Data processing and visualization methods, media and equipment

Abstract

This specification discloses a data processing and visualization method, apparatus, medium, and device, which relate to the computer technology field. The method includes selecting a data platform to acquire source data of a target company, organizing the source data and loading it into a data system as a source database table, performing primary data operations to process the source data into target data, performing secondary data operations to process the target data into value-added data, performing tertiary data operations to process related data into graphical data, and performing data visualization to render the graphical data into a visualization diagram. The method of the present invention at least partially solves the problems of inability to timely and completely acquire source data and inability to effectively utilize source data without processing it, thereby improving data processing efficiency, increasing the accuracy of data analysis of the target company through data modeling, and automatically combining background data with front-end displays such as panel interfaces through data visualization, thereby improving the effectiveness of data presentation and the availability of the data system.

Description

[Technical Field]

[0001] This specification Big Data and Artificial Intelligence In the field of technology, in particular data processing and visualization methods 、 Regarding media and equipment. [Background technology]

[0002] With the development of next-generation information technology, more and more data information resources are generated, providing better support for the development of enterprises in various industries. In the field of modern enterprise management research, listed enterprises are generally selected as the research object, and the business situation and market performance of the target enterprises are used as the benchmark for enterprise management, and relevant plans and programs are formulated.

[0003] At present, for the corresponding business data and market data, the prior art mainly processes selected data according to respective applications and combines it with commonly used data visualization methods.In the process of realizing the present invention, it was found that the prior art still has many problems in the process of obtaining, sorting, processing and visualizing the relevant data of the target enterprises, such as the problem that the source data cannot be obtained timely and completely, the problem that the relevant indicator data has serious delays, the problem that some of the published indicator data still has discrepancies, the problem that some of the relevant data needs to be dynamically updated, which also affects the efficiency of data processing, the problem that there is a lack of a more effective method for analyzing the capabilities of the relevant enterprises and the accuracy of the analysis is not high, the problem that there is a lack of an intuitive and clear data display method for representing the business situation and market of the target enterprises being studied, etc.

[0004] Therefore, how to improve the timeliness and completeness of source data acquisition, improve the efficiency of data processing, improve the accuracy of data analysis for target companies, improve the effectiveness of data display, and improve the availability of data systems are a series of problems that need to be solved urgently. Summary of the Invention

[0005] The present specification provides a data processing and visualization method that at least partially solves the technical problems of increasing the timeliness and completeness of source data acquisition, increasing the efficiency of data processing, increasing the accuracy of data analysis for target companies, increasing the effectiveness of data presentation, and increasing the availability of data systems. 、 Provides media and equipment.

[0006] To solve the above problems, this specification adopts the following technical solution.

[0007] 1. A method of data processing and visualization, comprising: Acquiring source data of the target company from the data platform, storing the source data in a preset data system, and organizing the source data stored in the preset data system before converting it into target data; Create a data model and algorithm, and based on the target data, predict the net profit growth rate of the target enterprise, determine the target enterprise's net profit after deducting corresponding extraordinary profits and losses as operating profit, determine the target enterprise's capability index based on the operating profit, determine the target enterprise's value space based on the capability index and the net profit growth rate, determine the target enterprise's value capability compatibility range and corresponding value score based on the value space, and further determine the target enterprise's comprehensive capability dimension score; Combining the target data, the value space, the value ability, the value score, and the comprehensive ability, and drawing and rendering a corresponding visualization diagram based on the background data relationship in the data model and algorithm, specifically: Selecting the graphic data and combining it with a program that uses the visualization tool software to complete the automated task independently, realizing the combination of background data and front-end display on the panel interface; Drawing and rendering corresponding visualization diagrams according to the background data relationships in the data model and algorithm, including industry map, concept map, comprehensive capability diagram, value capability diagram, growth capability diagram, operating income increase diagram, profit increase diagram, enterprise N-dimensional diagram and panel interface; Here, obtaining source data of the target company from the data platform specifically involves: The target data platform includes a plurality of different data platforms; According to a plurality of preset time points, the source data of the target enterprise corresponding to each time point is obtained from each of the data platforms, specifically, the source data is obtained by a division method based on data attributes and scroll refresh time, and each data belonging to the related data in the report is determined based on the report format, and the source data is obtained from the target data platform based on the computer-written division acquisition conditions to obtain each related data; determining missing data in the source data acquired at the latest time point, retrieving the missing data from source data acquired at other time points, supplementing the source data acquired at the latest time point, and storing the source data in a preset data system as source data to be processed; Then, the source data to be processed is organized into target data; Processing the source data stored in the pre-configured data system includes: performing primary data operations to output the source data as a primary database table; performing secondary data operations, outputting secondary database tables, and using the associated data to create multi-dimensional aggregation data models and algorithms to perform aggregation analysis on the target companies; performing tertiary data operations to process the associated data in the primary database table and the secondary database table into corresponding graphical database tables; Rendering the corresponding visualization includes: determining rendering colors for each of the industry maps and each of the concept maps based on the subordinate and associated relationships between the industry maps and each of the concept maps, and expressing the categories and hierarchical relationships of the industry maps and each of the concept maps through the rendering colors; Here, each industry map is divided based on the industry to which the target enterprise belongs, and each industry map is divided into at least three levels based on the dependency relationship of each industry map; each concept map is divided based on the concept to which the target enterprise belongs, and each concept map is divided into at least three levels based on the association relationship and / or dependency relationship of each concept map; The hierarchical rendering colors of the industry map and the concept map are associated and displayed via the panel interface, and the concept map is scrolled and displayed; A data processing and visualization method for automatically combining and displaying visualization diagrams corresponding to the target data, the value space, the value capability, the value scoring, and the overall capability, and obtaining the N-dimensional diagram of the company used to represent the overall outline of the business situation and market expression of the target company.

[0008] Creating a data model and algorithm, and determining the value capability conformance range and corresponding value score of the target enterprise based on the value space, and further determining each dimension score of the target enterprise's comprehensive capability, specifically: determining a value capability index, a growth capability index, an operating income growth index, and a profit growth index corresponding to the target enterprise based on the target data; Wherein, the value capability index includes the value capability conformance range and corresponding value score of the target enterprise; Based on the four basic dimensions of value capability index, growth capability index, operating income growth index, and profit growth index, the value score may be determined to characterize the overall capability of the target enterprise through interval scoring and contrast dimension.

[0009] Determining the value capability conformance range and corresponding value score of the target enterprise based on the value space specifically includes: It may also include determining a value ability compatibility range based on the upper and lower limits of the value space, comparing the value scores of the upper and lower limits of the value space to take the smaller score and determining a value score corresponding to the value ability.

