Data visualization method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a data visualization method and device, electronic equipment and a storage medium, belongs to the technical field of artificial intelligence, and is suitable for the field of financial science and technology and medical science and technology scenes. The method comprises the steps of obtaining target platform mirror image data in response to a data analysis request, and creating a container arrangement platform; performing mirror image deployment based on the target platform mirror image data and a container arrangement platform to obtain a target cloud platform; obtaining original business data and report data fields according to the data analysis request; performing structured processing on the obtained original business data based on the report data field to obtain candidate business data; and performing report generation on the candidate service data through the target cloud platform to obtain service report data, and performing visualization processing on the service report data. According to the embodiment of the invention, the efficiency and visibility of data analysis can be improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and is applicable to the fields of financial technology and medical technology, and in particular to a data visualization method and device, an electronic device, and a storage medium. Background Art

[0002] Data analysis typically involves analyzing and mining massive amounts of data using statistical methods, algorithmic models, and other technical means to generate reports that intuitively present patterns, trends, and interrelationships between the data, thereby providing data support for business analysis and decision-making. Data analysis technology can be applied in multiple scenarios. For example, in fintech, it can generate financial reports by extracting necessary insurance, wealth management, and financial data from massive amounts of financial business data and performing data analysis. In medical technology, it can generate medical business analysis reports by extracting necessary outpatient and inpatient data from medical business data and performing data analysis.

[0003] Currently, data analysis relies heavily on the experience of analysts. Faced with massive amounts of data, analysts need to devote considerable time and energy to data analysis, resulting in low efficiency, unintuitive data reports, and limited visibility.

[0004] Therefore, how to improve the efficiency and visibility of data analysis has become a technical problem that needs to be solved urgently. Summary of the Invention

[0005] The main purpose of the embodiments of the present application is to propose a data visualization method and device, an electronic device and a storage medium, aiming to improve the efficiency and visibility of data analysis.

[0006] To achieve the above objectives, a first aspect of an embodiment of the present application provides a data visualization method, the method comprising:

[0007] Responding to data analysis requests, obtaining target platform image data and creating a container orchestration platform;

[0008] Perform image deployment based on the target platform image data and the container orchestration platform to obtain a target cloud platform;

[0009] Obtaining original business data and report data fields according to the data analysis request;

[0010] Performing structured processing on the acquired original business data based on the report data fields to obtain candidate business data;

[0011] Generate a report for the candidate business data through the target cloud platform to obtain business report data, and perform visualization on the business report data.

[0012] In some embodiments, performing image deployment based on the target platform image data and the container orchestration platform to obtain a target cloud platform includes:

[0013] Obtaining the processing load status of the container orchestration platform;

[0014] Obtain resource requirements for target platform image data;

[0015] Allocate resources based on the resource requirements and the processing load status to obtain target platform resources;

[0016] The target platform image data is deployed on the container orchestration platform based on the target platform resources to obtain the target cloud platform.

[0017] In some embodiments, the original business requirement further includes report display parameters; and generating a report on the candidate business data through the target cloud platform to obtain business report data includes:

[0018] Performing integrity verification on the candidate business data through the target cloud platform to obtain target business data;

[0019] Adjusting the layout of the target business data based on the report display parameters to obtain display business data;

[0020] The business report data is generated based on the displayed business data.

[0021] In some embodiments, the data analysis request further includes a data calculation rule; and the structural processing of the obtained original business data based on the report data fields to obtain candidate business data includes:

[0022] Performing data cleaning on the original business data to obtain cleaned business data;

[0023] Screening the cleaning business data based on the report data fields to obtain initial business data;

[0024] The initial business data is calculated based on the data calculation rule to obtain the candidate business data.

[0025] In some embodiments, performing data cleansing on the original business data to obtain cleaned business data includes:

[0026] The original business data is screened for missing information to obtain missing business data.

[0027] Performing abnormal information detection on the original business data to obtain abnormal business data;

[0028] Data repair is performed on the missing business data and the abnormal business data in the original business data to obtain the cleaned business data.

