Intelligent configuration analysis system and method based on big data model

Abstract

The invention provides an intelligent configuration analysis system and method based on a big data model, and the system comprises a configuration module which is used for capturing related data from a plurality of data sources in real time, and inputting the related data and data dimensions corresponding to the related data into a business template; the analysis module is used for performing multi-dimensional business analysis on related data in the business template based on a big data model, and outputting business analysis description and a visual analysis graph; and the visualization module is used for carrying out visualization display on the business analysis description and the visualization analysis graph. Not only are convenience and effectiveness of analysis improved, but also accuracy of business analysis management is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to an intelligent configurable analysis system and method based on a big data model. Background Art

[0002] At present, with the rapid development of information technology and the explosive growth of data volume, enterprises and organizations are facing increasingly complex data processing and analysis needs. In all fields, in-depth understanding and effective use of data have become the key to improving competitiveness and decision-making accuracy;

[0003] However, traditional data analysis methods often have many limitations. On the one hand, the diversity and complexity of data make manual analysis extremely difficult and time-consuming, and it is difficult to deal with large-scale, multi-dimensional data. On the other hand, different business scenarios and needs require customized analysis processes and models, but rebuilding and adjusting these analysis models in the traditional way often requires a lot of professional knowledge and development work, which is costly and inefficient.

[0004] Therefore, in order to overcome the above technical problems, the present invention provides an intelligent configurable analysis system and method based on a big data model. Summary of the invention

[0005] The present invention provides an intelligent configurable analysis system and method based on a big data model, which can accurately determine the specific business objectives and requirements of the system and the processing by obtaining business configuration requirements, and can effectively capture relevant data by determining business templates and data sources, thereby improving the comprehensiveness of capturing relevant data. By inputting relevant data and data dimensions corresponding to the relevant data into business templates, effective integration of relevant data can be effectively achieved, thereby effectively realizing multi-dimensional analysis of business data based on big data models and business templates, thereby effectively realizing the acquisition of business analysis descriptions and visual analysis graphic structures, and can effectively help users understand and grasp key information more quickly and intuitively. By visually displaying business analysis descriptions and visual analysis graphics, it is convenient for users to view analysis results easily and conveniently, thereby improving user experience. This method not only improves the convenience and effectiveness of analysis, but also has the benefit of ensuring the accuracy of business analysis management.

[0006] An intelligent configuration analysis system based on a big data model, comprising:

[0007] Configuration requirement acquisition module, used to obtain business configuration requirements and read business templates and data sources in the business configuration requirements;

[0008] A configuration module is used to capture relevant data from multiple data sources in real time, and input the relevant data and the data dimensions corresponding to the relevant data into the business template;

[0009] The analysis module is used to perform multi-dimensional business analysis on the relevant data in the business template based on the big data model, and output the business analysis description and visual analysis graphics;

[0010] The visualization module is used to visualize the business analysis description and visualization analysis graphics.

[0011] Preferably, an intelligent configuration analysis system based on a big data model, a configuration requirement acquisition module, includes:

[0012] A demand access unit, used to access the management terminal and obtain the service configuration requirements of the management terminal based on the access result;

[0013] Requirements parsing unit, used to:

[0014] Perform text analysis on business configuration requirements, extract key data segments from the business configuration requirements, and determine business links based on the semantic features of the key data segments;

[0015] Determine business objectives and key elements based on the attribute information of business links, and determine multi-link functional requirements based on business objectives and key elements;

[0016] Based on the multi-link functional requirements, target business modules are matched from the business module database, and the target business modules are logically combined to obtain business templates;

[0017] At the same time, the required data items are determined based on the multi-link functional requirements, and the corresponding data sources are determined based on the required data items.

[0018] Preferably, an intelligent configuration analysis system based on a big data model, a demand analysis unit, comprises:

[0019] The result acquisition subunit is used to obtain the business templates and data sources corresponding to different business configuration requirements, and generate a requirement summary based on the multi-link functional requirements of the business configuration requirements;

[0020] The recording subunit is used to construct an information recording table and record the requirement summary, business template and data source in the information recording table based on the mapping relationship;

[0021] The template library construction subunit is used to generate a multi-dimensional business configuration requirement template library based on the recording results, configure an external access interface for the multi-dimensional business configuration requirement template library, and complete the construction of the template library based on the configuration results.

[0022] Preferably, an intelligent configuration analysis system based on a big data model, the configuration module includes:

[0023] A service type acquisition unit, used to acquire the service type of a target service;

[0024] A management target determination unit, used to read the management target corresponding to each business type;

[0025] Data capture unit for:

[0026] Determine the data source type based on the business type, and determine the data capture standard based on the management objectives;

[0027] Obtain the target data source according to the data source type, and at the same time, crawl data in the target data source according to the data crawling standard to obtain relevant data;

[0028] The input unit is used to retrieve a business template that is consistent with the business type of the target business, and at the same time, input relevant data and data dimensions corresponding to the relevant data into the business template.

