Data visualization processing method and system

Abstract

The invention relates to the technical field of data visualization processing, and provides a data visualization processing method and system, and the method comprises the steps: obtaining an internal data source of an enterprise, and constructing a data warehouse; docking the data warehouse with a preset technical architecture to generate a mobile BI visual platform; the mobile BI visualization platform is divided according to function modules, and a visualization data mode is adapted according to the function modules; and according to the visual data mode, when an access request of a user is received, outputting corresponding visual data. The customizability is high, and a visual data mode can be self-defined according to different business requirements and data characteristics so as to formulate a visual display scheme which is most suitable for a user and has the highest popularity; the method has good expansibility, and can realize visualization processing of data by docking different data sources and preset technical architectures.

Description

Technical Field

[0001] The present invention relates to the field of data visualization processing, and in particular to a data visualization processing method and system. Background Art

[0002] At present, all business operations of enterprises are processed in one stop through digital terminals. With the expansion and diversification of business, enterprises have accumulated a large amount of business data, which covers multiple business areas such as sales records, procurement information, financial statements, production data, etc. These data are not only large in volume, but also distributed in various independent information systems within the enterprise, such as CRM, ERP, SCM, etc. The data storage format and structure of each system are different. Some use relational databases, while others use unstructured data storage methods.

[0003] The dispersion and heterogeneity of this data have set up many obstacles for enterprises to conduct effective data integration and analysis. First, it is difficult for data between different systems to communicate directly, and complex conversion and mapping processes are required to achieve data unification. Secondly, due to differences in data formats and structures, enterprises often face problems of inconsistent, missing or incorrect data when trying to merge and analyze data. Furthermore, although traditional data analysis and reporting tools, such as Excel, are powerful, they often seem to be unable to cope with such large and complex data sets, resulting in low analysis efficiency and difficulty in achieving advanced data visualization effects.

[0004] In the prior art, the patent document with application number CN201810935431.5 proposes a business data visualization method, which visualizes the page visual effects and business data in the same image, solving the problems existing in the prior art that the product page structure, atmosphere, content and other information are separated from the business data, and there is no automated identification and retention plan. Summary of the invention

[0005] The present invention proposes a data visualization processing method and system for solving the problem in the prior art that information such as product page structure, atmosphere and content are separated from business data and there is no automatic identification and retention solution.

[0006] In a first aspect, the present invention proposes a data visualization processing method, comprising:

[0007] Obtain internal enterprise data sources and build data warehouses;

[0008] Connect the data warehouse with the preset technical architecture to generate a mobile BI visualization platform;

[0009] Divide the mobile BI visualization platform into functional modules and adapt the visualization data model according to the functional modules; the visualization data model is used to develop the most popular visualization display plan;

[0010] According to the visualization data mode, when receiving the user's access request, the corresponding visualization data is output.

[0011] Furthermore, the acquisition of internal enterprise data sources and construction of a data warehouse includes:

[0012] Obtain data types and business status information of multiple business data of one or more enterprise business nodes in any enterprise business,

[0013] For each enterprise business, based on the business status information, according to each business data type of the enterprise business node, calculate the execution rate of the enterprise business through each business node, and the calling speed of calling the enterprise business data in one or more enterprise internal data sources;

[0014] For more than one internal data source of an enterprise, a data warehouse is established by generating the execution rates of enterprise business nodes corresponding to different enterprise businesses during the business execution process.

[0015] Furthermore, the acquisition of the enterprise internal data source and the construction of the data warehouse also include:

[0016] Determine the enterprise business information based on the enterprise's internal data sources;

[0017] Determine the required data and candidate business indicator data for processing the business of the enterprise based on the business data of the enterprise;

[0018] Among them, demand data refers to the data demand information of enterprise business information during the execution process;

[0019] The business indicator candidate data represents a set of indicators among multiple indicators for evaluating the execution quality of the enterprise business during the execution process;

[0020] According to the business correlation between the business indicators corresponding to the business indicator candidate data and the business requirements shown by the demand data,

[0021] According to the business relevance, the visualization expectation corresponding to any business indicator is extracted from multiple business indicator candidate data.

[0022] Furthermore, the preset technical architecture is a topological framework structure of an SQI interface, a business BI interface, and a business SQI statement for business process conversion that describes the enterprise business port based on a BI visualization tool.