[0029] In some embodiments, the visualizing the business report data includes:

[0030] Performing page interception on the business report data to obtain an original business report image;

[0031] Adjusting the resolution of the original business report image to obtain an initial business report image;

[0032] Adjusting the margins of the initial business report image to obtain a target business report image;

[0033] Structural encapsulation is performed based on the target business report image to obtain the business report visualization data.

[0034] In some embodiments, performing structured encapsulation based on the target business report image to obtain the business report visualization data includes:

[0035] Obtaining a preset business data display template; wherein the business data display template includes an image position index;

[0036] The target business report image is added to the business data display template based on the image position index to obtain the business report visualization data information.

[0037] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a data visualization device, comprising:

[0038] An analysis request acquisition module is used to respond to data analysis requests, obtain target platform image data, and create a container orchestration platform;

[0039] An image deployment module, configured to perform image deployment based on the target platform image data and the container orchestration platform to obtain a target cloud platform;

[0040] A business data acquisition module, configured to acquire original business data and report data fields according to the data analysis request;

[0041] a structured processing module, configured to perform structured processing on the acquired original business data based on the report data fields to obtain candidate business data;

[0042] The report visualization module is used to generate reports for the candidate business data through the target cloud platform, obtain business report data, and visualize the business report data.

[0043] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.

[0044] To achieve the above-mentioned purpose, the fourth aspect of the embodiments of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the method described in the first aspect.

[0045] The data visualization method and device, electronic device, and storage medium proposed in this application obtain target platform image data in response to data analysis requests and create a container orchestration platform, providing a basic environment for subsequent platform deployment and data processing, ensuring environmental consistency and reusability. Next, image deployment is performed based on the target platform image data and the container orchestration platform to obtain a target cloud platform, enabling rapid establishment of a cloud environment for data analysis and improving deployment efficiency. Then, based on the data analysis request, raw business data and report data fields are obtained to clarify the direction and content for data processing. The obtained raw business data is structured based on the report data fields to obtain candidate business data, making the data more standardized and facilitating subsequent analysis. Finally, reports are generated for the candidate business data via the target cloud platform to obtain business report data. The business report data is then visualized, presenting complex data in intuitive graphical form, facilitating rapid understanding of the data's connotations and assisting decision-making, thereby improving the efficiency, accuracy, and visibility of data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of the data visualization method provided in an embodiment of the present application;

[0047] Figure 2 yes Figure 1 Flowchart of step S102 in FIG.

[0048] Figure 3 yes Figure 1 Flowchart of step S104 in FIG.

[0049] Figure 4 yes Figure 3 Flowchart of step S301 in FIG.

[0050] Figure 5 is a flow chart of a data visualization method provided by another embodiment of the present application;

[0051] Figure 6 is a flow chart of a data visualization method provided by another embodiment of the present application;

[0052] Figure 7 yes Figure 6 Flowchart of step S604 in FIG.

[0053] Figure 8 is a structural diagram of a data visualization device provided in an embodiment of the present application;

[0054] Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0056] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0058] First, let’s analyze some of the terms used in this application:

[0059] Artificial intelligence (AI) is a new technical discipline that studies and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence. A branch of computer science, AI seeks to understand the essence of intelligence and create new intelligent machines that can respond in a manner similar to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, and expert systems. AI can simulate the information processes of human consciousness and thinking. It also encompasses theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, to perceive the environment, acquire knowledge, and use that knowledge to achieve optimal results.

[0060] In the computer world, an image is a complete copy of data, systems, or files. Like a clone, an image contains all the information of the original object. For example, a system image contains all the operating system files and settings, allowing for system recovery or batch deployment. A software installation image completely stores all the files required for software installation, making it easier for users to install. Images are commonly used in scenarios such as data backup, software distribution, and system deployment to ensure data security and improve deployment efficiency.

[0061] A container orchestration platform is a tool used to automate the management, scheduling, and coordination of large numbers of containers. Based on pre-set rules, a container orchestration platform allocates containers to appropriate nodes for execution, achieving efficient resource utilization. Furthermore, a container orchestration platform provides features such as container status monitoring, automatic fault recovery, and load balancing to ensure the stable operation of containerized applications. A common container orchestration platform is Kubernetes, which can manage large-scale container clusters and improve application reliability and scalability.

