BI technology-based enterprise operation data management method and system

Abstract

The invention relates to the technical field of data management, and discloses an enterprise operation data management method and system based on a BI technology, and the method comprises the steps: matching an operation target, updating an operation knowledge graph, generating an operation abnormality report and an operation potential report, and carrying out the visual display. The system corresponds to the method. According to the application, the operation data is collected and the operation target is accurately matched by means of the operation knowledge graph, so that the enterprise operation information is effectively integrated, the internal relation between the data and the target is mined, and the decision pertinence is improved; the priority of the knowledge graph is updated based on the operation target, so that the knowledge system closely fits the enterprise operation dynamic state, the timeliness and accuracy of data processing are ensured, and the generated operation exception report and potential report provide a powerful basis for timely discovering operation problems and potential opportunities and optimizing operation of enterprises. And the report is visually displayed by using the updated knowledge graph, so that high-efficiency cooperation of various departments of an enterprise is promoted, and the operation management capability and competitiveness of the enterprise are comprehensively enhanced.

Description

Technical Field

[0001] This application relates to the technical field of data management, and specifically, to an enterprise operation data management method and system based on BI technology. Background Art

[0002] In the field of enterprise operation management, operation data has become a key asset, and the operation situation it contains can be used to guide and manage operations. The inventors found the following problems when researching existing data management methods: Enterprise internal data is scattered and stored in various business systems, forming data islands that are difficult to cross. The heterogeneity of different data sources makes data integration extremely difficult, seriously hindering the efficient utilization of data; Regarding external information, enterprises lack effective means for integration and analysis, resulting in a large amount of valuable information being left idle and unable to provide strong support for decision-making; Although existing technologies use knowledge graph technology to achieve data integration and analysis, static knowledge graphs perform poorly in analyzing operation anomalies and operation potential; Chinese Patent No. CN202410312068.7 discloses an enterprise operation digital management system based on digital analysis. Although it constructs an enterprise operation digital management system and integrates business modules to a certain extent, there are still obvious deficiencies. Specifically: in terms of data processing depth, the ability to mine and analyze complex data is limited, and it is difficult to discover deep-level associations and trends; in terms of system flexibility, it is difficult to adapt to the personalized needs and business changes of different enterprises, and scalability also faces challenges; in terms of external data integration, the coverage is narrow and the integration depth is insufficient, and emerging data sources cannot be fully utilized; In addition, measures for data security and privacy protection are weak, making it difficult to meet compliance requirements and bringing potential risks to enterprises.

[0003] In summary, there is an urgent need for a new technical solution for enterprise operation data management based on BI technology to promote the development of enterprise operation data management. Summary of the Invention

[0004] The purpose of this application is to provide an enterprise operation data management method and system based on BI technology to solve the technical problems raised in the above background art.

[0005] To achieve the above purpose, this application discloses the following technical solutions: In the first aspect, this application discloses an enterprise operation data management method based on BI technology, and the method includes: Collect operation data and match operation objectives using a preset operation knowledge graph; wherein, the operation data is used to represent the operation situation of an enterprise, the operation knowledge graph is constructed based on BI technology and stores operation knowledge, and the operation knowledge at least includes the relationship between operation data and its corresponding operation objectives. The operation objectives include a main objective and parallel objectives. The main objective is the main operation objective having the same time series as the operation data, and the parallel objectives are operation objectives that are matched using the operation data and the operation knowledge graph and can be executed in parallel with the main objective. Update the operation knowledge graph based on the operation objectives; wherein, the update of the operation knowledge graph is to update the priority of the corresponding knowledge in the operation knowledge graph based on the main objective and the parallel objectives. Process the operation data based on the updated operation knowledge graph to generate an operation anomaly report and an operation potential report; wherein, the processing of the operation data is to verify whether there are anomalies in the operation of the main objective based on the updated operation knowledge graph and generate a corresponding operation anomaly report, and to verify whether there are potential operation parallel objectives other than the main operation objective based on the updated operation knowledge graph and generate a corresponding operation potential report. Visualize and display the operation anomaly report and the operation potential report using the updated operation knowledge graph; wherein, the visualization and display of the operation anomaly report and the operation potential report is to display the collaboration relationship between the corresponding operation departments based on the updated operation knowledge graph. The operation departments are the departments in the enterprise that operate the operation objectives, and the collaboration relationship is the relationship between the operation subtasks undertaken by each operation part for operating the operation objectives. The operation objectives are composed of several such operation subtasks.