[0010] Specifically, determining the value space of the target company includes: Based on the target data, predict the target company's net profit growth rate, wherein the net profit growth rate includes a first net profit growth rate, a second net profit growth rate, and a third net profit growth rate, wherein the first net profit growth rate is the net profit growth rate for the first future year, the second net profit growth rate is the net profit growth rate for the second future year, and the third net profit growth rate is the average net profit growth rate for the next two years; determining a capability index of the target company based on the operating profit, the capability indexes including a first capability index, a second capability index, a third capability index, and a fourth capability index, wherein the first capability index is a ratio of the target company's market value to the annualized operating profit according to the current quarter's quarterly report, the second capability index is a ratio of the market value to the operating profit according to the current year's annual report, the third capability index is a ratio of the market value to the target company's operating profit for one year in the future, and the fourth capability index is a ratio of the market value to the annualized operating profit according to the predicted next quarterly report; Determining a value space for the target company based on the capability index and the net profit growth rate includes: determining a first group value index based on the first net profit growth rate, the third net profit growth rate, and the first performance index; determining a second group value index based on the first net profit growth rate, the third net profit growth rate, and the second performance index; determining a third group value index based on the second net profit growth rate, the third net profit growth rate, and the third performance index; determining a fourth group value index based on the first net profit growth rate, the third net profit growth rate, and the fourth performance index; determining an upper limit of the value space based on the first group value index, the second group value index, and the third group value index; determining a lower limit of the value space based on the first group value index, the second group value index, the third group value index, and the fourth group value index.

[0011] determining a value space for the target company; and Determine an incremental market return multiple as a GPET index based on the net profit growth rate and the dynamic price-to-earnings ratio after deducting extraordinary gains and losses of the target company, where the GPET index is a single-stage value index and / or a split-composite accumulation value index, and if the GPET index is an accumulation value index, determine the GPET index by combining a cross-comparison pricing method based on a comparison between the split-composite and / or combined net profit growth rate and the dynamic price-to-earnings ratio after deducting extraordinary gains and losses of the target company; and determining a value space based on the GPET index.

[0012] After determining the value space of the target company, Obtaining goodwill data from the platform corresponding to the ratio of goodwill to assets of the target company; and modifying the value space based on the goodwill data.

[0013] Determine the score for each dimension of the target company's overall capability; and The method may include determining a growth rate forecast indicator for the target company based on the forecast earnings per share growth rate included in the target data, re-determining the growth rate forecast indicator after updating the target data, determining a change trend in the target company's growth potential based on the change trend of the growth rate forecast indicator, and determining a growth capability dimension score in the target company's overall capability.

[0014] After determining the score for each dimension of the target company's overall capability, Re-acquiring source data of the target company at a predetermined time interval; In response to a refresh operation on the target data, the method may include using the most recently acquired target data to determine the range of change in the year-to-year forecast data of operating revenue, net profit, and earnings per share of the target company contained in the updated target data and the range of change in the year-to-year forecast data of operating revenue, net profit, and earnings per share of the target company contained in the target data before the update, and determining the range of correction based on the range of change.

[0015] After determining the score for each dimension of the target company's overall capabilities, Based on the target data, a target price total value for the target company may be determined, and based on the target price total value and current prices, a target space for the target company may be determined, and the target price total value data may be periodically updated to maintain a corrective cover. 。

[0016] A data processing and visualization medium that is a computer-readable storage medium on which a computer program is stored that, when executed by a processor, implements the method according to any one of the preceding claims.

[0017] An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, the processor implementing the method according to any one of the preceding claims when executing the program.

[0018] The at least one technical solution adopted in this specification can achieve the following beneficial effects:

[0019] The data processing and visualization method provided in this specification first obtains source data of a target enterprise from a data platform, stores the source data in a pre-defined data system, and organizes the source data stored in the pre-defined data system into target data. Then, a data model and algorithm are created to predict the net profit growth rate of the target enterprise based on the target data, determine the target enterprise's corresponding net profit after deducting extraordinary gains and losses as operating profit, determine the target enterprise's capability indicators based on the operating profit, determine the target enterprise's value space based on the capability indicators and the net profit growth rate, determine the target enterprise's value capability compatibility range and corresponding value score based on the value space, and further determine the dimension scores of the target enterprise's comprehensive capability. Then, the target data, the value space, the value capability, the value score, and the comprehensive capability are combined to draw and render a corresponding visualization diagram based on the background data relationships in the data model and algorithm.

[0020] As can be seen from the above method, by selecting different data platforms, acquiring data at different times, and splitting the data, it is possible to ensure that source data is acquired in a timely and complete manner. The acquired source data is organized according to data attributes and data scripts to ensure that the source data is available. A multi-dimensional integrated data model and algorithm are created, and new indicators are established to strengthen the rigor of the data model definition. In particular, the forecast net profit growth rate is determined by comparing it with the dynamic price-earnings ratio after deducting extraordinary gains and losses, and extraordinary gains and losses are deducted to reduce the impact of factors other than the company's normal operations on the analysis. The data model and algorithm of the present invention combine the determination of transfer basis splits to reduce the determination deviation using a mutual comparison price-taking method. The determination of additional forecast data improves the timeliness, and the determination of value adjustment coefficients reduces the risk. Thus, the data model and algorithm of the present invention systematically improve the accuracy of enterprise comprehensive capability analysis. By combining with a program for completing automated tasks independently created using visualization tool software, the combination of background data and front-end display on the panel interface is realized, improving the effectiveness of data display and also improving the availability of the data system. [Brief explanation of the drawings]

[0021] The drawings described herein are intended to provide further understanding of the present specification and constitute a part of the present specification, and the schematic examples and their descriptions in the present specification are intended to help interpret the present specification and are not intended to constitute undue limitations on the present specification.

[0022] [Figure 1] 1 is a flowchart of the data processing and visualization method provided herein. [Figure 2] FIG. 1 is a schematic diagram of an example of the data processing and visualization method provided herein. [Figure 3] 1 is a flowchart of a software medium implementation provided herein. [Figure 4] FIG. 2 is a schematic diagram of an electronic device corresponding to FIG. 1 provided herein. DETAILED DESCRIPTION OF THE INVENTION

[0023] In order to clarify the purpose, technical solution and advantages of this specification, the technical solution of this specification will be clearly and completely described below based on the specific embodiments of this specification and the corresponding drawings. It is clear that the described embodiments are only some of the embodiments of this specification, and do not cover all the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of this specification.

[0024] As can be seen from the above description, the key innovations of the data processing and visualization method provided herein are: acquiring source data in a partitioned manner based on relevant data attributes and rolling refresh times; creating a multi-dimensional integrated data model and algorithm; establishing new indicators to strengthen the rigor of the data model definition, particularly by comparing and determining the forecast net profit growth rate and the dynamic price-earnings ratio after non-recurring gains and losses; combining a moving-base partition determination to adopt a cross-comparison price-earnings ratio; adding forecast data determination and value adjustment coefficient determination; combining a program that uses visualization tool software to complete independently created automated tasks, combining background data with a front-end display of a panel interface, drawing and displaying visualization charts based on background data relationships in the data model and algorithm; and artificial intelligence rendering using machine learning and model training based on map mode, and artificial intelligence data simulation, prediction, and analysis based on machine learning and model training of the data model and algorithm. In this specification, the entity that specifically performs the data processing method may be a terminal device used by an operator, such as a desktop computer, laptop computer, or mobile phone; and for the sake of convenience, hereinafter, only the terminal device will be referred to as the entity that performs the data processing method provided herein.