[0062] Data analysis typically uses statistical methods, algorithmic models, and other technical means to analyze massive amounts of data and uncover patterns, trends, and connections within the data. This creates reports that intuitively present patterns, trends, and interrelationships between the data, thereby providing data support for business analysis and decision-making. Data analysis technology can be applied in multiple scenarios. For example, in fintech, it extracts required insurance, wealth management, and financial data from vast amounts of financial business data and analyzes them to generate financial business reports. In medical technology, it extracts required outpatient and inpatient data from medical business data and analyzes them to generate medical business analysis reports.

[0063] Reports are documents or tables used to present data. Reports organize, summarize, and display various types of data, such as business data, financial data, and operational data, according to specific formats and structures. Data reports allow users to intuitively understand data distribution, trends, and comparisons. For example, a sales report can display sales figures, sales volumes, and regional distribution for different products, helping managers quickly understand sales performance and providing data support for decision-making. It is a crucial tool for data analysis and decision support.

[0064] Currently, data analysis relies heavily on the experience of analysts. Faced with massive amounts of data, analysts need to devote considerable time and energy to data analysis, resulting in low efficiency, unintuitive data reports, and limited visibility.

[0065] Based on this, embodiments of the present application provide a data visualization method and device, an electronic device, and a storage medium, aiming to improve the efficiency and visibility of data analysis.

[0066] The data visualization method and device, electronic device, and storage medium provided in the embodiments of the present application are specifically illustrated through the following embodiments. First, the data visualization method in the embodiments of the present application is described.

[0067] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0068] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0069] The data visualization method provided in the embodiment of the present application relates to the field of artificial intelligence technology. The data visualization method provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or as a server cluster or distributed system composed of multiple physical servers, or as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the data visualization method, etc., but is not limited to the above forms.

[0070] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0071] It should be noted that in each specific embodiment of the present application, when it comes to the need to perform relevant processing based on data related to the user's identity or characteristics, such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0072] Figure 1 This is an optional flow chart of the data visualization method provided in the embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S106.

[0073] Step S101, in response to a data analysis request, obtaining target platform image data and creating a container orchestration platform;

[0074] Step S102: Perform image deployment based on the target platform image data and the container orchestration platform to obtain the target cloud platform;

[0075] Step S103: obtaining original business data and report data fields according to the data analysis request;

[0076] Step S104: Structuring the original business data based on the report data fields to obtain candidate business data;

[0077] Step S105 , generating a report for the candidate business data through the target cloud platform to obtain business report data, and visualizing the business report data.

[0078] In the embodiment of the present application, steps S101 to S105 are obtained by responding to the data analysis request, obtaining the target platform image data, and creating a container orchestration platform to provide a basic environment for subsequent platform deployment and data processing, thereby ensuring the consistency and reusability of the environment. Then, based on the target platform image data and the container orchestration platform, image deployment is performed to obtain the target cloud platform, which can quickly build a cloud environment for data analysis and improve deployment efficiency. Then, according to the data analysis request, the original business data and report data fields are obtained to clarify the direction and content for data processing, and the original business data is structured based on the report data fields to obtain candidate business data, making the data more standardized and convenient for subsequent analysis. Finally, the target cloud platform generates reports for the candidate business data to obtain business report data, and the business report data is visualized, and the complex data is displayed in intuitive graphics to facilitate rapid understanding of the data connotation, assist in decision-making, and improve the efficiency, accuracy and visibility of data analysis.

[0079] In step S101 of some embodiments, the data analysis request is an explicit instruction generated by a business person or initiated by the business end, instructing the analysis and visualization of specific business data. The data analysis request includes the storage address of the business data, report data fields, data calculation rules, report display parameters, etc. The instruction can be in the form of an email or a backend data stream, but is not limited to these.

[0080] Then, in response to the data analysis request, the target platform image data that matches the data analysis request is obtained from the preset image repository, and a container orchestration platform is created.

