary" are defined as having a parent-child hierarchical relationship because a specific model belongs only to a specific manufacturer; similarly, there is also a constraint between the "Province Dictionary" and the "City Dictionary" where the higher-level dictionary identifier imposes a constraint on the lower-level dictionary identifier. After the user completes the component layout of the form template and associates it with the dictionary, all form components in the template that have been bound to dictionary identifiers will be automatically traversed to identify dictionary identifier pairs with hierarchical relationships such as parent-child or grandparent-grandchild relationships. Once such a predefined cascading relationship is found between the dictionary identifiers bound to two components, a cascading rule from the parent component to the child component is automatically constructed. The essence of this rule is a set of reactive directives. It stipulates that when the selected value of the parent component changes, the child component needs to dynamically send a request to the data dictionary service based on the data filtering logic between the parent and child dictionaries, and only retrieve and display the dictionary entries that match the current value of the parent component as optional.

[0046] Furthermore, while providing value range constraints for form components, the data dictionary also assigns complete attribute definitions to each field. These attributes include, but are not limited to: the field's data type, maximum length, minimum and maximum allowed numerical values, whether null values ​​are allowed, whether global uniqueness is required, and regular expression templates for standardizing string patterns. During the generation of data entry forms, these attribute definitions for the corresponding fields of each form component are read, automatically converted into specific executable validation rules, and attached to the corresponding component instances. For example, for the "downlink peak traffic" field, its attribute definition in the data dictionary is "data type: integer, minimum value: 0, maximum value: 100000". Based on this, a numerical range validation rule is generated, stipulating that the input value must be an integer between 0 and 100000, and any out-of-bounds or non-integer input will be blocked upon submission. These validation rules, mapped from field attributes, work in conjunction with the aforementioned cascading rules to form a robust source data quality defense line. This ensures that various illegal, excessive, and conflicting data are accurately identified and blocked the moment they are entered, thereby achieving a very high degree of data accuracy in the collection of massive amounts of information and communication data.

[0047] In some possible embodiments of the present invention, receiving data entered by the user based on a data entry form and filling the data into the corresponding fields of the data entry form includes: When the form field type is configured as a fixed value, the corresponding field value is entered directly; When a form field is configured for dynamic association, the field value is configured as either a data dictionary or dynamic data. If configured as a data dictionary, it is associated with an existing data dictionary; if configured as dynamic data, it interacts with a third-party system for data exchange. When a form field is configured for formula calculation, the calculation formula is edited based on the field in the form to calculate the value of the form field.

[0048] In this embodiment of the invention, when the form field type is configured as a fixed value, the corresponding field value is directly entered; when the form field is configured as dynamically associated, the field value can be configured as a data dictionary or dynamic data. If configured as a data dictionary, it can be associated with an established data dictionary; if configured as dynamic data, it can interact with a third-party system through an HTTP request; when the form field is configured as a formula calculation, the calculation formula can be edited based on the field in the form, and the calculation result is the value of the field.

[0049] Custom forms can consist of multiple component areas, each with multiple display configurations, depending on data entry and approval processes and other business needs. When a single form object has no specific display configuration requirements, only the custom form components need to be configured. However, if the business process requires different content from the form components, the display configuration of the form's component areas needs to be dynamically configured, and the display configuration for the business process takes precedence over the general display configuration.

[0050] In practical use, the data entered needs to be validated to reduce human error and ensure the accuracy of subsequent analysis. The component can select simple validation rules such as required fields and value ranges to meet the convenient operation of non-developers. Complex rule validation can also be implemented through coding. After the form is customized, it can be published.

[0051] In some possible embodiments of the present invention, data is validated based on cascading rules and verification rules. After validation, the data in the data entry form is analyzed based on analysis requirements, including: Verify whether the values ​​of the corresponding fields of each form component in the data entry form meet the cascading rules and validation rules. If they do, analyze the data in the data entry form based on the analysis requirements. If they do not meet the requirements, output a validation prompt message.

[0052] In some possible embodiments of the present invention, after a user completes data entry and triggers the submission operation, the data is not immediately sent to the analysis engine. Instead, a comprehensive verification process is initiated first. This verification process performs compliance checks on the field values ​​corresponding to each form component in the data entry form in a preset priority order.

[0053] The first step is cascading rule validation. The system iterates through all parent-child component pairs constrained by cascading rules in the form, checking whether the current value of the child component and the selected value of the parent component form a valid hierarchical correspondence in the data dictionary. After the cascading rule validation passes, the system immediately executes the atomic checks defined by the validation rules. These checks cover multiple dimensions. Non-empty validation scans all fields marked as required, and immediately generates an error record if an empty value is found. Throughout the validation process, if a violation is found at any stage, the subsequent validation steps for that data will be immediately interrupted, and all accumulated validation results will be summarized into structured validation prompts and output to the user interface in real time. These prompts will be displayed with highlighted borders, inline error text, or pop-up messages, precisely indicating which field and which type of rule was violated, and providing correct input suggestions.