[0025] Currently, prior art still has many problems in the acquisition, organization, processing and visualization of relevant data of target companies, such as the inability to acquire source data in a timely and complete manner, the existence of serious delays in relevant indicator data, the existence of discrepancies in some published indicator data, the need for dynamic updates in some relevant data, which also affects the efficiency of data processing, the lack of more effective methods for analyzing the capabilities of relevant companies, and the inaccuracy of the analysis, and the lack of an intuitive and clear way to present the business situation and market of the target companies being studied.

[0026] Based on this, the present specification provides a data processing and visualization method to at least partially solve the above problems.

[0027] Hereinafter, the technical solutions provided by the embodiments of this specification will be described in detail with reference to the accompanying drawings.

[0028] FIG. 1 is a flowchart of the data processing and visualization method provided herein, which includes the following steps:

[0029] S101: Obtain source data of the target enterprise from the target data platform, store the source data in a pre-set source data system, and organize the source data stored in the pre-set data system into target data.

[0030] Specifically, the terminal device can acquire source data of the target company corresponding to each time point from each of multiple different data platforms according to multiple preset time points, determine data missing from the source data acquired at the latest time point, search for the missing data from source data acquired at other time points, supplement the source data acquired at the latest time point, store the source data as the source data to be processed in a preset data system, and then organize the source data to be processed as target data.

[0031] The terminal device can acquire source data of the target company corresponding to each time point from each of the data platforms according to multiple pre-set time points and based on computer-written division acquisition conditions.

[0032] In actual applications, the data to be processed can be classified into relevant data and non-relevant data. Here, relevant data must be obtained after other data has been determined. For example, if clothing factory A has not yet obtained its clothing material expenditures today, it cannot determine the data of today's net profit.

[0033] Therefore, when related data in the data to be processed is acquired as a whole, some related data may be lost, resulting in the loss of other related data and less acquired data. In this specification, the terminal device can acquire the format of the target company's report, determine each piece of data belonging to the related data in the report based on the report format, respectively capture each piece of related data, and acquire source data for each item. In actual application, the terminal device can acquire source data from the target data platform according to computer-written conditions and respectively acquire each piece of related data.

[0034] S102: Create a data model and algorithm, and based on the target data, predict the net profit growth rate of the target enterprise, determine the target enterprise's net profit after deducting corresponding extraordinary gains and losses as operating profit, determine the target enterprise's capability index based on the operating profit, determine the target enterprise's value space based on the capability index and the net profit growth rate, determine the target enterprise's value capability compatibility range and corresponding value score based on the value space, and further determine the score for each dimension of the target enterprise's overall capability.

[0035] After obtaining the target data, the terminal device can predict the target company's net profit growth rate based on the target data. Specifically, the terminal device may use a pre-trained net profit growth rate prediction model to predict the target company's net profit growth rate, or may directly use the target company's own predicted net profit growth rate contained in the target data.

[0036] In actual application, there may be some non-periodic additional revenues, which may cause the net profit data in the target data to be inaccurate. For example, Clothing Factory A sold a factory in the current quarter, and the revenue was included in the net profit for the current quarter, significantly increasing Clothing Factory A's net profit for the current quarter. This increase in net profit cannot characterize Clothing Factory A's management capabilities. Therefore, in order to more accurately analyze the management capabilities of the target company, in this specification, the target company's net profit after deducting the corresponding extraordinary gains and losses is determined based on the target data and is taken as operating profit.

[0037] In this specification, in order to more accurately characterize the management capability of the target enterprise, the ratio of the target enterprise's market value to its operating profit can be used as the capability indicator of the target enterprise, and the subsequent value space can be determined based on the capability indicator of the target enterprise.

[0038] After obtaining the target enterprise's net profit growth rate and current profit, the terminal device can determine the target enterprise's value space, which is an indicator characterizing the target enterprise's business management ability.

[0039] Specifically, the terminal device can predict the target company's net profit growth rate based on the target data, wherein the net profit growth rate includes a first net profit growth rate, a second net profit growth rate, and a third net profit growth rate, wherein the first net profit growth rate is the net profit growth rate for a first future year, the second net profit growth rate is the net profit growth rate for a second future year, and the third net profit growth rate is the average net profit growth rate for two future years; determine the target company's capability index based on the operating profit, wherein the capability index includes a first capability index, a second capability index, a third capability index, and a fourth capability index, wherein the first capability index is the ratio of the target company's market value to its annualized operating profit for the current quarter's quarterly report, the second capability index is the ratio of the market value to its operating profit for the current year's annual report, the third capability index is the ratio of the market value to the target company's operating profit for one future year, and the fourth capability index is the ratio of the market value to its annualized operating profit for the predicted next quarterly report; and then The terminal device can determine a value space of the target company based on the capability index and the net profit growth rate, specifically including: determining a first group value index based on the first net profit growth rate, the third net profit growth rate, and the first capability index; determining a second group value index based on the first net profit growth rate, the third net profit growth rate, and the second capability index; determining a third group value index based on the second net profit growth rate, the third net profit growth rate, and the third capability index; determining a fourth group value index based on the first net profit growth rate, the third net profit growth rate, and the fourth capability index; determining an upper limit of the value space based on the first group value index, the second group value index, and the third group value index; and determining a lower limit of the value space based on the first group value index, the second group value index, the third group value index, and the fourth group value index.

[0040] When the terminal device determines the value space of the target company, it can further determine an incremental market return multiple as a GPET index based on the net profit growth rate and the dynamic price-earnings ratio after deducting extraordinary gains and losses of the target company, where the GPET index is a single-stage value index and / or a split-composite accumulation value index, and if the GPET index is the accumulation value index, it determines the GPET index by combining a cross-comparison pricing method based on a comparison between the split-composite and / or combined net profit growth rate and the dynamic price-earnings ratio after deducting extraordinary gains and losses of the moving company, and determines a value space based on the GPET index.

[0041] In addition, after determining the value space of the target company, the terminal device can obtain goodwill data from the target platform corresponding to the proportion of the target company's goodwill in its assets, and modify the value space based on the goodwill data.

[0042] The terminal device can determine the value capability conformance range based on the upper and lower limits of the value space, and determine the corresponding value score of the value capability by comparing the value scores of the upper and lower limits of the value space and taking the smaller score. Note that, due to the influence of the current market environment, the target enterprises often cannot achieve the upper limit of the value space, and at the same time, for conservative estimation, the lower limit of the value space is often taken as the value score corresponding to the value space.