[0081] It is understandable that current data management systems are usually deployed in the browser of the local operating system. During the installation and operation and maintenance of the data management system, the following problems exist:

[0082] (1) Browser driver versions for different operating systems are not uniform, which can easily lead to compatibility issues;

[0083] (2) Locally installed drivers require manual adaptive configuration during large-scale deployment, increasing maintenance costs;

[0084] (3) The scalability and portability are poor, making it difficult to meet the needs of dynamic resource allocation.

[0085] The approach of deploying the target platform image data in the container orchestration platform eliminates the need for adaptive adjustments for different operating systems, simplifies the deployment process, reduces the workload of manual configuration, improves the maintainability and scalability of the data management system, and helps improve the efficiency of data analysis.

[0086] It should be noted that the data management system is a system designed for data analysis, statistics, and visualization, pre-configured based on actual application scenarios. The target platform image data is the image data of the data management system and includes multiple operating system versions, such as Kylin, Windows 64-bit, and Linux 64-bit. Specifically, a container orchestration platform can be created based on the operating system of the target platform image data, or the target platform image data for the corresponding operating system can be obtained based on the container orchestration platform.

[0087] See also Figure 2 In some embodiments, step S102 may include but is not limited to steps S201 to S204:

[0088] Step S201: Obtain the processing load status of the container orchestration platform;

[0089] Step S202, obtaining resource requirements of the target platform image data;

[0090] Step S203: Allocate resources based on resource requirements and processing load status to obtain target platform resources;

[0091] Step S204: deploy the target platform image data on the container orchestration platform based on the target platform resources to obtain the target cloud platform.

[0092] In the steps S201 to S204 shown in the embodiment of the present application, by obtaining the processing load status of the container orchestration platform, the current resource utilization of the container orchestration platform can be clearly understood; then the resource requirements of the target platform image data are obtained to clarify the scale of resources required for deployment. Based on this, resources are allocated based on resource requirements and processing load status to obtain target platform resources, which can achieve reasonable and accurate resource allocation and avoid resource waste or shortage. Finally, based on the target platform resources, the target platform image data is deployed on the container orchestration platform to obtain the target cloud platform, which can ensure that the deployment process is efficient and stable, improve overall performance and resource utilization, and enhance system reliability.

[0093] In step S201 of some embodiments, the container orchestration platform is a tool for automating deployment, management and expansion of containerized applications, including at least one running node, and the processing load state of the processing resources of each running node is not the same, so it is necessary to obtain real-time load data of each node in real time to provide a basis for subsequent resource allocation. The processing resources include CPU, memory, disk I / O and other resources.

[0094] In step S202 of some embodiments, the target platform image data is a container image for building a target cloud platform, which contains a data management system and required resource requirements, i.e. the CPU, memory, storage and other resources required for running the target platform image data. By explicitly specifying the resource requirements of the target platform image data, it is ensured that resource allocation can meet the running requirements of the data management system, and performance degradation or crashes due to insufficient resources are avoided.

[0095] In step S203 of some embodiments, resource allocation is performed based on resource requirements and processing load state, and the image resource requirements and platform load are considered comprehensively to select appropriate nodes and allocate corresponding resources to obtain target platform resources, which can achieve efficient use of resources and improve the overall performance and stability of the platform.

[0096] In step S204 of some embodiments, deployment is the process of starting a container instance on the container orchestration platform according to the allocated target platform resources of the target platform image data, and the target cloud platform is a cloud platform that can provide services externally after deployment. Specifically, the image can be deployed to the specified node using the commands or tools of the container orchestration platform (such as kubectl apply of Kubernetes), which can achieve fast deployment and elastic expansion of the target cloud platform and improve development and operation efficiency.

[0097] It should be noted that the target platform image data is also created at the same time as a corresponding deployment template, and based on the deployment rules recorded in the deployment template and the target platform resources, the target platform image data is deployed on the container orchestration platform to obtain the target cloud platform, which can achieve automated deployment and expansion of the target cloud platform without the need for adaptive configuration according to the differences between operating systems and browser driver versions, saving deployment time and improving data analysis efficiency.

[0098] It can be understood that the image deployment method using the container orchestration platform can reduce the dependence on the local operating system, reduce maintenance costs, and improve the portability and flexibility of the data management system.