[0006] Preferably, the collection of the operation data includes: Collect corresponding data from different operation departments using a preset data source adapter, and normalize the collected data using a preset data normalization algorithm to obtain the corresponding operation data.

[0007] Preferably, the matching of the operation objectives includes: Calculate the similarity between the operation data and the operation objectives using the operation knowledge, determine the operation objectives that satisfy a preset similarity threshold with the operation data as candidate operation objectives, calculate the time series matching degree and the dependency matching degree between the candidate operation objectives and the operation data, determine the candidate operation objectives that satisfy the preset time series matching degree threshold as the main objective, and determine the candidate operation objectives that satisfy the preset dependency matching degree as the parallel objectives. The calculation of the time series matching degree is: Among them, is the time series value of the element corresponding to the operation data ; is the time series value of the element corresponding to the operation knowledge graph ; is the absolute value operator is the number of time series elements is the calculated time series matching degree; The calculation of the dependency matching degree is: Among them, is the preset main target and the weight of the th dependency relationship with the candidate operation target is the main target and the satisfaction degree of the th dependency relationship with the candidate operation target is the number of dependency relationships is the main target and the normalized value of the predicted simultaneous operation time of the candidate operation target is the calculated dependency matching degree.

[0008] Preferably, the update of the operation knowledge graph includes: Calculating the updated priority of the corresponding knowledge by using the initial priority preset by the knowledge, the predicted time deviation of the operation completion, the predicted cost deviation of the operation completion, the quality index corresponding to the knowledge, the number of common entities between the operation knowledge graph before and after the update, and the total number of entities of the operation knowledge graph before the update.

[0009] Preferably, the generation of the operation anomaly report includes: Obtaining the key indicators in the operation data, calculating the statistical indicators corresponding to the key indicators, obtaining the preset anomaly threshold, calculating the operation anomaly index, and determining that there is an operation anomaly when the operation anomaly index is greater than the preset operation anomaly index threshold, and outputting the key indicators corresponding to the statistical indicators that do not meet the anomaly threshold as the report content in the operation anomaly report; among them, the calculation of the operation anomaly index is: Among them, represents the key indicator subtracted from its corresponding mean value and then divided by its corresponding standard deviation and then compared with its corresponding anomaly threshold When Assign the value as otherwise, assign the value as , is the number of key indicators, is the calculated operation anomaly index.

[0010] Preferably, the generation of the operation potential report includes: Obtain the market potential of the parallel target , cost savings value , resource utilization efficiency improvement value , risk index and implementation difficulty , calculate the operation potential index of the parallel target , the operation potential index is calculated as: For different parallel targets , based on their operation potential indices sort them, and preferentially operate the parallel targets with higher operation potential indices.

[0011] Preferably, the visualization of the operation anomaly report includes: Generate corresponding anomaly heat values based on the operation anomaly index, deconstruct the operation targets corresponding to the operation anomaly index to obtain the corresponding operation departments and their operation subtasks, decompose the anomaly heat values to the corresponding operation subtasks, and perform visual display in the operation departments corresponding to the operation subtasks.

[0012] Preferably, the visualization of the operation potential report includes: Generate corresponding potential heat values based on the operation potential index, deconstruct the operation targets corresponding to the operation potential index to obtain the corresponding operation departments and their operation subtasks, decompose the potential heat values to the corresponding operation subtasks, and perform visual display in the operation departments corresponding to the operation subtasks.

[0013] Preferably, the method further includes: Based on the confidentiality levels of the operation departments corresponding to the operation anomaly report and the operation potential report, match the corresponding preset encryption methods, and use the matched encryption methods to visually display the operation anomaly report and the operation potential report on the devices of the corresponding administrators.