[0043] The terminal device can determine a value capability index, a growth capability index, an operating income growth index, and a profit growth index corresponding to the target enterprise based on the target data, wherein the value capability index includes a value capability conformance range of the target enterprise and a corresponding value score, and the terminal device can determine the value score to characterize the overall capability of the target enterprise through interval scoring and contrast dimensions based on the four basic dimensions of the value capability index, growth capability index, operating income growth index, and profit growth index.

[0044] The terminal device may determine the score for each dimension of the target company's overall capability, and further determine a growth rate forecast indicator for the target company based on the forecast earnings per share growth rate included in the target data, re-determine the growth rate forecast indicator after updating the target data, determine the change trend of the target company's growth potential based on the change trend of the growth rate forecast indicator, and determine the growth capability dimension score in the target company's overall capability.

[0045] In addition, to ensure the validity of the data, after determining the scores for each dimension of the target company's overall capability, the terminal device re-acquires the source data of the target company at a preset time interval, and in response to a refresh operation on the target data, uses the latest acquired target data to determine the year-to-year forecast data of the target company's operating revenue, net profit, and earnings per share contained in the updated target data and the range of change in the year-to-year forecast data of the target company's operating revenue, net profit, and earnings per share contained in the target data before the update, and determines the range of correction based on the range of change.

[0046] After determining the dimension scores of the target enterprise's comprehensive capabilities, the terminal device can determine the target price comprehensive value of the target enterprise based on the target data, determine the target space of the target enterprise based on the target price comprehensive value and the current price, and maintain the corrected coverage by periodically updating the target price comprehensive value data.

[0047] S103: The target data, the value space, the value ability, the value scoring, and the comprehensive ability are combined to draw and render a corresponding visualization diagram based on the background data relationship in the data model and algorithm.

[0048] The terminal device selects graphic data and combines it with a program that uses visualization tool software to complete an automated task independently created, to realize the combination of background data and the front-end display of the panel interface, and can draw and render corresponding visualization diagrams according to the background data relationships in the data model and algorithm, where the visualization diagrams include industry maps, concept maps, comprehensive capability diagrams, value capability diagrams, growth capability diagrams, operating income increase diagrams, profit increase diagrams, enterprise N-dimensional diagrams, and panel interfaces.

[0049] The terminal device determines the rendering color of each industry map and each concept map based on the dependency and association relationships between each industry map and each concept map, and can represent the category and hierarchical relationship of each industry map and each concept map through the rendering color, wherein each industry map is divided based on the industry to which the target enterprise belongs, and each industry map is divided into at least three levels based on the dependency relationships of each industry map, and each concept map is divided based on the concept to which the target enterprise belongs, and each concept map is divided into at least three levels based on the association relationships and / or dependency relationships of each concept map.

[0050] The present specification provides a data processing and visualization method, including selecting a data platform to obtain source data of a target enterprise, organizing the source data and loading it into a data system as a source database table, performing primary data operations to process the source data into target data, performing secondary data operations to process the target data into added-value data, performing tertiary data operations to process related data into graphic data, and performing data visualization to draw and render the graphic data into a visualization diagram.

[0051] We developed a multi-dimensional aggregation data model and algorithm to conduct an aggregation analysis on the target companies, and established new indicators, mainly including the incremental market earnings multiple (GPET) and the dynamic price-earnings ratio (PEAN) after extraordinary gains and losses. GPET is a dynamic indicator that can be used as a single value indicator or a composite integrated value indicator, and is determined by the growth rate of net profit and the dynamic price-earnings ratio after extraordinary gains and losses.

[0052] PEAN is a dynamic indicator, determined by the market value and the annualized operating profit, and represents the target company's performance indicator in determining the value space in a data model.

[0053] Comprehensive capabilities include four basic dimensions, namely value capabilities, growth capabilities, operating income increase, and profit increase, as well as comparative dimensions. A scoring method based on division and comparison is used, and the scoring criteria are set on an annual basis. Specifically, this is done in the form of an expert symposium. Comprehensive capabilities are a comprehensive embodiment of the capabilities of the target enterprise in terms of the above four basic dimensions and comparative dimensions.

[0054] Based on the value scoring corresponding to the upper and lower limits of the value space determination result, the value scoring of the value capability is the one with the smallest score, and the value capability is embodied as the capability of the value conformance range that the target enterprise can achieve to achieve the value floating target.

[0055] The value space is determined by comparing the forecast net profit growth rate with the dynamic price-earnings ratio after deducting extraordinary gains and losses. Specifically, the corresponding figures are determined using the compound growth rate and split growth rate of two complete future years, and then the moving standards including the current quarter, current year, forecast quarter and future year are combined to determine each. Finally, a value is obtained by combining the mutual comparison method. In the process of determining the value, data with a low determined value is preferentially adopted as a constraint. Related determinations are also made for the forecast data of companies that have already issued performance forecasts. In addition, the proportion of goodwill in assets is approximately used as a risk factor for the realization of corporate value. The related determinations are then used as the adjustment coefficient for the corporate value space, and the value space is embodied as the achievable increase range of the target corporate value.

[0056] The target space captures the target price overall value of the data summary table in the target data, determines the target space in which the current price is more intuitive than the overall target price, and represents the determined result as a percentage.

[0057] Growth capacity is calculated by calculating the growth rate as future growth capacity based on the forecast earnings per share growth rate, and dynamically tracking the adjustment trend of the target company's growth forecast using growth forecast revisions.

[0058] Forecast revisions are made by periodically obtaining annual forecast data for the target company's operating revenue, net profit, and earnings per share, and then comparing the current value with the previous value for each item to obtain the revision range.

[0059] This specification provides a data processing and visualization device, including an acquisition module for selecting a data platform to acquire source data of a target company, an organization module for organizing the source data and loading it into a data system as a source database table, a processing module 1 for performing primary data operations to process the source data into target data, a processing module 2 for performing secondary data operations to process the target data into added value data, a processing module 3 for performing tertiary data operations to process related data into graphic data, and a visualization module for performing data visualization to draw and render the graphic data into a visualization diagram.

[0060] The technical solutions provided by the embodiments of this specification will be described in detail below with reference to the accompanying drawings.

[0061] FIG. 2 is a schematic diagram of an example of the data processing and visualization method provided herein, including:

[0062] S201: Source data acquisition.

[0063] You can select a data platform to obtain source data for the target company.

[0064] The terminal device selects different data platforms and periodically compares them to reduce the platform acquisition limit, acquires source data from the selected data platform using computer write conditions, compensates for acquisition losses due to fluctuations in background data calculation at a certain time by acquiring data at different points in time, and adopts a division method for related data attributes and rolling refresh time to divide the specific acquisition into 1-N stages.