[0099] In step S103 of some embodiments, based on the storage address of the business data recorded in the data analysis request, the corresponding business data is obtained to obtain the original business data.

[0100] It should be noted that raw business data is the unprocessed data generated and recorded by business systems in specific application scenarios. Raw business data can be in the form of structured data (such as table data in a database), semi-structured data (such as XML and JSON files), and unstructured data (such as text).

[0101] For example, in a fintech scenario, raw business data could include insurance business data, wealth management business data, financial data, departmental operations data, etc. In a medical technology scenario, raw business data could include outpatient business data, inpatient business data, medical consumables procurement data, etc. This is not limited to these.

[0102] Next, the data analysis request is parsed to obtain the report data fields, which are used to specify the fields that require data analysis, thereby accurately filtering out the data that requires data analysis from the original business data.

[0103] In some embodiments, the data analysis request also includes data calculation rules, which are pre-set rules for performing operations on original business data, including but not limited to: summation, average, ratio calculation, etc. The specific needs need to be set according to the actual business scenario, but are not limited to this.

[0104] See also Figure 3 In some embodiments, the data analysis request further includes data calculation rules. Step S104 may include but is not limited to steps S301 to S303:

[0105] Step S301: clean the original business data to obtain cleaned business data;

[0106] Step S302: Screening the cleaned business data based on the report data fields to obtain initial business data;

[0107] Step S303 : performing data calculation on the initial business data based on the data calculation rules to obtain candidate business data.

[0108] In the steps S301 to S303 shown in the embodiment of the present application, by performing data cleaning on the original business data, missing, abnormal and other data can be removed, thereby improving the data quality. Next, the cleaned business data is screened based on the report data fields to obtain the initial business data, which can accurately extract the data related to the report data fields, reduce the interference of irrelevant data, and improve the data processing efficiency. Finally, the initial business data is calculated based on the data calculation rules to obtain candidate business data. Data that meets the business logic and report display requirements can be obtained, which can improve the accuracy of data analysis.

[0109] It is understandable that since raw business data is unprocessed data generated and recorded by the business system in a specific application scenario, it may contain errors, omissions, anomalies, etc. Therefore, it is necessary to clean the raw business data to avoid the accuracy of data analysis being affected by abnormal data.

[0110] See also Figure 4 In some embodiments, step S301 may include but is not limited to steps S401 to S403:

[0111] Step S401, screening the original business data for missing information to obtain missing business data;

[0112] Step S402: Detect abnormal information on the original business data to obtain abnormal business data;

[0113] Step S403 : Repair the missing business data and abnormal business data in the original business data to obtain cleaned business data.

[0114] In steps S401 to S403 shown in the embodiment of the present application, missing business data and abnormal business data are obtained by screening the original business data for missing information and detecting abnormal information. Then, data repair is performed on the missing business data and abnormal business data in the original business data to obtain cleaned business data, which can effectively improve the data quality, provide a reliable basis for subsequent data analysis, and ensure the accuracy of business data analysis.

[0115] In step S401 of some embodiments, missing information refers to the presence of null values ​​or unfilled fields or records in the business data. Therefore, the original business data needs to be traversed to find the portion with missing information and obtain the missing business data.

[0116] In step S402 of some embodiments, abnormal information refers to data that does not conform to normal data patterns, rules, or ranges, which may be caused by input errors, system failures, etc. Therefore, it is necessary to use preset algorithms, rules, or statistical methods to find the part containing abnormal information from the original business data to obtain abnormal business data.

[0117] For example, if the data is numerical data, you can use the data to perform box plot statistics, set the abnormal threshold to Q1-1.5×IQR or Q3+1.5×IQR, and data that exceeds the abnormal threshold is considered abnormal.

[0118] In step S403 of some embodiments, the mean or median of the data can be used to replace the missing business data and abnormal business data in the original business data; linear interpolation, polynomial interpolation, etc. can also be used to replace the missing business data and abnormal business data in the original business data; in addition, the missing business data and abnormal business data in the original business data can also be deleted to obtain cleaned business data.

[0119] In step S302 of some embodiments, data related to report requirements is selected from the cleaned business data based on the report data fields, which can reduce the amount of data, focus on key information, and improve data analysis efficiency.