[0023] Furthermore, the docking of the data warehouse with the preset technical architecture includes:

[0024] According to the preset technical architecture, determine the service port and obtain the service characteristics corresponding to different service ports;

[0025] Extract the business type characteristics of the corresponding enterprise business on the data warehouse from the business characteristics;

[0026] The business type features are cross-convolutionally fused to determine the candidate storage addresses of the enterprise business in the data warehouse and the response isolation channels of the candidate storage addresses;

[0027] The data warehouse and business port are connected through the response isolation channel, and data transmission is performed in the preset safe working mode.

[0028] Furthermore, under the preset security model:

[0029] Determine the data security level through the business port and set up encryption requests for response isolation channels;

[0030] When the data warehouse receives the encryption application, it generates a security encryption matrix for the business data to be interacted with;

[0031] The weight of each interactive service item is calculated through the security encryption matrix, the weight coefficient of each interactive service item is determined, and the weight coefficient of each interactive service item is normalized to an interval, and the corresponding encryption request feature is generated according to the positive correlation between the weight coefficient and the security level;

[0032] Obtain the encryption strength, key length, encryption complexity, and encryption tendency of different preset encryption algorithms, and match them one by one with the encryption request characteristics to determine the optimal encryption algorithm.

[0033] Further, the adapting of the visualization data mode according to the functional module includes:

[0034] Obtain the visualization conversion function and historical visualization display data of the mobile BI visualization platform;

[0035] Generate visualization function trends of enterprise business and business data features corresponding to the visualization function trends based on visualization display data;

[0036] Generate a visualization call network of enterprise business data based on business data characteristics, visualization function tendencies and visualization conversion functions;

[0037] According to the visualization call network, when receiving the visualization request from the user, the visualization display popularity calculation is performed based on the visualized business data and business types;

[0038] Based on the visualization popularity calculation results, determine the visualization display plan for the enterprise business data and convert it into a visualization data model.

[0039] Furthermore, when receiving the access request from the user, the method further includes:

[0040] By receiving a request for visualization of any enterprise business data from any mobile terminal registered on the mobile network;

[0041] Based on the access control policy associated with the requested enterprise business data, determining whether the mobile terminal has a visualization display privilege in the data warehouse;

[0042] In response to determining that the mobile terminal has the visualization display privilege, identifying that the mobile terminal will perform a visualization conversion function call authorization to the mobile BI visualization platform when executing the visualization display privilege;

[0043] According to the calling authorization of the visualization conversion function, the access time in the access control policy is adjusted, and a display approval message is sent to the mobile terminal.

[0044] Furthermore, the generating of the mobile BI visualization platform also includes:

[0045] According to the preset technical architecture, the supervision test files are respectively set, and when there is an access request, the supervision test files are read and parsed to obtain the parsed first test data;

[0046] Get the data format parameters set for the supervision test file in the mobile BI visualization platform;

[0047] Performing format conversion on the first test data according to the data format parameter to obtain second test data;

[0048] Determine a plurality of functional test cases through the second test data;

[0049] Determine whether multiple functional test cases conform to the preset visualization display strategy, and start the corresponding visualization conversion function when the functional test cases conform to the preset visualization display strategy.

[0050] In a second aspect, a data visualization processing system includes:

[0051] Data warehouse module: used to obtain internal enterprise data sources and build data warehouses;

[0052] Mobile BI visualization platform building module: used to connect the data warehouse with the preset technical architecture to generate a mobile BI visualization platform;

[0053] Visualization conversion module: used to divide the mobile BI visualization platform into functional modules and adapt the visualization data mode according to the functional modules; the visualization data mode is used to formulate the most popular visualization display plan;

[0054] Visualization output module: used to output corresponding visualization data according to the visualization data mode when receiving the user's access request.

[0055] The beneficial effects of the present invention are:

[0056] It is highly customizable and can customize the visualization data mode according to different business needs and data characteristics to develop the most suitable and popular visualization display plan;

[0057] It has good scalability and can realize data visualization by connecting to different data sources and preset technical architectures;

[0058] It can quickly respond to user access requests. According to the visualization data mode, when receiving the user's access request, it can quickly output the corresponding visualization data to improve the user experience.