[0065] In actual data acquisition processes, data platforms have limitations on the amount of data they can acquire. For example, one platform is configured with 80 search criteria, 120 header indicator columns, and 500 character query length. However, the amount of data required for this invention exceeds these settings. The data platform does not always refresh all indicator data at the same time. This is related to data attributes. For example, while it is possible to acquire operating revenue data for all target companies at 3:00 PM, it is not possible to acquire complete rolling net profit data. To solve this problem, in this embodiment, the source data is divided into eight stages and acquired at 3:00 PM and 8:00 AM each day, ensuring the speed and completeness of data acquisition.

[0066] Here, the source data of the target company may be data of each item in the company's daily report, monthly report, quarterly report, annual report, etc. In this specification, the terminal device may set multiple time points for acquiring data in order to acquire source data of the target company corresponding to each time point.

[0067] After the terminal device acquires source data corresponding to a plurality of time points, the data to be processed acquired at the most recent time point is the most accurate data, so the terminal device first determines data missing from the data to be processed acquired at the latest time point, then searches for the missing data from source data acquired at other time points, supplements the source data acquired at the latest time point, and stores the source data in a preset data system as the source data to be processed.

[0068] In practical applications, source data can be classified into relevant data and non-relevant data, where relevant data must be obtained after other data has been determined. For example, if Company A has not obtained extraordinary profit and loss data today, it cannot determine the data of deducting non-net profit.

[0069] Regarding related data, when the related data in the source data is acquired as a whole, some of the related data may be lost, resulting in the loss of other related data and less acquired data. Therefore, in this specification, the terminal device can acquire the format of the target company's report, determine the data of each item belonging to the related data in the report based on the report format, respectively capture each related data, and acquire the source data of each item.

[0070] S202: Source data organization.

[0071] The source data is organized and loaded into a pre-configured data system as a source database table. The terminal device organizes the acquired source data to be processed according to data attributes and data scripts, and loads the data into the data system as a source database table. In this embodiment, the data fields, data scripts, and data order are mainly organized, and redundant data is removed before loading into the data system to ensure that the data format is consistent with the design of the data system.

[0072] S203: Primary data processing.

[0073] The terminal device can perform primary data operations to process source data into target data. It performs the primary data operation Ya = f(Xb), outputs the primary database table, and In an embodiment, the terminal device converts the source data into a daily table, a quarterly table, a yearly table, an irregular table, and a total database table based on the definition fields representing data attributes and the time script.

[0074] S204: Secondary data processing.

[0075] The terminal device can perform secondary data operations to process the target data into additional value data.

[0076] Execute the secondary data operation Yc=f(Xd), output the secondary database table, and The instrument can use the relevant data to create multi-dimensional aggregation data models and algorithms to perform aggregation analysis on target companies.

[0077] below is an example of the data model and algorithms provided herein. explanation and includes the following methods:

[0078] New indicators are established, mainly including the incremental market earnings multiple (GPET) and the dynamic price-earnings ratio (PEAN) after extraordinary gains and losses.

[0079] GPET is a dynamic indicator, which can be used as a single value indicator or a composite integrated value indicator, and is determined by the growth rate of net profit and the dynamic price-earnings ratio after deducting extraordinary gains and losses.

[0080] PEAN is a dynamic indicator, determined by the market value and the annualized operating profit, and represents the target company's performance indicator in determining the value space in a data model.

[0081] Comprehensive capabilities including four basic dimensions of value capability, growth capability, operating income increase, and profit increase, as well as a comparative dimension, will be determined, and a scoring method will be used in which the capabilities are divided into intervals and compared. The scoring criteria will be examined on an annual basis, and this will be done in the form of an expert symposium.

[0082] Specifically, the overall ability index is represented by CAP, and the section scoring criteria can be referred to as follows: [Table 1]

[0083] Determine the value ability, determine the upper and lower limits of the result based on the value space, take the smaller score of the corresponding score as the value ability score, determine the corresponding value ability conformance range, including the upper and lower limits of the value ability determination result.

[0084] Specifically, the value capability index is represented by VC, and the following formula is used:

number

[0085] The value space is determined by comparing the forecast net profit growth rate with the dynamic price-earnings ratio after deducting extraordinary gains and losses. Specifically, the corresponding figures are determined using the compound growth rate and split growth rate of two complete future years, and then the moving standards including the current quarter, the current year, the forecast quarter and the future year are combined to determine the corresponding figures. Finally, the value is obtained by combining the mutual comparison method. In the process of obtaining the value, the data with the lowest determined value is preferentially adopted as the constraint. Related determinations are also made for the forecast data of companies that have already issued performance forecasts. In addition, the proportion of goodwill in assets is approximately used as a risk factor for the realization of corporate value, and the related determination is then used as the adjustment coefficient for the corporate value space.

[0086] Specifically, refer to the following formula:

number

[0087] Specifically, reference is made to the determined correlation matrix. [Table 2]

[0088] The target space is determined, the target price comprehensive value of the data summary table in the target data is captured, and the target space whose current price is more intuitive than the comprehensive target price is determined, and represented by the percentage of the determination result.

[0089] Specifically, refer to the following formula:

number

[0090] Determine growth capacity, derive growth rate forecasts using projected earnings per share growth rates to represent future growth capacity, and dynamically track the adjustment trends of the target company's growth forecasts using growth forecast revisions.

[0091] Specifically, refer to the following formula:

number

[0092] Forecast revisions are determined, and annual forecast data for the target company's operating revenue, net income, and earnings per share is periodically obtained, and the current value and previous value for each item are compared to obtain the extent of the revision.

[0093] Specifically, refer to the following formula:

number

[0094] The terminal device can determine the value capacity range and value capacity score based on the above formula, determine the value space, target space, growth capacity, and forecast revision, and thereby determine the comprehensive capacity analysis of the target enterprise.

[0095] the above De To clarify the explanation of the data model and algorithm, the key indicators are summarized as follows: New indicators [Table 3] General indicators [Table 4]

[0096] S205: Tertiary data processing.

[0097] The terminal device can perform tertiary data operations to process the related data into graphical data.

[0098] Tertiary data calculation Ym = f(Xn) is performed, and the related primary and secondary data are displayed in the diagram. In this embodiment, the industry and concept data in the data summary table in the primary database table are selected, and data related to overall capacity, value capacity, growth capacity, operating income increase, and profit increase in the secondary database table are selected, and these data are processed into the corresponding diagram database table.

[0099] S206: Data visualization.

[0100] The terminal device can perform data visualization and display the graphical data by drawing it into a visualized diagram.

[0101] Select graphic data and combine it with a program that completes automated tasks created by the user using visualization tool software, realizing the combination of background data and front-end display on the panel interface. The aforementioned Based on the background data relationships in the data model and algorithm, corresponding visualization diagrams are drawn and rendered, where the industry map and concept map also respectively adopt the methods of dependency and relationship hierarchy, rendering color, and representing belonging categories and hierarchical relationships with color.