[0014] In a second aspect, the present application discloses an enterprise operation data management system based on BI technology. This system is applicable to the enterprise operation data management method based on BI technology as described above. This system includes: An operation target matching module, where the operation target matching module is configured to: collect operation data and match operation targets by using a preset operation knowledge graph; wherein, the operation data is used to represent the operation situation of an enterprise, the operation knowledge graph is constructed based on BI technology and stores operation knowledge, and the operation knowledge at least includes the relationship between operation data and its corresponding operation target. The operation targets include a main target and parallel targets. The main target is the main operation target having the same time series as the operation data, and the parallel targets are operation targets that can be executed in parallel with the main target and are matched by using the operation data and the operation knowledge graph. An operation knowledge graph updating module, where the operation knowledge graph updating module is configured to: update the operation knowledge graph based on the operation targets; wherein, the update of the operation knowledge graph is to update the priority of the corresponding knowledge in the operation knowledge graph based on the main purpose and the parallel purposes. A report generation module, where the report generation module is configured to: process the operation data based on the updated operation knowledge graph to generate an operation anomaly report and an operation potential report; wherein, the processing of the operation data is to verify whether there is an anomaly in the operation of the main target based on the updated operation knowledge graph and generate a corresponding operation anomaly report, and to verify whether there are potential operation parallel targets other than the main operation target based on the updated operation knowledge graph and generate a corresponding operation potential report. A visualization module, where the visualization module is configured to: visually display the operation anomaly report and the operation potential report by using the updated operation knowledge graph; wherein, the visual display of the operation anomaly report and the operation potential report is to display the collaboration relationship between the corresponding operation departments based on the updated operation knowledge graph. The operation departments are the departments in the enterprise that operate the operation targets, and the collaboration relationship is the relationship between the operation subtasks undertaken by each operation part for operating the operation targets. The operation target consists of several such operation subtasks.

[0015] Beneficial effects: The enterprise operation data management method and system based on BI technology in this application collect operation data and accurately match operation targets with the help of an operation knowledge graph, effectively integrating enterprise operation information, mining the internal connection between data and targets, and enhancing the pertinence of decision-making; updating the priority of the knowledge graph based on operation targets makes the knowledge system closely conform to the enterprise operation dynamics, ensuring the timeliness and accuracy of data processing. Furthermore, the generated operation anomaly report and potential report provide a strong basis for timely discovering operation problems and potential opportunities and optimizing enterprise operations. Visualizing the reports by using the updated knowledge graph clearly presents the collaboration relationship between operation departments, promotes the efficient cooperation of each department in the enterprise, comprehensively enhances the enterprise operation management ability and competitiveness, and promotes the sustainable development of the enterprise. Description of the Drawings

[0016] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those skilled in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0017] Figure 1 It is a flowchart of the enterprise operation data management method based on BI technology provided by the embodiment of the present application; Figure 2 It is a structural block diagram of the enterprise operation data management system based on BI technology provided by the embodiment of the present application. Specific embodiments

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0019] In this article, the term "including" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such a process, method, article or device. Without further limitations, the elements defined by the statement "including..." do not exclude the existence of other identical elements in the process, method, article or device including the said elements.

[0020] The first aspect of this embodiment discloses a Figure 1 kind of enterprise operation data management method based on BI technology as shown in the figure, and the method includes: Collect operation data and use a preset operation knowledge graph to match operation goals; wherein, the operation data is used to represent the operation situation of the enterprise, the operation knowledge graph is constructed based on BI technology and stores operation knowledge, and the operation knowledge at least includes the relationship between the operation data and its corresponding operation goals. The operation goals include main goals and parallel goals. The main goal is the main operation goal with the same time series as the operation data, and the parallel goal is the operation goal that can be executed in parallel with the main goal and is matched by using the operation data and the operation knowledge graph; Update the operation knowledge graph based on the operation goals; wherein, the update of the operation knowledge graph is to update the priority of the corresponding knowledge in the operation knowledge graph based on the main purpose and the parallel purpose; The operation data is processed based on the updated operation knowledge graph to generate an operation anomaly report and an operation potential report; wherein the operation data is processed by verifying whether there is an anomaly in the operation of the main target based on the updated operation knowledge graph and generating a corresponding operation anomaly report, and verifying whether there is potential to operate parallel targets other than the main operation target based on the updated operation knowledge graph and generating a corresponding operation potential report; The updated operation knowledge graph is used to visualize the operation exception report and the operation potential report; wherein, the visualization of the operation exception report and the operation potential report is based on the updated operation knowledge graph to display the collaborative relationship between the corresponding operation departments, the operation department is the department in the enterprise that operates the operation objectives, the collaborative relationship is the relationship between the operation subtasks undertaken by each operation part to operate the operation objectives, and the operation objectives are composed of several operation subtasks.