[0029] Preferably, in an intelligent configurable analysis system based on a big data model, in a data capture unit, data is captured in a target data source according to a data capture standard to obtain relevant data, including:

[0030] A reading unit is used to read the target data source, determine the data coverage of the target data source, and at the same time, read the data capture standard and determine multiple data capture areas in the target data source according to the data capture standard;

[0031] A marking unit, used for marking a data capture area within a data coverage range;

[0032] Distributed layout unit for:

[0033] Generate data capture features based on data capture standards, and arrange data acquisition nodes in each data capture area according to the marking results. At the same time, construct data receiving nodes, and distribute multiple data acquisition nodes and data receiving nodes according to the preset communication protocol;

[0034] Among them, one data acquisition node is arranged in one data capture area;

[0035] The relevant data acquisition unit is used for:

[0036] Based on the distributed layout result and according to the data receiving node, the initial relevant data corresponding to the data collection node in each data capture area is received in real time;

[0037] The initial relevant data is cleaned and sorted to obtain relevant data.

[0038] Preferably, an intelligent configurable analysis system based on a big data model, the analysis module comprises:

[0039] A coordinate system construction unit, used to construct a time interval, and create multiple time nodes in the time interval according to a preset time interval, and construct a rectangular coordinate system using the multiple time nodes as the horizontal axis and each data dimension as the vertical axis;

[0040] A data range determination unit for:

[0041] Obtain historical related data, and divide the historical related data according to data dimensions to obtain sub-historical related data sets corresponding to each dimension;

[0042] Map the sub-history related data sets in the corresponding ordinate with the time nodes of the abscissa to obtain the target change curve of the sub-history related data sets with the time nodes in each data dimension;

[0043] Collect the curve inflection points in each target change curve, and mark the curve inflection points in each target change curve. At the same time, obtain the data attribute characteristics of each data dimension, and determine the first data range of each data dimension during normal operation and the second data range of each data dimension during abnormal operation based on the data attribute characteristics of each data dimension and the curve inflection points in the corresponding target change curve;

[0044] Data analysis unit for:

[0045] Read relevant data collected in real time, and divide the relevant data according to data dimensions to obtain multiple sub-relevant data corresponding to the data dimensions;

[0046] comparing the sub-related data with the first data range and the second data range of the corresponding data dimension;

[0047] If the sub-related data is within the first data range, the data change trend of the corresponding sub-related data is output according to the target change curve combined with the big data model;

[0048] If the sub-related data is within the second data range, an abnormal prediction is performed on the sub-related data according to the target change curve combined with the big data model, and the abnormal prediction data is output;

[0049] The business analysis description generating unit is used to generate a business analysis description according to abnormal prediction data or data change trend.

[0050] Preferably, an intelligent configurable analysis system based on a big data model, in which the analysis module outputs a visual analysis graphic structure, includes:

[0051] A visualization graphic model retrieval unit is used to read visualization requirements and retrieve a visualization graphic model from a preset model library according to the visualization requirements;

[0052] A display title determination unit, used to read the business analysis description and determine the display title according to the business analysis description;

[0053] The visualization graphic structure generation unit is used to perform a first filling in the visualization image model according to the display title, and perform a corresponding second filling in the visualization graphic model based on the first filling result according to the business analysis description, and at the same time, generate a visualization analysis graphic according to the second filling result.

[0054] Preferably, an intelligent configurable analysis system based on a big data model, a visualization module, comprises:

[0055] A display interface calling unit, used to call the display interface and determine the target size of the display interface;

[0056] Optimal visible size determination unit for:

[0057] Determining a first optimal visible size of the visual analysis graph in the display interface according to a target size of the display interface;

[0058] Determining a second optimal visible size of the business analysis description in the display interface according to the target size of the display interface;

[0059] Analysis layout unit, used to:

[0060] Obtaining a sum of the first optimal visible size and the second optimal visible size, and comparing the sum with a target size of the display interface;

[0061] When the sum of the sizes is less than or equal to the target size of the display interface, layout is performed in the display interface according to the first optimal visible size and the second optimal visible size to obtain a target display interface;

[0062] When the size is greater than the target size of the display interface, the display interface is copied, and the visual analysis graphics are laid out in the first display interface according to the first optimal visual size according to the copy result, and the business analysis description is laid out in the second display interface according to the second optimal visual size;

[0063] Generate a target display interface set based on the layout result;

[0064] The visualization display unit is used to visualize the business analysis description and the visualization analysis graph according to the target display interface or the target display interface set.

[0065] An intelligent configuration analysis method based on a big data model, comprising:

[0066] Step 1: Obtain business configuration requirements and read the business template and data source in the business configuration requirements;

[0067] Step 2: Capture relevant data from multiple data sources in real time, and input the relevant data and the data source dimensions corresponding to the relevant data into the business template;

[0068] Step 3: Perform multi-dimensional business analysis on the relevant data in the business template based on the big data model, and output the business analysis description and visual analysis graphics;

[0069] Step 4: Visualize the business analysis description and visualization analysis graphics.