[0059] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0060] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0062] Figure 1 A method flow chart of a data visualization processing method in an embodiment of the present invention;

[0063] Figure 2 A system composition diagram of a data visualization processing system in an embodiment of the present invention;

[0064] Figure 3 This is a display diagram of a newly added sales order in an embodiment of the present invention;

[0065] Figure 4 A display diagram for selecting goods in an embodiment of the present invention;

[0066] Figure 5This is a function menu display diagram for visual analysis and display in an embodiment of the present invention;

[0067] Figure 6 This is a visualization diagram of the sales data of the previous day in an embodiment of the present invention;

[0068] Figure 7 A sales trend statistical chart in an embodiment of the present invention;

[0069] Figure 8 This is a data display diagram of different commodities under different selection conditions in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0071] like Figure 1 As shown, this embodiment provides a data visualization processing method, including:

[0072] Obtain internal enterprise data sources and build data warehouses;

[0073] Connect the data warehouse with the preset technical architecture to generate a mobile BI visualization platform;

[0074] Divide the mobile BI visualization platform into functional modules and adapt the visualization data model according to the functional modules; the visualization data model is used to develop the most popular visualization display plan;

[0075] According to the visualization data mode, when receiving the user's access request, the corresponding visualization data is output.

[0076] The principle of the above technical solution is:

[0077] In the specific implementation process, the internal data source of the enterprise is obtained to build a data warehouse. The data warehouse collects various data from various departments within the enterprise or external channels, and integrates these data into a unified warehouse to generate a multi-data source docking platform and a massive data storage platform integrated with the database. The data warehouse is docked with the preset technical architecture to generate a mobile BI visualization platform, which is to dock the data warehouse with the preset technical architecture to generate a mobile BI visualization platform. The mobile BI visualization platform can be based on a web page or an APP, can be used on any device, and can be accessed anytime and anywhere. The mobile BI visualization platform is divided according to functional modules, and the visualization data mode is adapted according to the functional modules. The mobile BI visualization platform integrates a variety of business processing functions. In the implementation process, the mobile BI visualization platform is divided according to different functional modules, and different visualization data modes are adapted according to these functional modules. In this case, different data visualization display solutions are provided for different users. The data source identifier of the display identifier of the same data in different visualization data modes is consistent, but different display modes and display forms, such as text and image, have the same data source identifier but inconsistent data display form identifier when displaying in two different modes. According to the visualization data mode, when receiving the user's access request, the corresponding visualization data is output. This is when the user requests to access the data, according to the corresponding visualization data mode, the corresponding visualization data is quickly output. This ensures that the user can quickly obtain the required information and improves the user experience. When outputting visualization data, the visualization function can be automatically set according to different types, such as the attached Figure 5 shown.

[0078] The beneficial effects of the above technical solution are:

[0079] It is highly customizable and can customize the visualization data mode according to different business needs and data characteristics to develop the most suitable and popular visualization display plan;

[0080] It has good scalability and can realize data visualization by connecting to different data sources and preset technical architectures;

[0081] It can quickly respond to user access requests. According to the visualization data mode, when receiving the user's access request, it can quickly output the corresponding visualization data to improve the user experience.

[0082] As an embodiment of the present invention, the step of obtaining an internal data source of an enterprise and building a data warehouse includes:

[0083] According to the internal data source of the enterprise, data types and business status information of multiple business data of more than one enterprise business node of the enterprise business are obtained;

[0084] For the enterprise services and service status information, respectively, according to each service data type of the enterprise service node, calculate the execution rate of the enterprise services through each service node, and the calling speed of calling the enterprise service data in one or more enterprise internal data sources;

[0085] For more than one internal data source of an enterprise, a data warehouse is established by generating the execution rates of enterprise business nodes corresponding to different enterprise businesses during the business execution process.

[0086] The principle of the above technical solution is:

[0087] In the specific implementation process, the data types and business status information of multiple business data of more than one business node in the enterprise business are obtained according to the internal data source of the enterprise. In actual business operations, such as sales business, relevant data can be extracted from various business systems of the enterprise, and these data can be classified and divided into. For example: in the sales process, there is a new sales order business, such as the attached Figure 3 As shown, and the commodity selection task is Figure 4 .

[0088] For the enterprise business and business status information, the execution rate of the enterprise business through each business node and the calling speed of calling the enterprise business data in one or more internal data sources of the enterprise are calculated according to each business data type of the enterprise business node. Through the above steps, the data of each business node can be converted into indicators such as execution rate and calling speed, and then the operation status of the enterprise on different business nodes can be reflected according to different indicators.