[0120] For example: In the FinTech scenario: A company wants to prepare a quarterly insurance business report. Based on the fields such as "quarter", "product category", and "sales" in the report, it filters out the data for the corresponding quarter (i.e., initial business data) from the cleaned full-year insurance business data (i.e., cleaned business data).

[0121] In step S303 of some embodiments, data calculation is performed on the initial business data obtained by data screening based on data calculation rules to obtain candidate business data. This allows data that meets business data analysis requirements to be mined from the original business data, thereby improving the accuracy of data analysis.

[0122] It should be noted that the original business data and cleansed business data may be semi-structured or unstructured data. However, the initial business data and candidate business data obtained after processing are structured data, that is, the initial business data and candidate business data are presented in the form of data tables.

[0123] It should be noted that the original business requirements also include report display parameters. Report display parameters are pre-set rules for controlling report presentation, such as font, color, row and column layout, display format (such as data tables, graphic reports, etc.), etc. Specific settings need to be made according to the actual business scenario, but are not limited to this.

[0124] See also Figure 5 In some embodiments, the step of "generating a report on the candidate business data through the target cloud platform to obtain business report data" in step S105 may include but is not limited to steps S501 to S503:

[0125] Step S501: Perform integrity verification on the candidate business data through the target cloud platform to obtain the target business data;

[0126] Step S502: adjusting the layout of target business data based on the report display parameters to obtain display business data;

[0127] Step S503: Generate business report data based on the displayed business data.

[0128] In steps S501 to S503, the target cloud platform verifies the integrity of the candidate business data, ensuring data accuracy and integrity. Next, the target business data is layout-adjusted based on the report presentation parameters to obtain presentation data. Business report data is then generated based on the presentation data, presenting the data in a more rational and intuitive manner, enhancing the visibility of data analysis.

[0129] In step S501 of some embodiments, since the amount of candidate business data may be relatively large, data loading, calculation and other processing require a long time. Therefore, it is necessary to perform integrity check on the candidate business data to ensure that the candidate business data is a complete data table.

[0130] In step S502 of some embodiments, based on the rules recorded in the report display parameters, such as font, color, row and column layout, display form (such as data table, graphic report, etc.), the position and format of the target business data in the data table are adjusted to obtain displayed business data, so that the displayed business data is presented in a manner that is more in line with business needs, thereby improving the readability, visibility and comprehensibility of the data.

[0131] In step S503 of some embodiments, the business report data is data in the form of a report that is finally generated and can be used for presentation or analysis. The business report data can be obtained by saving and exporting the presentation business data.

[0132] See also Figure 6 In some embodiments, the step of "visualizing the business report data" in step S105 includes but is not limited to steps S601 to S604:

[0133] Step S601: intercepting the page of the business report data to obtain the original business report image;

[0134] Step S602: Adjust the resolution of the original business report image to obtain an initial business report image;

[0135] Step S603: Adjust the margins of the initial business report image to obtain a target business report image;

[0136] Step S604: performing structured packaging based on the target business report image to obtain business report visualization data.

[0137] In steps S601 to S604 shown in the embodiment of the present application, the business report data is captured on the page, and the report content is converted into an image form to obtain the original business report image. Then, the resolution of the original business report image is adjusted to obtain an initial business report image, which can improve the image clarity and ensure that the report details are clearly presented. Next, the margins of the initial business report image are adjusted to make the image layout more regular and appropriate, and the target business report image is obtained. Finally, structured encapsulation is performed based on the target business report image to obtain business report visualization data, which improves the visibility of the data report, facilitates storage and transmission, and improves the practicality and flexibility of the data report.

[0138] In step S601 of some embodiments, a preset screenshot tool can be used to capture the page of business report data to avoid information loss or format confusion during data storage and transmission; in addition, through page capture, direct exposure of original business data is avoided, and the risk of data being illegally copied, tampered with, or maliciously extracting sensitive information is reduced, which helps to protect the privacy and security of data.

[0139] In step S602 of some embodiments, the resolution of the original business report image can be increased or decreased according to actual business needs or a preset clarity threshold, so that the image can achieve a balance between clarity and storage and loading efficiency to meet the usage requirements in different business scenarios.