[0102] In this embodiment, the first-level industry map, second-level industry map, third-level industry map, first-level concept map, second-level concept map, third-level concept map, comprehensive capability map, value capability map, growth capability map, operating income growth map, profit growth map, enterprise N-dimensional map and panel interface are respectively output, and the relationship between these maps is displayed through human interaction, buttons, colors, marks, etc. through the operation design of the terminal panel interface, optimizing the user experience, improving the effectiveness of data display and increasing the availability of the data system.

[0103] Below 、 The industry map layering and visualization provided herein Using an example explain.

[0104] The industry map is divided according to the industry to which the target enterprise belongs, and is divided into a total of three levels according to the subordinate relationships, with the first level including the second level and the second level including the third level. The industry data for each level is plotted on a grid through the terminal device and rendered in color, different industries and different levels within the same industry are distinguished by color. Each cell in these diagrams indicates the name of the industry and the number of enterprises included. The terminal device can find the target enterprises through the target data linked to these cells, and the industry information is also displayed on the panel interface of the target enterprises.

[0105] below 、 The concept map hierarchy and visualization provided in this paper Using an example Explain.

[0106] The concept map is divided according to the concepts to which the target enterprises belong, and is divided into a total of three levels according to related but not necessarily subordinate relationships. The concept data of each level is drawn on a grid through the terminal device and color-rendered, different concepts and different levels of the same concept are distinguished by color. Each cell in these diagrams indicates the concept name and the number of enterprises included. The terminal device can find the target enterprises from the target data linked to these cells, and the concept information is also displayed on the panel interface of the target enterprises.

[0107] below 、The present specification provides an example of a comprehensive capability diagram. Using explain.

[0108] Total The combined capability map adopts the form of a radar diagram and is expressed as a value radar map, with the outer curve representing the standard scoring of the target company within the industry determined based on the graphic data acquired by the terminal device, and the inner curve representing the company's corporate scoring. The terminal device can score the target company in four dimensions: value capability, growth capability, operating income increase, and profit increase.

[0109] below 、 Examples of value capability diagrams provided herein are Using explain.

[0110] Price The value capability diagram adopts the value space determination and is expressed as a value space diagram, and the terminal device can determine the corresponding graphic data as a fitting curve of the value capability range of the target enterprise, and combines the existing target price comprehensive value and the current price, i.e., the display of the current price, to intuitively and clearly express the improvement capability space that the enterprise value has. Here, for a more recognizable display, V max and V min In the corresponding data model and algorithm embodiment using The upper and lower limits of the value capacity determination range VC max and VC min At the same time, the terminal device draws a comprehensive target line according to the acquired target price comprehensive value data and corresponding correction data.

[0111] below 、 Examples of growth potential diagrams provided herein are Using explain.

[0112] Growth The capacity chart adopts the determination of growth forecast and is expressed as a growth forecast chart, and the terminal device can plot the corresponding graphic data on the curve of the current value and previous value of the growth forecast, thereby showing the tendency of the target enterprise's possibility of achieving future growth.

[0113] below 、Examples of operating income growth charts provided herein are Using explain.

[0114] Business The business revenue growth curve and histogram are drawn based on the graphic data acquired by the terminal device, and intuitively show the target company's achievement status in terms of forecasted operating revenue targets, including the allocation and accumulation of forecasted targets, the accumulation of actual operating revenue, and the correction of forecasted targets. Furthermore, the graphics can be used to observe data fluctuation trends compared to the same period of the previous year and the previous period.

[0115] below 、 Examples of profit growth figures provided herein are Using explain.

[0116] The profit growth curve and histogram are drawn based on the graphic data acquired by the terminal device and intuitively show the target company's progress towards achieving its forecasted profit targets, including the allocation and accumulation of forecast targets, the accumulation of actual profits, and the revision of forecast targets. Furthermore, the graphics can be used to observe the trends in data fluctuations compared to the same period last year and the previous period.

[0117] below 、 The present specification provides an example of an N-dimensional enterprise diagram. Using explain.

[0118] end The terminal device can automatically combine and display the visualization charts of the above five dimensions, and can centrally display the current status, trends, and expected fluctuations in each dimension of the company's overall capacity, value capacity, growth capacity, operating income growth, and profit growth, and can represent the overall outline of the target company's business situation and market performance in a single integrated chart.

[0119] below 、 Examples of panel interface diagrams provided herein are Using explain.

[0120] endThe terminal device can create an intuitive, clear and easy-to-operate panel interface as a window that can be used as a data system, and the terminal device can operate the central button. Different figures combined into a panel interface Display can 、 In addition, the right side of the panel interface displays hierarchical rendering colors related to the industry map and concept map, and in particular, the concept map section can be scrolled by sliding it with the mouse. In addition, the panel interface 、 Related display of target data was also performed.

[0121] That's all about the background data for data visualization. 、 It is based on data models and algorithms.

[0122] As can be seen from the above method, the terminal device can select different data platforms, acquire data at different times, and acquire data in a timely and complete manner to ensure that source data is acquired. The acquired source data can be organized according to data attributes and data scripts to ensure that the source data is available. A multi-dimensional integrated data model and algorithm are created, and new indicators are established to strengthen the rigor of the data model definition. In particular, the forecast net profit growth rate is determined by comparing it with the dynamic price-earnings ratio after deducting extraordinary gains and losses, and extraordinary gains and losses are deducted to reduce the impact of factors other than the company's normal operations on the analysis. The data model and algorithm of the present invention combine the determination of transfer basis splits to reduce the determination deviation using the mutual comparison price-taking method. The determination of additional forecast data improves the timeliness, and the determination of value adjustment coefficients reduces the risk. Thus, the data model and algorithm of the present invention systematically improve the accuracy of enterprise comprehensive capability analysis. Combined with a program for completing automated tasks independently created using visualization tool software, the combination of background data and front-end display on the panel interface is realized, improving the effectiveness of data display and also improving the availability of the data system.

[0123] The above is a data processing method provided by one or more embodiments of this specification. 。

[0124] The present specification provides a data processing and visualization medium, i.e., a computer-readable storage medium, having a computer program stored therein, the computer program being capable of executing the method illustrated in the flowcharts of FIGS. 1 and 2 when executed by a processor.

[0125] figure 3 As shown in Fig. 1, database software is selected as the data processing tool software, and a corresponding computer program is created using SQL statements, an automatic programming language, and controls for the database table design and creation part. Then, data visualization tool software is selected, and the database table interface is opened from the database software to the data visualization software. A graphics drawing program is created using the automatic programming language and controls, and a panel interface is designed and created. The operation and use of the data system is realized through software implementation.

[0126] Here, by adopting the artificial intelligence technologies of machine learning and model training based on the map data model, which includes word frequency statistics, class rules, number merging, color value reading, and color rendering of map data, the computer program can automatically render and automatically update the corresponding map model, ensuring that the more than 1,000 colors that characterize industry concept attributes are unique. Furthermore, based on the data model and algorithm, the artificial intelligence technologies of machine learning and model training are also adopted for the output of value data, which can provide applications such as simulation, prediction, and analysis of more specialized data sets.