[0089] For more than one internal data source of an enterprise, the execution rate of the enterprise business nodes corresponding to different enterprise businesses in the business execution process is generated to establish a data warehouse. These generated execution rate and call speed indicators are used as new data and put into the corresponding internal data source to form a complete enterprise-level data warehouse. When receiving a user's access request, according to the user's access request, combined with the above data warehouse, a corresponding user interface is generated to achieve data visualization display. This makes it easier for users to better understand and analyze the data of the enterprise business.

[0090] The technical effects of the above technical solution are:

[0091] The present invention can integrate all data in an enterprise by building a data warehouse, thereby realizing one-stop analysis and call of business data.

[0092] As an embodiment of the present invention, the step of obtaining the internal data source of the enterprise and building the data warehouse further includes:

[0093] Determine the enterprise business information based on the enterprise's internal data sources;

[0094] Determine the required data and candidate business indicator data for processing the business of the enterprise based on the business data of the enterprise;

[0095] Among them, demand data refers to the data demand information of enterprise business information during the execution process;

[0096] The business indicator candidate data represents a set of indicators among multiple indicators for evaluating the execution quality of the enterprise business during the execution process;

[0097] According to the business correlation between the business indicators corresponding to the business indicator candidate data and the business requirements shown by the demand data,

[0098] According to the business relevance, the visualization expectation corresponding to any business indicator is extracted from multiple business indicator candidate data.

[0099] The technical principle of the above technical solution is:

[0100] During the specific implementation process, determine the business information of the enterprise: through in-depth research on the internal data sources of the enterprise, determine the overall operation of the corresponding business of the enterprise, including information such as product services, customer groups, and competitors. Determine the demand data and business indicator candidate data for processing the business of the enterprise: demand data usually includes various raw data generated by the enterprise in daily operations, such as sales records, production reports, etc. The candidate data of business indicators are important indicators for evaluating the operation of the enterprise, such as customer satisfaction, product reputation, sales, etc. According to the candidate data of business indicators and demand data, find out the appropriate visualization expectations: according to the business correlation between the candidate data of business indicators and the demand data, find the indicators that can most intuitively reflect the business status of the enterprise, so as to provide corresponding indicator parameters for data visualization. Finally, in the process of building a data warehouse, all data needs to be sorted, cleaned and formatted to meet the acceptance standards of the mobile BI visualization platform.

[0101] The technical effects of the above technical solution are:

[0102] The present invention divides the enterprise business data into demand data and business indicator candidate data before resuming the data warehouse, so as to determine the business relevance and business indicator data in the quality assessment of the enterprise business, so that when visualizing, the visualized expected data corresponds to direct indicator data.

[0103] As an embodiment of the present invention, the preset technical architecture is a topological framework structure of the SQI interface, the business BI interface, and the business SQI statement for business process conversion that describes the enterprise business port according to the BI visualization tool. The SQI interface is a channel for interaction between the BI visualization tool and the data source, and is also a channel for interaction between the mobile BI visualization platform and the data source. The SQI interface realizes data exchange and conversion between the mobile BI visualization platform and the data source through preset rules and protocols. The business BI interface is the user interface of the mobile BI visualization platform, and users can view and operate the visualized data through this interface. The design and layout of the business BI interface are generated according to the template predefined by the BI tool, so that all users can have the same user experience when using the mobile BI visualization platform. The business SQI statement for business process conversion is a set of statements that converts data from the data source into a visual data model. These statements are usually optimized for specific data sources and visualization requirements, and data conversion and modeling are realized through preset grammatical and semantic rules. These statement sets can be easily loaded and used without manual writing every time. The topological framework structure of the preset technical architecture is designed to achieve efficient collaboration and collaborative work of these components. Through predefined relationships and connection methods, the SQI interface, business BI interface and business SQI statements of business process conversion can coordinate with each other to jointly achieve the goal of data visualization processing.

[0104] As an embodiment of the present invention, the step of connecting the data warehouse to the preset technical architecture includes:

[0105] According to the preset technical architecture, determine the service port and obtain the service characteristics corresponding to different service ports;

[0106] Extract the business type characteristics of the corresponding enterprise business on the data warehouse from the business characteristics;

[0107] The business type features are cross-convolutionally fused to determine the candidate storage addresses of the enterprise business in the data warehouse and the response isolation channels of the candidate storage addresses;

[0108] The data warehouse and business port are connected through the response isolation channel, and data transmission is performed in the preset safe working mode.