[0070] Preferably, an intelligent configuration analysis method based on a big data model, step 1, obtaining business configuration requirements, and reading business templates and data sources in the business configuration requirements, including:

[0071] S101: Access a management terminal and obtain a service configuration requirement of the management terminal based on the access result;

[0072] S102: parsing the business configuration requirements, extracting key data segments in the business configuration requirements, and determining business links based on semantic features of the key data segments;

[0073] S103: Determine business objectives and key elements based on the attribute information of the business link, and determine multi-link functional requirements based on the business objectives and key elements;

[0074] S104: Match the target business module from the business module database based on the multi-link functional requirements, and logically combine the target business modules to obtain a business template; at the same time, determine the required data items based on the multi-link functional requirements, and determine the corresponding data source based on the required data items.

[0075] Compared with the prior art, the present invention has the following beneficial effects:

[0076] By obtaining the business configuration requirements, the specific business goals and requirements of the system and the processing can be accurately determined. By determining the business templates and data sources, the relevant data can be effectively captured, which improves the comprehensiveness of the relevant data capture. By inputting the relevant data and the data dimensions corresponding to the relevant data into the business template, the relevant data can be effectively integrated, thereby effectively realizing the multi-dimensional analysis of business data based on the big data model and the business template, thereby effectively realizing the acquisition of business analysis descriptions and visual analysis graphics, which can effectively help users understand and grasp key information more quickly and intuitively. By visually displaying the business analysis descriptions and visual analysis graphics, it is convenient for users to view the analysis results directly and easily, thereby improving the user experience. This method not only improves the convenience and effectiveness of the analysis, but also has the benefit of ensuring the accuracy of business analysis management.

[0077] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0078] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0080] Figure 1 This is a structural diagram of an intelligent configuration analysis system based on a big data model in an embodiment of the present invention;

[0081] Figure 2 This is a structure diagram of a visualization module in an intelligent configuration analysis system based on a big data model in an embodiment of the present invention;

[0082] Figure 3 The present invention is a flowchart of an intelligent configuration analysis method based on a big data model in an embodiment of the present invention. DETAILED DESCRIPTION

[0083] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0084] Embodiment 1:

[0085] This embodiment provides an intelligent configuration analysis system based on a big data model. Figure 1As shown, including:

[0086] Configuration requirement acquisition module, used to obtain business configuration requirements and read business templates and data sources in the business configuration requirements;

[0087] A configuration module is used to capture relevant data from multiple data sources in real time, and input the relevant data and the data dimensions corresponding to the relevant data into the business template;

[0088] The analysis module is used to perform multi-dimensional business analysis on the relevant data in the business template based on the big data model, and output the business analysis description and visual analysis graphics;

[0089] The visualization module is used to visualize the business analysis description and visualization analysis graphics.

[0090] In this embodiment, the service configuration requirement is obtained from the management terminal and is used to characterize the type of service management that needs to be performed and the management purpose that needs to be achieved.

[0091] In this embodiment, the business template may be a module corresponding to the business requirement configuration and capable of executing the corresponding business requirement analysis, and different business templates may correspond to different business configuration requirements.

[0092] In this embodiment, the data source may be a data source required for business management needs, for example, when performing financial management, the required data sources include financial expenditure data, financial income data, and material purchase status.

[0093] In this embodiment, the relevant data may be specific data content required for business configuration requirements captured from the corresponding data source.

[0094] In this embodiment, the data dimension may be specific data type information corresponding to the relevant data, thereby facilitating effective analysis of different types of business management.

[0095] In this embodiment, the business analysis description may be an analysis result obtained after performing a multi-dimensional business analysis on relevant data, that is, specific content that explains the analysis result through text content.

[0096] In this embodiment, the visual analysis graph may be in the form of a chart corresponding to the analysis result, so that the management personnel can effectively view the analysis result through the graphic structure.

[0097] The working principle and beneficial effects of the above technical solution are: by obtaining the business configuration requirements, the specific business objectives and requirements of the system and the processing can be accurately determined; by determining the business template and data source, the relevant data can be effectively captured, thereby improving the comprehensiveness of the relevant data capture; by inputting the relevant data and the data dimensions corresponding to the relevant data into the business template, the relevant data can be effectively integrated, thereby effectively realizing the multi-dimensional analysis of business data based on the big data model and the business template, thereby effectively realizing the acquisition of business analysis descriptions and visual analysis graphic structures, which can effectively help users understand and grasp key information more quickly and intuitively; by visually displaying the business analysis description and the visual analysis graphics, it is convenient for users to view the analysis results easily and easily, thereby improving the user experience; this method not only improves the convenience and effectiveness of the analysis, but also has the benefit of ensuring the accuracy of business analysis management.