[0054] Only when all field values ​​in the form meet the stringent requirements of the cascading and validation rules will the data be marked as valid and officially persisted to the analysis-ready dataset associated with the form. Subsequently, in response to user-triggered or pre-set analysis requests, the target fields are retrieved from this thoroughly cleaned, high-quality data, and analysis logic such as aggregation, grouping, sorting, or filtering is executed to ultimately produce accurate and reliable data analysis results.

[0055] In some possible embodiments of the present invention, such as Figure 7 As shown, the data in the data entry form is analyzed based on the analysis requirements, and the data analysis results are as follows: S701, Determine the time dimension, spatial dimension, and type dimension of data analysis based on analysis requirements; S702 performs multi-dimensional analysis on the data in the data entry form based on time, space, and type dimensions, and visualizes the analysis results through graphical means.

[0056] In this embodiment of the invention, data visualization statistical analysis presents statistical results of data in a graphical way, helping users intuitively understand data characteristics and inherent patterns. Analysis results are displayed intuitively through charts, dashboards, and other formats, and real-time alarms and dynamic data updates are supported, improving user experience and decision-making efficiency. This module supports customized statistical analysis functions, allowing the introduction of multiple different analysis dimensions such as time (year, month, week, day, etc.), type (device, network system, etc.), and spatial dimensions as needed. This allows for in-depth exploration of the patterns and trends behind the data. Analysis results are presented in different report formats, such as bar charts, pie charts, line charts, and tables, and report export is supported. This provides a more intuitive reflection of data change trends, facilitates a comprehensive overview of resources, and can provide decision support based on statistical analysis results, enabling adjustments to communication support resources.

[0057] This invention improves the efficiency of data collection and analysis by establishing a data dictionary, customizing forms, and configuring statistical analysis dimensions, providing flexible and accurate analysis results. Based on information communication needs, a data dictionary is established to form the foundation for data collection and improve data quality. It also meets user needs, supports visually configurable forms, supports multi-dimensional statistical analysis of data, and generates reports.

[0058] To better implement the data customization analysis method in the embodiments of the present invention, based on the data customization analysis method, correspondingly, such as... Figure 8 As shown, this embodiment of the invention also provides a data customization analysis device, the data customization analysis device 800 including: The form building module 801 is used to respond to the user's form creation operation, select the corresponding form component from the preset form component library, lay out the form component, and generate a data entry form template. The form association module 802 is used to build a data dictionary based on the industry characteristics of the data to be analyzed, associate the form components in the data entry form template with the data dictionary, wherein the data dictionary is used to limit the values ​​in the form components, establish the cascading rules of each form component in the data entry form template, configure the validation rules of the corresponding fields of each form component in the data entry form template, and generate the data entry form. The data entry and analysis module 803 is used to receive data entered by users based on the data entry form, fill the data into the corresponding fields of the data entry form, validate the data based on cascading rules and validation rules, and analyze the data in the data entry form based on analysis requirements after validation to obtain data analysis results.

[0059] The data customization analysis device 900 provided in the above embodiments can realize the technical solutions described in the above data customization analysis method embodiments. The specific implementation principles of each module or unit can be found in the corresponding content in the above data customization analysis method embodiments, and will not be repeated here.

[0060] like Figure 9 As shown, the present invention also provides a data analysis terminal 900. The terminal 900 includes a processor 901, a memory 902, and a front-end interactive interface 903. Figure 9 Only some of the components of terminal 900 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0061] In some embodiments, processor 901 may be a central processing unit (CPU), a microprocessor, or other data processing chip, used to run program code stored in memory 902 or process data, such as the data customization analysis method in this invention.

[0062] In some embodiments, processor 901 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processor 901 may be local or remote. In some embodiments, processor 901 may be implemented on a cloud platform. In some embodiments, the cloud platform may include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, internal cloud, multi-cloud, etc., or any combination thereof.

[0063] In some embodiments, memory 902 may be an internal storage unit of terminal 900, such as a hard disk or memory of terminal 900. In other embodiments, memory 902 may also be an external storage device of terminal 900, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on terminal 900.

[0064] Furthermore, the memory 902 may include both internal storage units of the terminal 900 and external storage devices. The memory 902 is used to store application software and various types of data installed on the terminal 900.

[0065] The front-end interactive interface 903 can be an electronic display screen, a touch screen display, etc.

[0066] In some embodiments, when the processor 901 executes a data customization analysis program in the memory 902, the following steps may be performed: In response to the user's form creation operation, the system selects the corresponding form component from the preset form component library, lays out the form component, and generates a data entry form template. A data dictionary is constructed based on the industry characteristics of the data to be analyzed. The form components in the data entry form template are associated with the data dictionary. The data dictionary is used to limit the values ​​in the form components, establish the cascading rules of each form component in the data entry form template, configure the validation rules of the corresponding fields of each form component in the data entry form template, and generate the data entry form. It receives data entered by users based on data entry forms, fills the data into the corresponding fields of the data entry forms, validates the data based on cascading rules and validation rules, and analyzes the data in the data entry forms based on analysis requirements after validation to obtain data analysis results.

[0067] It should be understood that when the processor 901 executes the data customization analysis program in the memory 902, in addition to the functions mentioned above, it can also perform other functions, as detailed in the description of the corresponding method embodiments above.