[0109] The principle of the above technical solution is:

[0110] In the specific implementation process, according to the preset technical architecture, the business port is determined, and the business features corresponding to different business ports are obtained. According to the requirements of the preset technical architecture, the business features corresponding to each business port are determined, and the business attributes and requirements of each business port are described through the business features. The business type features of the corresponding enterprise business on the data warehouse are extracted from the business features. After obtaining the business features corresponding to each business port, the business type features related to the overall business of the enterprise are extracted. These features can determine the overall business structure and requirements of the enterprise. The response isolation channel of the candidate storage address is to determine the candidate storage address and candidate storage address of each enterprise business in the data warehouse by cross-convolution fusion processing of the business type features, and calculate the corresponding response isolation channel. These addresses and channels can realize more fine-grained database design and query solutions, and can also improve data visualization and query efficiency. The data warehouse and the business port are connected through the response isolation channel, and data transmission is performed when the preset security working mode is set. The data warehouse and the business port are connected, and the security mode is set and controlled during the connection process to ensure the security and integrity of the data. After the connection is completed, data transfer can be performed in the preset safe working mode to transfer data from the data warehouse to the mobile BI visualization platform for users to perform visualization and analysis.

[0111] The beneficial effects of the above technical solution are:

[0112] The present invention can set up corresponding isolation channels to transmit business data in a preset security mode to ensure the security of data transmission.

[0113] As an embodiment of the present invention, under the preset security model:

[0114] Determine the data security level through the business port and set up encryption requests for response isolation channels;

[0115] When the data warehouse receives the encryption application, it generates a security encryption matrix for the business data to be interacted with;

[0116] The weight of each interactive service item is calculated through the security encryption matrix, the weight coefficient of each interactive service item is determined, and the weight coefficient of each interactive service item is normalized to an interval, and the corresponding encryption request feature is generated according to the positive correlation between the weight coefficient and the security level;

[0117] Obtain the encryption strength, key length, encryption complexity, and encryption tendency of different preset encryption algorithms, and match them one by one with the encryption request characteristics to determine the optimal encryption algorithm.

[0118] The principle of the above technical solution is:

[0119] In the specific implementation process, the data security level is determined through the business port, and the encryption application of the response isolation channel is set. The security level of each data object needs to be determined according to the business type characteristics and the security requirements of the enterprise data. Then, the corresponding response isolation channel is set, and the corresponding encryption application is set according to the requirements of the business port. This ensures that only authorized users and devices can access and process sensitive data. When the data warehouse receives the encryption application, a secure encryption matrix for the interactive business data is generated. The original plaintext of the data object is converted into a secure encryption matrix to protect the confidentiality of the data. In the implementation, different preset encryption algorithms are used, combined with factors such as encryption strength, key length, encryption complexity and encryption tendency, to generate a suitable encryption matrix. The weight of each interactive business item is calculated through the secure encryption matrix, the weight coefficient of each interactive business item is determined, and the weight coefficient of each interactive business item is normalized to the interval, and the corresponding encryption request feature is generated according to the positive correlation between the weight coefficient and the security level. In the specific implementation, the weight of each interactive business item needs to be calculated according to the business type characteristics and the characteristics of the enterprise data. Then, the weight coefficient is normalized so that it falls within the predetermined interval. Next, according to the positive correlation between the weight coefficient and the security level, the corresponding encryption request feature is generated. The encryption strength, key length, encryption complexity and encryption tendency of different preset encryption algorithms are obtained, and they are matched one by one with the encryption request features to determine the optimal encryption algorithm. The encryption algorithm that best matches the encryption request feature is found to ensure the efficiency and security of encryption. A series of encryption algorithms are pre-set, and then these algorithms are matched with the encryption request features to find the optimal encryption algorithm.

[0120] The beneficial effects of the above technical solution are:

[0121] The present invention can achieve all-round encryption by setting a preset security mode, passing sensitive data and data to be encrypted through a security encryption matrix, configuring the closest encryption algorithm.

[0122] As an embodiment of the present invention, the method of adapting the visualization data mode according to the functional module includes:

[0123] Obtain the visualization conversion function and historical visualization display data of the mobile BI visualization platform;

[0124] Generate visualization function trends of enterprise business and business data features corresponding to the visualization function trends based on visualization display data;

[0125] Generate a visualization call network of enterprise business data based on business data characteristics, visualization function tendencies and visualization conversion functions;

[0126] According to the visualization call network, when receiving the visualization request from the user, the visualization display popularity calculation is performed based on the visualized business data and business types;

[0127] Based on the visualization popularity calculation results, determine the visualization display plan for the enterprise business data and convert it into a visualization data model.