[0098] Embodiment 2:

[0099] Based on Example 1, this embodiment provides an intelligent configuration analysis system based on a big data model, and a configuration requirement acquisition module, including:

[0100] A demand access unit, used to access the management terminal and obtain the service configuration requirements of the management terminal based on the access result;

[0101] Requirements parsing unit, used to:

[0102] Perform text analysis on business configuration requirements, extract key data segments from the business configuration requirements, and determine business links based on the semantic features of the key data segments;

[0103] Determine business objectives and key elements based on the attribute information of business links, and determine multi-link functional requirements based on business objectives and key elements;

[0104] Based on the multi-link functional requirements, target business modules are matched from the business module database, and the target business modules are logically combined to obtain business templates;

[0105] At the same time, the required data items are determined based on the multi-link functional requirements, and the corresponding data sources are determined based on the required data items.

[0106] In this embodiment, the key data segment may be data information in the business configuration requirement that can characterize the subject of the business configuration requirement, and is a part of the text in the business configuration requirement.

[0107] In this embodiment, the semantic feature may be the specific subject content corresponding to the key data segment.

[0108] In this embodiment, the attribute information may be the type of the business link and the function corresponding to the business link.

[0109] In this embodiment, the business goal may be a purpose that a business link needs to achieve.

[0110] In this embodiment, the key elements may be parameter indicators that play an important role when the business link is running.

[0111] In this embodiment, the target service module may be a service template applicable to the current service configuration requirement, which is one of the service templates in the service template database.

[0112] In this embodiment, the required data items may be data types that can be processed by each business link during operation.

[0113] The working principle and beneficial effects of the above technical solution are: by accessing the management terminal, the business configuration requirements can be effectively acquired, and by parsing the business configuration requirements, the key data fragments in the business configuration requirements can be effectively extracted, so that the business requirements can be determined through the semantic features of the key data fragments. Through the attribute information of the business link, the business goals and key elements can be effectively determined, so as to realize the multi-link common requirements based on business goals and key elements. Through the multi-link functional requirements, the target business module can be effectively matched in the business module database, so as to realize the determination of the business template through logical combination. By determining the required data items according to the multi-link functional requirements, the data source can be determined, which provides important guarantees for the efficient operation and accurate analysis of the entire intelligent configurable analysis system.

[0114] Embodiment 3:

[0115] Based on Example 2, this embodiment provides an intelligent configuration analysis system based on a big data model, a demand analysis unit, including:

[0116] The result acquisition subunit is used to obtain the business templates and data sources corresponding to different business configuration requirements, and generate a requirement summary based on the multi-link functional requirements of the business configuration requirements;

[0117] The recording subunit is used to construct an information recording table and record the requirement summary, business template and data source in the information recording table based on the mapping relationship;

[0118] The template library construction subunit is used to generate a multi-dimensional business configuration requirement template library based on the recording results, configure an external access interface for the multi-dimensional business configuration requirement template library, and complete the construction of the template library based on the configuration results.

[0119] In this embodiment, the requirement summary is determined based on the multi-link functional requirements and is used to briefly describe the multi-link functional requirements.

[0120] In this embodiment, the mapping relationship may be a one-to-one correspondence between the demand summary, the business template, and the data source, thereby facilitating corresponding recording in the information recording table.

[0121] The beneficial effect of the above technical solution is: by determining the business templates, data sources and requirement summaries corresponding to different business configuration requirements, and recording the mapping relationship between them, it provides data support for building a multi-dimensional business configuration requirement template library, ensuring the effectiveness and comprehensiveness of the construction of the template library, and at the same time, it is conducive to the effective reference of the template library.

[0122] Embodiment 4:

[0123] Based on Example 1, this embodiment provides an intelligent configuration analysis system based on a big data model, and the configuration module includes:

[0124] A service type acquisition unit, used to acquire the service type of a target service;

[0125] A management target determination unit, used to read the management target corresponding to each business type;

[0126] Data capture unit for:

[0127] Determine the data source type based on the business type, and determine the data capture standard based on the management objectives;

[0128] Obtain the target data source according to the data source type, and at the same time, crawl data in the target data source according to the data crawling standard to obtain relevant data;

[0129] The input unit is used to retrieve a business template that is consistent with the business type of the target business, and at the same time, input relevant data and data dimensions corresponding to the relevant data into the business template.

[0130] In this embodiment, the data capture standard is determined according to the management goal and is a rule for collecting data.

[0131] In this embodiment, the target data source may be a source capable of data collection determined according to the data source type.

[0132] In this embodiment, the relevant data may be the result obtained after data is captured in the target data source according to the data capture standard, that is, the data corresponding to the management target.

[0133] The working principle and beneficial effects of the above technical solution are: by obtaining the business type of the target business and reading the management target corresponding to each business type, the data source type and data capture standard can be effectively determined, thereby achieving accurate and effective capture of relevant data in the target data source through the data capture standard, thereby improving the effectiveness and accuracy of capturing relevant data.