[0127] This specification provides a data processing and visualization device, i.e., an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable by the processor, and which, when executing the program, implements the method described in the flow charts of Figures 1 and 2.

[0128] figure 4 A structural schematic diagram of an electronic device corresponding to FIG. 1 is shown in FIG. 1. In terms of hardware, this electronic device includes a processor, an internal bus, a network interface, memory, and non-volatile memory, and may also include hardware necessary for other tasks. The processor loads the corresponding computer program from the non-volatile memory into memory and executes it to implement the data processing method described in FIG. 1. Of course, this specification does not exclude other implementation forms other than software implementation, such as logic devices or a combination of software and hardware. In other words, the execution entity of the following process flow is not limited to each logic unit, but may also be hardware or logic devices. It is clear to those skilled in the art that a hardware circuit that implements the logical method flow can be easily obtained by simply programming the method flow logically using some of the above hardware description languages ​​and programming it into an integrated circuit.

[0129] The systems, devices, modules, or units described in the above embodiments may be specifically implemented by computer chips or physical objects, or may be implemented by products having certain functions. Those skilled in the art should understand that the embodiments of the present specification may be provided as methods, systems, or computer program products. This specification will be described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present specification. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions are provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, such that the instructions, executed by the processor of the computer or other programmable data processing device, generate an apparatus for implementing the functions specified in one or more flows and / or one or more blocks in the flowcharts and / or block diagrams.

[0130] These computer program instructions may be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, and the instructions stored in the computer-readable memory generate an article of manufacture that includes an instruction apparatus that implements the functions specified in one or more flows of the flowcharts and / or one or more blocks of the block diagrams. In a typical arrangement, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0131] Those skilled in the art should understand that the embodiments of the present specification may be provided as a method, a system, or a computer program product. Accordingly, the present specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. The present specification may also take the form of a computer program product embodied in one or more computer-usable storage media containing computer-usable program code. The present specification may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types.

[0132] It is noted that the use of the terms "comprehensive," "including," or any variation thereof, is intended to imply a non-exclusive inclusion, such that a process, method, article, or apparatus that includes a set of elements includes not only those elements but also other elements not expressly listed, or includes the inherent elements of such process, method, article, or apparatus. In the absence of further limitations, an element limited by "including one of..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0133] Each embodiment in this specification will be described in a sequential manner, and the same or similar parts between the embodiments may be referred to, and each embodiment will focus on the differences from other embodiments. In particular, since the system embodiments are basically similar to the method embodiments, the description will be relatively simple, and the relevant points may be referred to the description of some of the method embodiments.

[0134] The above description is merely an example of the present specification and is not intended to limit the present specification. Various modifications and variations are possible for those skilled in the art to make to the present specification. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present specification should be included within the scope of the claims of the present specification.

Claims

1. 1. A method of data processing and visualization, comprising: Acquiring source data of the target company from the data platform, storing the source data in a preset data system, and organizing the source data stored in the preset data system before converting it into target data; Create a data model and algorithm, and based on the target data, predict the net profit growth rate of the target enterprise, determine the target enterprise's net profit after deducting corresponding extraordinary profits and losses as operating profit, determine the target enterprise's capability index based on the operating profit, determine the target enterprise's value space based on the capability index and the net profit growth rate, determine the target enterprise's value capability compatibility range and corresponding value score based on the value space, and further determine the target enterprise's comprehensive capability dimension score; Combining the target data, the value space, the value ability, the value score, and the comprehensive ability, and drawing and rendering a corresponding visualization diagram based on the background data relationship in the data model and algorithm, specifically: Selecting the graphic data and combining it with a program that uses the visualization tool software to complete the automated task independently, realizing the combination of background data and front-end display on the panel interface; Drawing and rendering corresponding visualization diagrams according to the background data relationships in the data model and algorithm, including industry map, concept map, comprehensive capability diagram, value capability diagram, growth capability diagram, operating income growth diagram, profit growth diagram, enterprise N-dimensional diagram and panel interface; Here, obtaining source data of the target company from the data platform specifically involves: The target data platform includes a plurality of different data platforms; According to a plurality of preset time points, the source data of the target enterprise corresponding to each time point is obtained from each of the data platforms, specifically, the source data is obtained by a division method based on data attributes and scroll refresh time, and each data belonging to the related data in the report is determined based on the report format, and the source data is obtained from the target data platform based on the computer-written division acquisition conditions to obtain each related data; determining missing data in the source data acquired at the latest time point, retrieving the missing data from source data acquired at other time points, supplementing the source data acquired at the latest time point, and storing the source data in a preset data system as source data to be processed; Then, the source data to be processed is organized into target data; Processing the source data stored in the pre-configured data system includes: performing primary data operations to output the source data as a primary database table; performing secondary data operations, outputting secondary database tables, and using the associated data to create multi-dimensional aggregation data models and algorithms to perform aggregation analysis on the target companies; performing tertiary data operations to process the associated data in the primary database table and the secondary database table into corresponding graphical database tables; Rendering the corresponding visualization includes: determining a rendering color for each of the industry maps and each of the concept maps based on the dependency and association relationships between the industry maps and each of the concept maps, and expressing the categories and hierarchical relationships of the industry maps and each of the concept maps through the rendering color; Here, each industry map is divided based on the industry to which the target enterprise belongs, and each industry map is divided into at least three classes based on the dependency relationships of each industry map; each concept map is divided based on the concept to which the target enterprise belongs, and each concept map is divided into at least three classes based on the association relationships and / or dependency relationships of each concept map; The hierarchical rendering colors of the industry map and the concept map are associated and displayed via the panel interface, and the concept map is scrolled and displayed; A data processing and visualization method for automatically combining and displaying visualization diagrams corresponding to the target data, the value space, the value capability, the value scoring, and the overall capability, and obtaining the N-dimensional diagram of the company used to represent the overall outline of the business situation and market expression of the target company.

2. Creating a data model and algorithm, and determining the value capability conformance range and corresponding value score of the target enterprise based on the value space, and further determining each dimension score of the target enterprise's comprehensive capability, specifically: determining a value capability index, a growth capability index, an operating income growth index, and a profit growth index corresponding to the target enterprise based on the target data; Wherein, the value capability index includes the value capability conformance range and corresponding value score of the target enterprise; The method according to claim 1, characterized in that the value score for characterizing the overall capability of the target enterprise is determined through interval scoring and contrast dimensions based on four basic dimensions: value capability index, growth capability index, operating income growth index, and profit growth index.

3. Determining the value capability conformance range and corresponding value score of the target enterprise based on the value space specifically includes:

3. The method of claim 2, further comprising: determining a value capability compatibility range based on the upper and lower limits of the value space; comparing the value scores of the upper and lower limits of the value space to take the smaller score; and determining a value score corresponding to the value capability.