[0128] The principle of the above technical solution is:

[0129] In the specific implementation process, obtain the visualization conversion function and historical visualization display data of the mobile BI visualization platform. Figure 8 , and display different visualization data. This is to obtain the visualization conversion function and historical visualization display data possessed by the mobile BI visualization platform. Based on the visualization display data, generate the visualization function tendency of the enterprise business and the business data characteristics corresponding to the visualization function tendency. This generates the visualization function tendency of the enterprise business and the corresponding business data characteristics based on the visualization display data. Better understand and grasp the key points and directions of data visualization, and determine the subsequent visualization data mode. Generate a visualization call network for enterprise business data based on business data characteristics, visualization function tendency and visualization conversion function. Generate a visualization call network for enterprise business data based on the above three factors. The visualization call network can generate a visualization display scheme when receiving a visualization request. According to the visualization call network, when receiving a visualization request, the visualization display popularity is calculated based on the visualized business data and business types. This is to use the visualization call network generated previously, and after receiving the visualization request, the visualization display popularity is calculated. According to different business types and the needs of visualization display, the visualization display scheme is dynamically adjusted. According to the visualization popularity calculation results, the visualization display scheme of the enterprise business data is determined and converted into a visualization data mode. In the final presentation stage, based on all the previous work and the results of the visualization popularity calculation, the visualization display scheme that best matches the enterprise business data will be determined and converted into a visualization data model, such as Figure 6 , to visualize the previous day's revenue. And Figure 7 , to visualize sales trends.

[0130] The beneficial effects of the above technical solution are:

[0131] The present invention configures the visualization data mode through the functional module, and determines the most popular visualization display schemes for different data according to the visualization popularity, and performs data display, so that the display results are of higher quality acceptable to customers.

[0132] As an embodiment of the present invention, when receiving an access request from a user, the method further includes:

[0133] By receiving a request for visualization of any enterprise business data from any mobile terminal registered on the mobile network;

[0134] Based on the access control policy associated with the requested enterprise business data, determining whether the mobile terminal has a visualization display privilege in the data warehouse;

[0135] In response to determining that the mobile terminal has the visualization display privilege, identifying that the mobile terminal will perform a visualization conversion function call authorization to the mobile BI visualization platform when executing the visualization display privilege;

[0136] According to the calling authorization of the visualization conversion function, the access time in the access control policy is adjusted, and a display approval message is sent to the mobile terminal.

[0137] The principle of the above technical solution is:

[0138] In the specific implementation process, mobile network communication technology is used to allow users to send data requests through mobile terminals (such as smartphones, tablets, etc.). It mainly applies mobile network protocols and the application programming interface (API) of mobile devices. Access control policy is a security mechanism used to determine which users or devices have access to specific data resources. In the specific implementation, there will be user authentication, role permission management, and access permission configuration. When a data request is received, the requester's permissions are verified according to the predefined access control policy. The data warehouse is a central repository for storing enterprise business data. The visual display privilege judgment process involves database query and permission check to determine whether the requester has access privileges to specific data. In the specific implementation, it is achieved by querying the user permission table or access control list (ACL). After determining that the mobile terminal has the visual display privilege, the system needs to authorize the mobile terminal to call the visual conversion function. In the specific implementation, authorization mechanisms such as token generation and API key management are adopted to ensure that only authorized terminals can perform specific operations. The adjustment of access time is a dynamic modification of the access control policy to adapt to the needs of specific users. In the specific implementation, the user's access time limit is updated through the interface call of the policy management system. Once the access rights are confirmed and adjusted, the system sends an approval message to the user's mobile terminal via the mobile network. This involves push messaging technologies such as SMS, in-app notifications or WebSocket communication.

[0139] The beneficial effects of the above technical solution are:

[0140] The present invention uses a mobile network to call authorization and visualization privileges when performing visualization display. The visualization privileges are preset, and the visualization access request process can be quickly displayed.

[0141] As an embodiment of the present invention, generating a mobile BI visualization platform further includes:

[0142] According to the preset technical architecture, the supervision test files are respectively set, and when there is an access request, the supervision test files are read and parsed to obtain the parsed first test data;

[0143] Get the data format parameters set for the supervision test file in the mobile BI visualization platform;

[0144] Performing format conversion on the first test data according to the data format parameter to obtain second test data;

[0145] Determine a plurality of functional test cases through the second test data;

[0146] Determine whether multiple functional test cases conform to the preset visualization display strategy, and start the corresponding visualization conversion function when the functional test cases conform to the preset visualization display strategy.