[0134] Embodiment 5:

[0135] Based on Example 4, this embodiment provides an intelligent configurable analysis system based on a big data model. In the data capture unit, data is captured in a target data source according to a data capture standard to obtain relevant data, including:

[0136] A reading unit is used to read the target data source, determine the data coverage of the target data source, and at the same time, read the data capture standard and determine multiple data capture areas in the target data source according to the data capture standard;

[0137] A marking unit, used for marking a data capture area within a data coverage range;

[0138] Distributed layout unit for:

[0139] Generate data capture features based on data capture standards, and arrange data acquisition nodes in each data capture area according to the marking results. At the same time, construct data receiving nodes, and distribute multiple data acquisition nodes and data receiving nodes according to the preset communication protocol;

[0140] Among them, one data acquisition node is arranged in one data capture area;

[0141] The relevant data acquisition unit is used for:

[0142] Based on the distributed layout result and according to the data receiving node, the initial relevant data corresponding to the data collection node in each data capture area is received in real time;

[0143] The initial relevant data is cleaned and sorted to obtain relevant data.

[0144] In this embodiment, data cleaning and organization of the initial relevant data include: deduplication, missing value processing, outlier detection, etc., to improve data quality.

[0145] In this embodiment, the data coverage may be data type information contained in the target data source.

[0146] In this embodiment, the multiple data capture areas may be data segments that can be captured and are determined in the target data source according to the data capture standard.

[0147] In this embodiment, the data capture feature may be determined according to the data capture standard, and is used to characterize information such as the capture amount during data capture.

[0148] In this embodiment, the data acquisition node may be a specific location corresponding to the data to be captured in each data capture area.

[0149] In this embodiment, the preset communication protocol is set in advance and is used to connect the data acquisition node and the data receiving node.

[0150] In this embodiment, the initial relevant data may be specific data information corresponding to the data acquisition node.

[0151] The beneficial effects of the above technical solution are: by determining the data capture area, the accuracy of data capture is effectively guaranteed, and through a distributed layout, the data collection and organization are effectively realized, and then by cleaning the initial relevant data, the quality of the relevant data is improved.

[0152] Embodiment 6:

[0153] Based on Example 1, this embodiment provides an intelligent configurable analysis system based on a big data model, and the analysis module includes:

[0154] A coordinate system construction unit, used to construct a time interval, and create multiple time nodes in the time interval according to a preset time interval, and construct a rectangular coordinate system using the multiple time nodes as the horizontal axis and each data dimension as the vertical axis;

[0155] A data range determination unit for:

[0156] Obtain historical related data, and divide the historical related data according to data dimensions to obtain sub-historical related data sets corresponding to each dimension;

[0157] Map the sub-history related data sets in the corresponding ordinate with the time nodes of the abscissa to obtain the target change curve of the sub-history related data sets with the time nodes in each data dimension;

[0158] Collect the curve inflection points in each target change curve, and mark the curve inflection points in each target change curve. At the same time, obtain the data attribute characteristics of each data dimension, and determine the first data range of each data dimension in normal operation and the second data range of each data dimension in abnormal operation in the corresponding target change curve according to the data attribute characteristics of each data dimension and the curve inflection points;

[0159] Data analysis unit for:

[0160] Read relevant data collected in real time, and divide the relevant data according to data dimensions to obtain multiple sub-relevant data corresponding to the data dimensions;

[0161] comparing the sub-related data with the first data range and the second data range of the corresponding data dimension;

[0162] If the sub-related data is within the first data range, the data change trend of the corresponding sub-related data is output according to the target change curve combined with the big data model;

[0163] If the sub-related data is within the second data range, an abnormal prediction is performed on the sub-related data according to the target change curve combined with the big data model, and the abnormal prediction data is output;

[0164] The business analysis description generating unit is used to generate a business analysis description according to abnormal prediction data or data change trend.

[0165] In this embodiment, the preset time interval is set in advance and is used to create multiple time nodes in the time interval, wherein the time node is a unit time point for visual display in a coordinate system.

[0166] In this embodiment, the sub-history related data set may be a specific data set corresponding to each dimension obtained after splitting the history related data according to the data dimension.

[0167] In this embodiment, data mapping of the sub-history related data set in the corresponding vertical axis with the time node of the horizontal axis can be performed by displaying the sub-history related data set in a rectangular coordinate system in a bit-by-bit manner based on the correspondence between the timestamps corresponding to each data in the sub-history related data set and the time node of the horizontal axis.

[0168] In this embodiment, the target change curve may be a graph showing changes in the sub-history related data set at different time nodes.

[0169] In this embodiment, the curve inflection point may be a position point where a value in the target change curve undergoes a turning point change.

[0170] In this embodiment, the data attribute feature may be a feature that characterizes the relative relationship between the data dimension and the data value under the data dimension. For example, a larger value indicates a better effect of the data dimension.

[0171] In this embodiment, the sub-related data may be a data set that corresponds one-to-one to the data dimensions in the related data.

[0172] In this embodiment, the abnormal prediction data may be a result obtained by performing abnormal prediction on the sub-related data according to the target change curve and the big data model when the sub-related data is within the second data range.