[0068] Furthermore, this embodiment of the invention does not specifically limit the type of terminal 900 mentioned. Terminal 900 can be a portable terminal such as a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, or laptop computer. Exemplary embodiments of portable terminals include, but are not limited to, portable terminals running iOS, Android, Microsoft, or other operating systems. The aforementioned portable terminal can also be other portable terminals, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the invention, terminal 900 may not be a portable terminal, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0069] Accordingly, this application also provides a computer-readable storage medium for storing computer-readable programs or instructions. When the programs or instructions are executed by a processor, they can implement the steps or functions of the data customization analysis methods provided in the above-described method embodiments.

[0070] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0071] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A data customization analysis method, characterized in that, include: In response to the user's form creation operation, the corresponding form component is selected from the preset form component library, and the form component is laid out to generate a data entry form template; A data dictionary is constructed based on the industry characteristics of the data to be analyzed. The form components in the data entry form template are associated with the data dictionary. The data dictionary is used to limit the values ​​in the form components and to establish cascading rules for each form component in the data entry form template. The validation rules for the corresponding fields of each form component in the data entry form template are configured to generate the data entry form. The system receives data entered by the user based on the data entry form and fills the data into the corresponding fields of the data entry form. It then verifies the data based on the cascading rules and the validation rules. After the verification is completed, it analyzes the data in the data entry form based on the analysis requirements to obtain the data analysis results.

2. The data customization analysis method according to claim 1, characterized in that, The form creation operation includes component selection, component layout, and attribute configuration. Responding to the user's form creation operation, the corresponding form component is selected from a preset form component library, and the form component is laid out to generate a data entry form template, including: In response to the user's component selection action, select the corresponding form component from the preset component area; In response to the user's component layout operation, the layout of the form components is adjusted in the preset component editing area; Configure the properties of the form component in response to the user's property configuration operation.

3. The data customization analysis method according to claim 1, characterized in that, The data dictionary constructed based on the industry characteristics of the data to be analyzed includes: Dictionary identifiers are determined based on the terminology, indicators, processes, operating procedures, and technical standards of the industry to which the data to be analyzed belongs; Based on the field value requirements corresponding to the dictionary identifier, determine the dictionary value corresponding to the dictionary identifier, and construct a data dictionary based on the dictionary identifier and the dictionary value.

4. The data customization analysis method according to claim 3, characterized in that, The step of establishing cascading rules for each form component in the data entry form template and configuring validation rules for corresponding fields of each form component in the data entry form template includes: The cascading rules for each form component are constructed based on the cascading relationship between the dictionary identifiers of the data dictionaries associated with each form component in the data entry form template. The validation rules for each field in each form component are defined based on the attribute definitions of the fields in the data entry form template.

5. The data customization analysis method according to claim 4, characterized in that, The step of receiving data entered by the user based on the data entry form and filling the data into the corresponding fields of the data entry form includes: When the form field type is configured as a fixed value, the corresponding field value is entered directly; When a form field is configured for dynamic association, the field value is configured as either a data dictionary or dynamic data. If configured as a data dictionary, it is associated with an existing data dictionary; if configured as dynamic data, it interacts with a third-party system for data exchange. When a form field is configured for formula calculation, the value of the form field is calculated based on the formula edited within the form field.

6. The data customization analysis method according to claim 1, characterized in that, The data is validated based on the cascading rules and the validation rules. After validation, the data in the data entry form is analyzed based on analysis requirements, including: The system verifies whether the values ​​of the corresponding fields of each form component in the data entry form meet the cascading rules and the verification rules. If they do, the system analyzes the data in the data entry form based on the analysis requirements. If they do not meet the requirements, the system outputs a verification prompt message.

7. The data customization analysis method according to claim 1, characterized in that, The analysis of the data in the data entry form based on the analysis requirements yields the following data analysis results: Determine the time dimension, spatial dimension, and type dimension of data analysis based on the analysis requirements; The data in the data entry form is analyzed from multiple dimensions, including time, space, and type, and the analysis results are visualized using graphical methods.

8. A data customization analysis device, characterized in that, include: The form building module is used to respond to the user's form creation operation, select the corresponding form component from the preset form component library, lay out the form component, and generate a data entry form template. The form association module is used to construct a data dictionary based on the industry characteristics of the data to be analyzed, associate the form components in the data entry form template with the data dictionary, wherein the data dictionary is used to limit the values ​​in the form components, establish cascading rules for each form component in the data entry form template, configure the validation rules for the corresponding fields of each form component in the data entry form template, and generate the data entry form. The data entry and analysis module is used to receive data entered by the user based on the data entry form, fill the data into the corresponding fields of the data entry form, verify the data based on the cascading rules and the verification rules, and analyze the data in the data entry form based on the analysis requirements after the verification is completed to obtain the data analysis results.

9. A data analysis terminal, characterized in that, This includes the front-end user interface, memory, and processor, among which, The front-end interactive interface is used to receive user operations and display data entry forms and data analysis results; The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the data customization analysis method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the data customization analysis method according to any one of claims 1 to 7.

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