4. Specifically, determining the value space of the target company includes: Based on the target data, predict the target company's net profit growth rate, wherein the net profit growth rate includes a first net profit growth rate, a second net profit growth rate, and a third net profit growth rate, wherein the first net profit growth rate is the net profit growth rate for the first future year, the second net profit growth rate is the net profit growth rate for the second future year, and the third net profit growth rate is the average net profit growth rate for the next two years; determining a performance index of the target company based on the operating profit, the performance indexes including a first performance index, a second performance index, a third performance index, and a fourth performance index, wherein the first performance index is a ratio of the target company's market value to the annualized operating profit according to the current quarter's quarterly report, the second performance index is a ratio of the market value to the operating profit according to the current year's annual report, the third performance index is a ratio of the market value to the target company's operating profit for one year in the future, and the fourth performance index is a ratio of the market value to the annualized operating profit according to the predicted next quarterly report; Determining a value space for the target company based on the capability index and the net profit growth rate includes: determining a first group value index based on the first net profit growth rate, the third net profit growth rate, and the first performance index; determining a second group value index based on the first net profit growth rate, the third net profit growth rate, and the second performance index; determining a third group value index based on the second net profit growth rate, the third net profit growth rate, and the third performance index; determining a fourth group value index based on the first net profit growth rate, the third net profit growth rate, and the fourth performance index; determining an upper limit of the value space based on the first group value index, the second group value index, and the third group value index; and determining a lower limit of the value space based on the first group value index, the second group value index, the third group value index, and the fourth group value index.

5. determining a value space for the target company; and Determine an incremental market return multiple as a GPET index based on the net profit growth rate and the dynamic price-to-earnings ratio after deducting extraordinary gains and losses of the target company, wherein the GPET index is a single-stage value index and / or a split-composite accumulation value index, and if the GPET index is an accumulation value index, determine the GPET index by combining a cross-comparison pricing method based on a comparison between the split-composite and / or combined net profit growth rate and the dynamic price-to-earnings ratio after deducting extraordinary gains and losses of the target company; and determining a value space based on the GPET index.

6. After determining the value space of the target company, Obtaining goodwill data from the platform corresponding to the ratio of goodwill to assets of the target company; and modifying the value space based on the goodwill data.

7. Determine the score for each dimension of the target company's overall capability; and The method according to claim 2, further comprising: determining a growth rate forecast indicator for the target company based on the forecasted earnings per share growth rate included in the target data; re-determining the growth rate forecast indicator after updating the target data; determining a change trend in the growth potential of the target company based on the change trend in the growth rate forecast indicator; and determining a growth capability dimension score in the overall capability of the target company.

8. After determining the score for each dimension of the target company's overall capability, Re-acquiring source data of the target company at a predetermined time interval; 3. The method of claim 2, further comprising: in response to a refresh operation on the target data, using the most recently acquired target data, determining the range of change in the year-to-year forecast data of operating revenue, net profit, and earnings per share of the target company contained in the updated target data and the year-to-year forecast data of operating revenue, net profit, and earnings per share of the target company contained in the target data before the update; and determining the range of correction based on the range of change.

9. After determining the score for each dimension of the target company's overall capability, 3. The method of claim 2, further comprising: determining a target price aggregate for the target company based on the target data; determining a target space for the target company based on the target price aggregate and current prices; and maintaining a revised coverage by periodically updating the target price aggregate data.

10. 1. A data processing and visualization device, comprising: an acquisition module for acquiring source data of the target enterprise from the target data platform, storing the source data in a predetermined source data system, and arranging the source data stored in the predetermined data system into target data; a determination module that creates a data model and an algorithm, and based on the target data, predicts the target enterprise's net profit growth rate, determines the target enterprise's net profit after deducting corresponding non-recurring profits and losses as operating profit, determines the target enterprise's capability index based on the operating profit, determines the target enterprise's value space based on the capability index and the net profit growth rate, determines the target enterprise's value capability compatibility range and corresponding value score based on the value space, and further determines the target enterprise's comprehensive capability dimension score; a visualization module that combines the target data, the value space, the value ability, the value score, and the comprehensive ability to draw and render a corresponding visualization diagram based on the background data relationship in the data model and algorithm, specifically: Selecting the graphic data and combining it with a program that uses the visualization tool software to complete the automated task independently, realizing the combination of background data and front-end display on the panel interface; Drawing and rendering corresponding visualization diagrams according to the background data relationships in the data model and algorithm, including industry map, concept map, comprehensive capability diagram, value capability diagram, growth capability diagram, operating income growth diagram, profit growth diagram, enterprise N-dimensional diagram and panel interface; Here, obtaining source data of the target company from the data platform specifically involves: The target data platform includes a plurality of different data platforms; According to a plurality of preset time points, the source data of the target enterprise corresponding to each time point is obtained from each of the data platforms, specifically, the source data is obtained by a division method based on data attributes and scroll refresh time, and each data belonging to the related data in the report is determined based on the report format, and the source data is obtained from the target data platform based on the computer-written division acquisition conditions to obtain each related data; determining missing data in the source data acquired at the latest time point, retrieving the missing data from source data acquired at other time points, supplementing the source data acquired at the latest time point, and storing the source data in a preset data system as source data to be processed; Then, the source data to be processed is organized into target data; Organizing source data stored in a pre-defined data system includes: performing primary data operations to output the source data as a primary database table; performing secondary data operations, outputting secondary database tables, and using the associated data to create multi-dimensional aggregation data models and algorithms to perform aggregation analysis on the target companies; performing tertiary data operations to process the associated data in the primary database table and the secondary database table into corresponding graphical database tables; Rendering the corresponding visualization includes: determining a rendering color for each of the industry maps and each of the concept maps based on the dependency and association relationships between the industry maps and each of the concept maps, and expressing the categories and hierarchical relationships of the industry maps and each of the concept maps through the rendering color; Here, each industry map is divided based on the industry to which the target enterprise belongs, and each industry map is divided into at least three classes based on the dependency relationships of each industry map; each concept map is divided based on the concept to which the target enterprise belongs, and each concept map is divided into at least three classes based on the association relationships and / or dependency relationships of each concept map; The hierarchical rendering colors of the industry map and the concept map are associated and displayed via the panel interface, and the concept map is scrolled and displayed; A data processing and visualization device that automatically combines and displays visualization diagrams corresponding to the target data, the value space, the value capability, the value scoring, and the overall capability, thereby obtaining the N-dimensional diagram of the company that is used to represent the overall outline of the business situation and market expression of the target company.

11. A data processing and visualization medium, characterized in that it is a computer-readable storage medium on which a computer program for implementing the method according to any one of claims 1 to 9 when executed by a processor is stored.

12. A data processing and visualization device comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor is an electronic device that realizes the method according to any one of claims 1 to 9 when executing the program.

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