[0173] The working principle and beneficial effects of the above technical solution are: by determining the horizontal and vertical coordinates of the rectangular coordinate system, it is convenient to map and display the historical related data in the constructed rectangular coordinate system, and analyze the historical related data according to the mapping display results, so as to accurately and effectively determine the first data range of each data dimension during normal operation and the second data range during abnormal operation. Secondly, the relevant data collected in real time is compared with the first data range and the second data range respectively, so as to accurately and effectively determine the data change trend when the data is normal and the abnormal prediction data when the data is abnormal, realize the effective acquisition of business analysis description, and effectively realize the comprehensiveness and effectiveness of multi-dimensional business analysis of relevant data in business templates based on big data models.

[0174] Embodiment 7:

[0175] Based on Example 1, this embodiment provides an intelligent configurable analysis system based on a big data model, in which the analysis module outputs a visual analysis graph, including:

[0176] A visualization graphic model retrieval unit is used to read visualization requirements and retrieve a visualization graphic model from a preset model library according to the visualization requirements;

[0177] A display title determination unit, used to read the business analysis description and determine the display title according to the business analysis description;

[0178] The visualization graphic structure generation unit is used to perform a first filling in the visualization image model according to the display title, and perform a corresponding second filling in the visualization graphic model based on the first filling result according to the business analysis description, and at the same time, generate a visualization analysis graphic according to the second filling result.

[0179] In this embodiment, the preset model library is set in advance and is used to store a variety of different visualization graphic templates.

[0180] In this embodiment, the display title may be determined according to the business analysis description and is used to summarize the data information of the business analysis model.

[0181] In this embodiment, the first filling may be to fill in the display title in the visual image model.

[0182] In this embodiment, the second filling may be to fill in the business analysis description in a visual graphic model.

[0183] The beneficial effects of the above technical solution are: by calling the visualization graphic model according to the visualization requirements and parsing the business analysis description, the display title can be accurately and effectively determined; secondly, by filling in the display logo and business analysis description in the visualization graphic model respectively, the visualization analysis graphic can be effectively determined, ensuring that users can effectively review the analysis results.

[0184] Embodiment 8:

[0185] Based on Example 1, this example provides an intelligent configuration analysis system based on a big data model, such as Figure 2 As shown, the visualization module includes:

[0186] A display interface calling unit, used to call the display interface and determine the target size of the display interface;

[0187] Optimal visible size determination unit for:

[0188] Determining a first optimal visible size of the visual analysis graph in the display interface according to a target size of the display interface;

[0189] Determining a second optimal visible size of the business analysis description in the display interface according to the target size of the display interface;

[0190] Analysis layout unit, used to:

[0191] Obtaining a sum of the first optimal visible size and the second optimal visible size, and comparing the sum with a target size of the display interface;

[0192] When the sum of the sizes is less than or equal to the target size of the display interface, layout is performed in the display interface according to the first optimal visible size and the second optimal visible size to obtain a target display interface;

[0193] When the size is greater than the target size of the display interface, the display interface is copied, and the visual analysis graphics are laid out in the first display interface according to the first optimal visual size according to the copy result, and the business analysis description is laid out in the second display interface according to the second optimal visual size;

[0194] Generate a target display interface set based on the layout result;

[0195] The visualization display unit is used to visualize the business analysis description and the visualization analysis graph according to the target display interface or the target display interface set.

[0196] In this embodiment, the target size may be used to characterize the size of the display interface.

[0197] In this embodiment, the first optimal visible size may be optimal size information of an area in the display interface for displaying the visual analysis graph.

[0198] In this embodiment, the second optimal visible size may be optimal size information of an area in the display interface for displaying the business analysis description.

[0199] In this embodiment, the target display interface can be the result of laying out the visualization analysis graphics and the business analysis description at a first optimal visual size and a second optimal visual size that is less than or equal to a target size of the display interface, wherein the visualization analysis graphics and the business analysis description need to be displayed synchronously in the display interface.

[0200] In this embodiment, the target display interface set may be a set of all display interfaces obtained by copying the display interface when the size does not meet the display requirement.

[0201] The working principle and beneficial effects of the above technical solution are: by calling up the display interface and determining the target size of the display interface, the sum of the first optimal visual size of the visual analysis graphic based on the target size of the display interface and the second optimal visual size of the business analysis description based on the target size of the display interface can be effectively determined; by comparing the sum of the sizes with the target size, the effective display of the visual analysis graphic and the business analysis description based on the display interface can be effectively achieved, thereby improving the quality and effectiveness of the display on the display interface and facilitating users to conveniently view the analysis results.

[0202] Embodiment 9:

[0203] This embodiment provides an intelligent configuration analysis method based on a big data model. Figure 3 As shown, including:

[0204] Step 1: Obtain business configuration requirements and read the business template and data source in the business configuration requirements;

[0205] Step 2: Capture relevant data from multiple data sources in real time, and input the relevant data and the data source dimensions corresponding to the relevant data into the business template;

[0206] Step 3: Perform multi-dimensional business analysis on the relevant data in the business template based on the big data model, and output the business analysis description and visual analysis graphics;

[0207] Step 4: Visualize the business analysis description and visualization analysis graphics.