[0021] Based on the above, this embodiment utilizes the enterprise operation data management method based on BI technology to achieve efficient management and in-depth application of enterprise operation data; it collects operation data and uses the operation knowledge graph to accurately match operation goals, effectively integrates enterprise operation information, explores the intrinsic connection between data and goals, and improves the pertinence of decision-making; updates the knowledge graph priority based on operation goals, so that the knowledge system is closely aligned with the enterprise operation dynamics, ensuring the timeliness and accuracy of data processing, and then generates operation exception reports and potential reports to provide a strong basis for timely discovery of operation problems and potential opportunities and optimization of enterprise operations. The updated knowledge graph is used to visualize the report, clearly presenting the collaborative relationship between operation departments, promoting efficient collaboration among various departments of the enterprise, comprehensively enhancing the enterprise's operation management capabilities and competitiveness, and promoting sustainable development of the enterprise.

[0022] Specifically, the collection of operational data includes: Use the preset data source adapter to collect corresponding data from different operating departments, and use the preset data normalization algorithm to normalize the collected data to obtain the corresponding operating data.

[0023] Based on the above, this embodiment uses the preset existing data source adapter and the existing data normalization algorithm to collect operational data, thereby realizing rapid data collection and standardized processing. The data source adapter ensures that data can be accurately obtained from different operating departments, overcomes the problem of scattered data sources, and improves data collection efficiency. The data normalization algorithm unifies the data format and scale, enhances the comparability and availability of data, and lays a solid foundation for subsequent target matching and analysis. In this way, the complexity of data processing is reduced, and the fluency of the overall data management process is improved, so that operational data can better serve corporate decision-making, optimize corporate operating processes, and improve operational efficiency and quality.

[0024] Specifically, the matching of operational objectives includes: Calculate the similarity between operation data and operation objectives using operation knowledge, determine the operation objectives that meet the preset similarity threshold with the operation data as candidate operation objectives, calculate the time series matching degree and dependency matching degree between the candidate operation objectives and the operation data, determine the main objectives for the candidate operation objectives that meet the preset time series matching degree threshold, and determine the parallel objectives for the candidate operation objectives that meet the preset dependency matching degree; The calculation of the time series matching degree is as follows: Wherein, is the time series value of the corresponding element of the operation data ; is the time series value of the corresponding element of the operation knowledge graph ; is the absolute value operator; is the number of time series elements; is the calculated time series matching degree; The calculation of the dependency matching degree is as follows: Wherein, is the weight of the preset main objective and the th dependency relationship of the candidate operation objective; is the satisfaction degree of the main objective and the th dependency relationship of the candidate operation objective; is the number of dependency relationships; is the normalized value of the predicted simultaneous operation time of the main objective and the candidate operation objective; is the calculated dependency matching degree.

[0025] Through the above, this embodiment calculates the similarity between operation data and operation objectives using operation knowledge, and determines the main objectives and parallel objectives in combination with the time series matching degree and dependency matching degree, achieving accurate target screening and positioning. By calculating the similarity, the target range is quickly narrowed down, and then the consistency between the main objective and the operation data time series is ensured according to the time series matching degree, making the decision closely follow the current operation rhythm of the enterprise. The calculation of the dependency matching degree fully considers the association and coordination between objectives, excavates potential parallel objectives, and provides possibilities for the enterprise to expand its operation ideas and optimize resource allocation. This multi-dimensional matching method improves the accuracy and scientificity of target determination, and effectively enhances the rationality and effectiveness of enterprise operation decisions.

[0026] Specifically, the update of the operation knowledge graph includes: Calculate the updated priority of the corresponding knowledge by using the initial priority preset by the knowledge, the predicted time deviation of the operation completion, the predicted cost deviation of the operation completion, the quality index corresponding to the knowledge, the number of common entities between the operation knowledge graph before and after the update, and the total number of entities in the operation knowledge graph before the update.

[0027] It should be noted that the initial priority preset by the knowledge, the predicted time deviation of the operation completion, the predicted cost deviation of the operation completion, and the quality index corresponding to the knowledge in this embodiment are all empirical values well-known to those skilled in the art obtained by using existing BI technology. As a preferred implementation manner of this embodiment, use the preset priority update formula to update the priority of the knowledge in the operation knowledge graph. The priority update formula is: Among them, is the initial priority preset by the knowledge ; is the predicted time deviation of the operation completion based on the knowledge ; is the predicted cost deviation of the operation completion based on the knowledge ; is the quality index corresponding to the knowledge ; is the number of common entities between the th update and the operation knowledge graph before the update; is the total number of entities in the operation knowledge graph before the th update; , , and are preset weights; is the priority of the knowledge after the th update calculated.