[0140] In step S603 of some embodiments, by modifying the top, bottom, left, and right margins of the initial business report image, the position of the image content on the page is made more reasonable, so that the image can be standardized and visible when printed, displayed or embedded in other documents, thereby ensuring the overall visual effect.

[0141] It should be noted that structured encapsulation is to encapsulate the target business report image according to a preset template or format to facilitate storage, transmission and display, and meet different data visualization needs.

[0142] See also Figure 7 In some embodiments, step S604 may include but is not limited to steps S701 to S702:

[0143] Step S701: obtaining a preset business data display template; wherein the business data display template includes an image position index;

[0144] Step S702 : adding the target business report image to the business data display template based on the image position index to obtain business report visualization data information.

[0145] In steps S701 to S702 shown in the embodiment of the present application, by obtaining a preset business data display template and adding the target business report image to the business data display template based on the image position index in the business data display template, the business report visualization data information is obtained, the visibility of the business report is improved, and the convenience of information acquisition and utilization is enhanced.

[0146] In step S701 of some embodiments, the preset business data display template is designed based on a specific business scenario. Using the preset business data display template to structure and encapsulate the target business report image allows for redesigning the layout each time data is displayed, saving time and effort while ensuring consistency in the presentation of business data reports in specific scenarios. The preset business data display template can be an email, web page, document, or the like.

[0147] Specifically, the business data display template includes an image location index, which indicates the placement of the target business report image. This index is typically presented as coordinates, a region identifier, or other positioning methods, ensuring that the image is accurately added to the designated location. Additionally, the business data display template may also include a text location index, which indicates the placement of target explanatory text. This index is typically presented as coordinates, a region identifier, or other positioning methods. The target explanatory text is information used to explain the target business report image.

[0148] In step S702 of some embodiments, the specific location where the image should be placed is determined based on the image position index defined in the template, and the target business report image is inserted into the specified location of the business data display template, making the display of the data report more intuitive and enhancing the visibility of data analysis.

[0149] In one embodiment, the business data display template is an email. The target business report image is added to the business data display template to obtain business report visualization data information, and the business report visualization data information is sent to the business personnel or person in charge who initiated the data analysis request, thereby improving the convenience of data analysis and the user experience.

[0150] In some embodiments, when the target cloud platform has been created, when a data analysis request is received, the implementation method shown in steps S103 to S105 can be directly executed without repeatedly deploying the target cloud platform, which can improve the efficiency of data analysis.

[0151] See also Figure 8 The present application also provides a data visualization device that can implement the above-mentioned data visualization method. The device includes:

[0152] Analysis request acquisition module 801, used to respond to data analysis requests, obtain target platform image data, and create a container orchestration platform;

[0153] Image deployment module 802, used to deploy images based on the target platform image data and the container orchestration platform to obtain the target cloud platform;

[0154] Business data acquisition module 803, used to obtain original business data and report data fields according to data analysis request;

[0155] The structured processing module 804 is used to perform structured processing on the original business data based on the report data fields to obtain candidate business data;

[0156] The report visualization module 805 is used to generate reports for candidate business data through the target cloud platform, obtain business report data, and visualize the business report data.

[0157] The specific implementation of the data visualization device is basically the same as the specific embodiment of the above-mentioned data visualization method, and will not be repeated here.

[0158] The present application also provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned data visualization method when executing the computer program. The electronic device can be any smart terminal including a tablet computer, an in-vehicle computer, or the like.

[0159] See also Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is shown. The electronic device includes:

[0160] The processor 901 can be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0161] The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program codes are stored in the memory 902 and are called by the processor 901 to execute the data visualization method of the embodiments of this application.

[0162] Input / output interface 903, used to implement information input and output;

[0163] Communication interface 904, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);

[0164] Bus 905 , which transmits information between various components of the device (e.g., processor 901 , memory 902 , input / output interface 903 , and communication interface 904 );

[0165] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0166] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned data visualization method is implemented.