[0208] The working principle and beneficial effects of the above technical solution are: by obtaining the business configuration requirements, the specific business objectives and requirements of the system and the processing can be accurately determined; by determining the business template and data source, the relevant data can be effectively captured, thereby improving the comprehensiveness of the relevant data capture; by inputting the relevant data and the data dimensions corresponding to the relevant data into the business template, the relevant data can be effectively integrated, thereby effectively realizing the multi-dimensional analysis of business data based on the big data model and the business template, thereby effectively realizing the acquisition of business analysis descriptions and visual analysis graphic structures, which can effectively help users understand and grasp key information more quickly and intuitively; by visually displaying the business analysis description and the visual analysis graphics, it is convenient for users to view the analysis results easily and easily, thereby improving the user experience; this method not only improves the convenience and effectiveness of the analysis, but also has the benefit of ensuring the accuracy of business analysis management.

[0209] Embodiment 10:

[0210] Based on Example 9, this embodiment provides an intelligent configuration analysis method based on a big data model, step 1, obtaining a business configuration requirement, and reading a business template and a data source in the business configuration requirement, including:

[0211] S101: Access a management terminal and obtain a service configuration requirement of the management terminal based on the access result;

[0212] S102: parsing the business configuration requirements, extracting key data segments in the business configuration requirements, and determining business links based on semantic features of the key data segments;

[0213] S103: Determine business objectives and key elements based on the attribute information of the business link, and determine multi-link functional requirements based on the business objectives and key elements;

[0214] S104: Match the target business module from the business module database based on the multi-link functional requirements, and logically combine the target business modules to obtain a business template; at the same time, determine the required data items based on the multi-link functional requirements, and determine the corresponding data source based on the required data items.

[0215] The working principle and beneficial effects of the above technical solution are: by accessing the management terminal, the business configuration requirements can be effectively acquired, and by parsing the business configuration requirements, the key data fragments in the business configuration requirements can be effectively extracted, so that the business requirements can be determined through the semantic features of the key data fragments. Through the attribute information of the business link, the business goals and key elements can be effectively determined, so as to realize the multi-link common requirements based on business goals and key elements. Through the multi-link functional requirements, the target business module can be effectively matched in the business module database, so as to realize the determination of the business template through logical combination. By determining the required data items according to the multi-link functional requirements, the data source can be determined, which provides important guarantees for the efficient operation and accurate analysis of the entire intelligent configurable analysis system.

[0216] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent configuration analysis system based on big data model, characterized in that: include: Configuration requirement acquisition module, used to obtain business configuration requirements and read business templates and data sources in the business configuration requirements; A configuration module is used to capture relevant data from multiple data sources in real time, and input the relevant data and the data dimensions corresponding to the relevant data into the business template; The analysis module is used to perform multi-dimensional business analysis on the relevant data in the business template based on the big data model, and output the business analysis description and visual analysis graphics; The visualization module is used to visualize the business analysis description and visualization analysis graphics.

2. According to claim 1, an intelligent configuration analysis system based on a big data model is characterized in that: Configuration requirements acquisition module, including: A demand access unit, used to access the management terminal and obtain the business configuration requirements of the management terminal based on the access result; Requirements parsing unit, used to: Perform text analysis on business configuration requirements, extract key data segments from the business configuration requirements, and determine business links based on the semantic features of the key data segments; Determine business objectives and key elements based on the attribute information of business links, and determine multi-link functional requirements based on business objectives and key elements; Based on the multi-link functional requirements, target business modules are matched from the business module database, and the target business modules are logically combined to obtain business templates; At the same time, the required data items are determined based on the multi-link functional requirements, and the corresponding data sources are determined based on the required data items.

3. The intelligent configuration analysis system based on big data model according to claim 2 is characterized in that: Requirements analysis unit, including: The result acquisition subunit is used to obtain the business templates and data sources corresponding to different business configuration requirements, and generate a requirement summary based on the multi-link functional requirements of the business configuration requirements; The recording subunit is used to construct an information recording table and record the requirement summary, business template and data source in the information recording table based on the mapping relationship; The template library construction subunit is used to generate a multi-dimensional business configuration requirement template library based on the recording results, configure an external access interface for the multi-dimensional business configuration requirement template library, and complete the construction of the template library based on the configuration results.

4. The intelligent configuration analysis system based on big data model according to claim 1 is characterized in that: Configuration modules, including: A service type acquisition unit, used to acquire the service type of a target service; A management target determination unit, used to read the management target corresponding to each business type; Data capture unit for: Determine the data source type based on the business type, and determine the data capture standard based on the management objectives; Obtain the target data source according to the data source type, and at the same time, crawl data in the target data source according to the data crawling standard to obtain relevant data; The input unit is used to retrieve a business template that is consistent with the business type of the target business, and at the same time, input relevant data and data dimensions corresponding to the relevant data into the business template.