[0147] The principle of the above technical solution is:

[0148] In specific implementation, the supervision test files are designed according to the preset technical architecture to verify whether the data visualization processing method can be executed correctly. These files contain data samples for testing and expected processing results. When there is an access request, the system reads the supervision test file, parses its content, and extracts the first test data. This usually involves file I / O operations and data processing logic. The mobile BI visualization platform pre-sets data format parameters, which define how to convert input data into the format required for visualization. These parameters are obtained to ensure that subsequent data format conversion can be executed correctly. By applying the data format parameters, the first test data is converted to the second test data. This process may include operations such as data cleaning, formatting, and type conversion. Based on the converted second test data, multiple functional test cases are generated. These cases are designed to test whether the visualization conversion function can work as expected. The system evaluates the functional test cases according to the preset visualization display strategy. If the test case complies with the strategy, it indicates that the visualization conversion function can be executed correctly.

[0149] The beneficial effects of the above technical solution are:

[0150] The present invention can set test data during data access, determine corresponding visualization display strategies through test data and functional test cases, and realize visualization conversion.

[0151] In a second aspect, a data visualization processing system includes:

[0152] Data warehouse module: used to obtain internal enterprise data sources and build data warehouses;

[0153] Mobile BI visualization platform building module: used to connect the data warehouse with the preset technical architecture to generate a mobile BI visualization platform;

[0154] Visualization conversion module: used to divide the mobile BI visualization platform into functional modules and adapt the visualization data mode according to the functional modules; the visualization data mode is used to formulate the most popular visualization display plan;

[0155] Visualization output module: used to output corresponding visualization data according to the visualization data mode when receiving the user's access request.

[0156] like Figure 2 As shown, in the specific implementation process, the internal data source of the enterprise is obtained and a data warehouse is built. This is to collect various data from various departments within the enterprise or external channels, and integrate these data into a unified warehouse for subsequent data processing and management. The data warehouse is connected with the preset technical architecture to generate a mobile BI visualization platform. This is to connect the data warehouse with the preset technical architecture to generate a mobile BI visualization platform. This platform can be based on a web page or an APP, can be used on any device, and can be accessed anytime and anywhere. The mobile BI visualization platform is divided according to functional modules, and the visualization data mode is adapted according to the functional modules. This is to divide the mobile BI visualization platform according to different functional modules, and adapt different visualization data modes according to these functional modules. In this way, different data visualization display solutions can be provided for different users. According to the visualization data mode, when receiving the user's access request, the corresponding visualization data is output. This is when the user requests to access the data, the corresponding visualization data is quickly output according to the corresponding visualization data mode. In this way, it can be ensured that users can quickly obtain the required information and improve the user experience.

[0157] The beneficial effects of the above technical solution are:

[0158] It is highly customizable and can customize the visualization data mode according to different business needs and data characteristics to develop the most suitable and popular visualization display plan;

[0159] It has good scalability and can realize data visualization by connecting to different data sources and preset technical architectures;

[0160] It can quickly respond to user access requests. According to the visualization data mode, when receiving the user's access request, it can quickly output the corresponding visualization data to improve the user experience.

[0161] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention belong to the scope of the present invention and its equivalent technologies, the present invention is also intended to include these changes and variations.

Claims

1. A data visualization processing method, characterized in that: include: Obtain internal enterprise data sources and build data warehouses; Connect the data warehouse with the preset technical architecture to generate a mobile BI visualization platform; Divide the mobile BI visualization platform into functional modules and adapt the visualization data model according to the functional modules; the visualization data model is used to develop the most popular visualization display plan; According to the visualization data mode, when receiving the user's access request, the corresponding visualization data is output.

2. A data visualization processing method according to claim 1, characterized in that: The step of obtaining the internal data source of the enterprise and building a data warehouse includes: According to the internal data source of the enterprise, data types and business status information of multiple business data of more than one enterprise business node of the enterprise business are obtained; For the enterprise services and service status information, respectively, according to each service data type of the enterprise service node, calculate the execution rate of the enterprise services through each service node, and the calling speed of calling the enterprise service data in one or more enterprise internal data sources; For more than one internal data source of an enterprise, a data warehouse is established by generating the execution rates of enterprise business nodes corresponding to different enterprise businesses during the business execution process.