[0167] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0168] The data visualization method and device, electronic device and storage medium provided in the embodiments of the present application obtain target platform image data and create a container orchestration platform in response to a data analysis request, thereby providing a basic environment for subsequent platform deployment and data processing and ensuring the consistency and reusability of the environment. Then, based on the target platform image data and the container orchestration platform, image deployment is performed to obtain a target cloud platform, which can quickly build a cloud environment for data analysis and improve deployment efficiency. Then, according to the data analysis request, the original business data and report data fields are obtained to clarify the direction and content for data processing, and the original business data is structured based on the report data fields to obtain candidate business data, making the data more standardized and convenient for subsequent analysis. Finally, the target cloud platform generates reports for the candidate business data to obtain business report data, and the business report data is visualized, and the complex data is displayed in intuitive graphics, which is convenient for quickly understanding the data connotation, assisting decision-making, and improving the efficiency, accuracy and visibility of data analysis.

[0169] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0170] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0171] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0172] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0173] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0174] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0175] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0176] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0177] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0178] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0179] The non-Company software tools or components appearing in the embodiments of this application are for illustrative purposes only and do not represent actual use.

[0180] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A data visualization method, characterized in that: The method comprises: Responding to data analysis requests, obtaining target platform image data and creating a container orchestration platform; Perform image deployment based on the target platform image data and the container orchestration platform to obtain a target cloud platform; Obtaining original business data and report data fields according to the data analysis request; Performing structured processing on the acquired original business data based on the report data fields to obtain candidate business data; Generate a report for the candidate business data through the target cloud platform to obtain business report data, and perform visualization on the business report data.

2. The method according to claim 1, characterized in that The performing image deployment based on the target platform image data and the container orchestration platform to obtain a target cloud platform includes: Obtaining the processing load status of the container orchestration platform; Obtain resource requirements for target platform image data; Allocate resources based on the resource requirements and the processing load status to obtain target platform resources; The target platform image data is deployed on the container orchestration platform based on the target platform resources to obtain the target cloud platform.

3. The method according to claim 1, characterized in that The original business requirements also include report display parameters; Generating a report on the candidate business data through the target cloud platform to obtain business report data includes: Performing integrity verification on the candidate business data through the target cloud platform to obtain target business data; Adjusting the layout of the target business data based on the report display parameters to obtain display business data; The business report data is generated based on the displayed business data.

4. The method according to claim 1, wherein The data analysis request further includes data calculation rules; the structured processing of the acquired original business data based on the report data fields to obtain candidate business data includes: Performing data cleaning on the original business data to obtain cleaned business data; Screening the cleaning business data based on the report data fields to obtain initial business data; The initial business data is calculated based on the data calculation rule to obtain the candidate business data.

5. The method according to claim 4, characterized in that The step of performing data cleaning on the original business data to obtain cleaned business data includes: The original business data is screened for missing information to obtain missing business data. Performing abnormal information detection on the original business data to obtain abnormal business data; Data repair is performed on the missing business data and the abnormal business data in the original business data to obtain the cleaned business data.

6. The method according to any one of claims 1 to 5, characterized in that The visual processing of the business report data includes: Performing page interception on the business report data to obtain an original business report image; Adjusting the resolution of the original business report image to obtain an initial business report image; Adjusting the margins of the initial business report image to obtain a target business report image; Structural encapsulation is performed based on the target business report image to obtain the business report visualization data.

7. The method according to claim 6, characterized in that The step of performing structural encapsulation based on the target business report image to obtain the business report visualization data includes: Obtaining a preset business data display template; wherein the business data display template includes an image position index; The target business report image is added to the business data display template based on the image position index to obtain the business report visualization data information.

8. A data visualization device, characterized in that: The device comprises: An analysis request acquisition module is used to respond to data analysis requests, obtain target platform image data, and create a container orchestration platform; An image deployment module, configured to perform image deployment based on the target platform image data and the container orchestration platform to obtain a target cloud platform; A business data acquisition module, configured to acquire original business data and report data fields according to the data analysis request; a structured processing module, configured to perform structured processing on the acquired original business data based on the report data fields to obtain candidate business data; The report visualization module is used to generate reports for the candidate business data through the target cloud platform, obtain business report data, and visualize the business report data.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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