5. The intelligent configuration analysis system based on big data model according to claim 4 is characterized in that: In the data capture unit, data is captured from the target data source according to the data capture standard to obtain relevant data, including: A reading unit is used to read the target data source, determine the data coverage of the target data source, and at the same time, read the data capture standard and determine multiple data capture areas in the target data source according to the data capture standard; A marking unit, used for marking a data capture area within a data coverage range; Distributed layout unit for: Generate data capture features based on data capture standards, and arrange data acquisition nodes in each data capture area according to the marking results. At the same time, construct data receiving nodes, and distribute multiple data acquisition nodes and data receiving nodes according to the preset communication protocol; Among them, one data acquisition node is arranged in one data capture area; The relevant data acquisition unit is used to: Based on the distributed layout result and according to the data receiving node, the initial relevant data corresponding to the data collection node in each data capture area is received in real time; The initial relevant data is cleaned and sorted to obtain relevant data.

6. The intelligent configuration analysis system based on big data model according to claim 1, characterized in that: Analysis modules, including: A coordinate system construction unit, used to construct a time interval, and create multiple time nodes in the time interval according to a preset time interval, and construct a rectangular coordinate system using the multiple time nodes as the horizontal axis and each data dimension as the vertical axis; Data range determination unit, used to: Obtain historical related data, and divide the historical related data according to data dimensions to obtain sub-historical related data sets corresponding to each dimension; Map the sub-history related data sets in the corresponding ordinate with the time nodes of the abscissa to obtain the target change curve of the sub-history related data sets with the time nodes in each data dimension; Collect the curve inflection points in each target change curve, and mark the curve inflection points in each target change curve. At the same time, obtain the data attribute characteristics of each data dimension, and determine the first data range of each data dimension during normal operation and the second data range of each data dimension during abnormal operation based on the data attribute characteristics of each data dimension and the curve inflection points in the corresponding target change curve; Data analysis unit for: Read relevant data collected in real time, and divide the relevant data according to data dimensions to obtain multiple sub-relevant data corresponding to the data dimensions; comparing the sub-related data with the first data range and the second data range of the corresponding data dimension; If the sub-related data is within the first data range, the data change trend of the corresponding sub-related data is output according to the target change curve combined with the big data model; If the sub-related data is within the second data range, an abnormal prediction is performed on the sub-related data according to the target change curve combined with the big data model, and the abnormal prediction data is output; The business analysis description generating unit is used to generate a business analysis description according to abnormal prediction data or data change trend.

7. The intelligent configuration analysis system based on big data model according to claim 1 is characterized in that: In the analysis module, visual analysis graphics are output, including: A visualization graphic model retrieval unit is used to read visualization requirements and retrieve a visualization graphic model from a preset model library according to the visualization requirements; A display title determination unit, used to read the business analysis description and determine the display title according to the business analysis description; The visualization graphic structure generation unit is used to perform a first filling in the visualization image model according to the display title, and perform a corresponding second filling in the visualization graphic model based on the first filling result according to the business analysis description, and at the same time, generate a visualization analysis graphic according to the second filling result.

8. The intelligent configuration analysis system based on big data model according to claim 1, characterized in that: Visualization module, including: A display interface calling unit, used to call the display interface and determine the target size of the display interface; Optimal visible size determination unit for: Determining a first optimal visible size of the visual analysis graph in the display interface according to a target size of the display interface; Determining a second optimal visible size of the business analysis description in the display interface according to the target size of the display interface; Analysis layout unit, used to: Obtaining a sum of the first optimal visible size and the second optimal visible size, and comparing the sum with a target size of the display interface; When the sum of the sizes is less than or equal to the target size of the display interface, layout is performed in the display interface according to the first optimal visible size and the second optimal visible size to obtain the target display interface; When the size is greater than the target size of the display interface, the display interface is copied, and the visual analysis graphics are laid out in the first display interface according to the first optimal visual size according to the copy result, and the business analysis description is laid out in the second display interface according to the second optimal visual size; Generate a target display interface set based on the layout result; The visualization display unit is used to visualize the business analysis description and the visualization analysis graph according to the target display interface or the target display interface set.

9. An intelligent configuration analysis method based on a big data model, characterized in that: include: Step 1: Obtain business configuration requirements and read the business template and data source in the business configuration requirements; Step 2: Capture relevant data from multiple data sources in real time, and input the relevant data and the data source dimensions corresponding to the relevant data into the business template; Step 3: Perform multi-dimensional business analysis on the relevant data in the business template based on the big data model, and output the business analysis description and visual analysis graphics; Step 4: Visualize the business analysis description and visualization analysis graphics.

10. The intelligent configuration analysis method based on big data model according to claim 9, characterized in that: Step 1: Obtain the business configuration requirements and read the business templates and data sources in the business configuration requirements, including: S101: Access a management terminal and obtain a service configuration requirement of the management terminal based on the access result; S102: performing text parsing on the business configuration requirements, extracting key data segments in the business configuration requirements, and determining business links based on semantic features of the key data segments; S103: Determine business objectives and key elements based on the attribute information of the business link, and determine multi-link functional requirements based on the business objectives and key elements; S104: Match the target business module from the business module database based on the multi-link functional requirements, and logically combine the target business modules to obtain a business template; at the same time, determine the required data items based on the multi-link functional requirements, and determine the corresponding data source based on the required data items.

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