3. A data visualization processing method according to claim 1, characterized in that: The acquisition of the enterprise internal data source and the construction of the data warehouse also include: Determine the enterprise business information based on the enterprise's internal data sources; Determine the required data and candidate business indicator data for processing the business of the enterprise based on the business data of the enterprise; Among them, demand data refers to the data demand information of enterprise business information during the execution process; The business indicator candidate data represents a set of indicators among multiple indicators for quality evaluation of the enterprise business during execution; Based on the business correlation between the business indicator corresponding to the business indicator candidate data and the business demand indicated by the demand data; According to the business relevance, the visualization expectation corresponding to any business indicator is extracted from multiple business indicator candidate data.

4. A data visualization processing method according to claim 1, characterized in that: The preset technical architecture is a topological framework structure of an SQI interface, a business BI interface, and a business SQI statement for business process conversion that describes the enterprise business port based on a BI visualization tool.

5. A data visualization processing method according to claim 1, characterized in that: The connecting of the data warehouse with the preset technical architecture includes: According to the preset technical architecture, determine the service port and obtain the service characteristics corresponding to different service ports; Extract the business type characteristics of the corresponding enterprise business on the data warehouse from the business characteristics; The business type features are cross-convolutionally fused to determine the candidate storage addresses of the enterprise business in the data warehouse and the response isolation channels of the candidate storage addresses; The data warehouse and business port are connected through the response isolation channel, and data transmission is performed in the preset safe working mode.

6. A data visualization processing method according to claim 5, characterized in that: Under the preset security model: Determine the data security level through the business port and set up encryption requests for response isolation channels; When the data warehouse receives the encryption application, it generates a security encryption matrix for the business data to be interacted with; The weight of each interactive service item is calculated through the security encryption matrix, the weight coefficient of each interactive service item is determined, and the weight coefficient of each interactive service item is normalized to an interval, and the corresponding encryption request feature is generated according to the positive correlation between the weight coefficient and the security level; Obtain the encryption strength, key length, encryption complexity, and encryption tendency of different preset encryption algorithms, and match them one by one with the encryption request characteristics to determine the optimal encryption algorithm.

7. A data visualization processing method as claimed in claim 1, characterized in that: According to the functional module, the visualization data mode is adapted, including: Obtain the visualization conversion function and historical visualization display data of the mobile BI visualization platform; Generate visualization function trends of enterprise business and business data features corresponding to the visualization function trends based on visualization display data; Generate a visualization call network of enterprise business data based on business data characteristics, visualization function tendencies and visualization conversion functions; According to the visualization call network, when receiving the visualization request from the user, the visualization display popularity calculation is performed based on the visualized business data and business types; Based on the visualization popularity calculation results, determine the visualization display plan for the enterprise business data and convert it into a visualization data model.

8. A data visualization processing method as claimed in claim 1, characterized in that: When receiving the access request from the user, the method further includes: By receiving a request for visualization of any enterprise business data from any mobile terminal registered on the mobile network; Based on the access control policy associated with the requested enterprise business data, determining whether the mobile terminal has a visualization display privilege in the data warehouse; In response to determining that the mobile terminal has the visualization display privilege, identifying that the mobile terminal will perform a visualization conversion function call authorization to the mobile BI visualization platform when executing the visualization display privilege; According to the calling authorization of the visualization conversion function, the access time in the access control policy is adjusted, and a display approval message is sent to the mobile terminal.

9. A data visualization processing method according to claim 1, characterized in that: The generating of the mobile BI visualization platform further comprises: According to the preset technical architecture, the supervision test files are respectively set, and when there is an access request, the supervision test files are read and parsed to obtain the parsed first test data; Get the data format parameters set for the supervision test file in the mobile BI visualization platform; Performing format conversion on the first test data according to the data format parameter to obtain second test data; Determine a plurality of functional test cases through the second test data; Determine whether multiple functional test cases conform to the preset visualization display strategy, and start the corresponding visualization conversion function when the functional test cases conform to the preset visualization display strategy.

10. A data visualization processing system, characterized in that: include: Data warehouse module: used to obtain internal enterprise data sources and build data warehouses; Mobile BI visualization platform building module: used to connect the data warehouse with the preset technical architecture to generate a mobile BI visualization platform; Visualization conversion module: used to divide the mobile BI visualization platform into functional modules and adapt the visualization data mode according to the functional modules; the visualization data mode is used to formulate the most popular visualization display plan; Visualization output module: used to output corresponding visualization data according to the visualization data mode when receiving the user's access request.

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