[0028] Through the above, this embodiment updates the knowledge priority in the operation knowledge graph by using the priority update formula, realizing the dynamic optimization of the knowledge graph. Adjust the priority according to the time deviation, cost deviation, quality index of the operation completion and the entity association situation with the graph before the update, so that the knowledge graph can timely reflect the actual operation situation. This helps to highlight key knowledge, guide data processing and decision-making analysis to focus on important information, and avoid information overload and decision-making misguidance. By continuously updating the priority, maintain the vitality and adaptability of the knowledge graph, better support the enterprise to cope with the complex and changeable operation environment, and improve the flexibility and accuracy of operation management.

[0029] Specifically, the generation of the operation anomaly report includes: Obtain the key indicators in the operation data, calculate the statistical indicators corresponding to the key indicators, obtain the preset abnormal threshold, calculate the operation abnormal index, and determine that there is an operation abnormality when the operation abnormal index is greater than the preset operation abnormal index threshold. Output the key indicators corresponding to the statistical indicators that do not meet the abnormal threshold as the report content in the operation abnormal report; among them, the calculation of the operation abnormal index is as follows: Among them, represents the key indicator subtract its corresponding mean value and then divide by its corresponding standard deviation and then compare with its corresponding abnormal threshold When assign the value otherwise assign the value , is the number of key indicators, is the calculated operation abnormal index.

[0030] By the above, this embodiment generates an operation abnormal report by using key indicator statistics and operation abnormal index calculation, realizing effective monitoring and early warning of operation risks. By calculating the statistics of key indicators and comparing them with the thresholds preset based on the common knowledge and experience of those skilled in the art, the degree of abnormality is accurately quantified, and abnormal situations in operation are quickly identified. The operation abnormal index intuitively reflects the overall abnormal state, providing a clear risk signal for the enterprise. Outputting the abnormal report content in a timely manner helps the enterprise take measures to correct deviations in a timely manner, prevent the expansion of risks, ensure the stability and reliability of enterprise operation, reduce potential losses, and maintain the normal production and operation order of the enterprise.

[0031] Specifically, the generation of the operation potential report includes: Obtain the market potential of the parallel target , cost savings , resource utilization efficiency improvement value , risk index and implementation difficulty , calculate the operation potential index of the parallel target , the calculation of the operation potential index is as follows: For different parallel targets , based on their operation potential index sort them, and give priority to operating the parallel targets with high operation potential index.

[0032] Through the above, this embodiment generates an operation potential report by using the multi-factor evaluation of parallel objectives and the calculation of the operation potential index, realizing the in-depth exploration of the potential development opportunities of the enterprise. Considering factors such as market potential, cost savings, resource utilization efficiency, and risk implementation difficulty, it comprehensively evaluates the feasibility and value of parallel objectives. The operation potential index provides a quantitative decision-making reference for the enterprise, facilitating the comparison and ranking of different parallel objectives. Prioritizing the objectives with a high operation potential index helps the enterprise allocate resources reasonably, seize development opportunities, enhance market competitiveness, and achieve innovative development and benefit growth.

[0033] Specifically, the visualization of the operation anomaly report includes: Generating a corresponding anomaly heat value based on the operation anomaly index, deconstructing the operation objectives corresponding to the operation anomaly index to obtain the corresponding operation departments and their operation subtasks, decomposing the anomaly heat value to the corresponding operation subtasks, and visually displaying it in the operation departments corresponding to the operation subtasks.

[0034] Through the above, this embodiment uses the visualization technology in the existing BI technology to realize the operation of generating the anomaly heat value from the operation anomaly index, and decomposes it to the operation subtasks for visual display, realizing the intuitive presentation and accurate positioning of operation anomalies. The anomaly heat value intuitively reflects the severity of the anomaly. Decomposing it to specific operation subtasks and departments enables enterprise managers to quickly focus on the root cause of the problem. The visual display enhances the readability and comprehensibility of information, facilitates cross-departmental communication and collaboration, and accelerates the process of problem-solving. In this way, the response speed and processing efficiency of the enterprise to operation anomalies are improved, and the negative impact of anomalies on enterprise operation is reduced.

[0035] Specifically, the visualization of the operation potential report includes: Generating a corresponding potential heat value based on the operation potential index, deconstructing the operation objectives corresponding to the operation potential index to obtain the corresponding operation departments and their operation subtasks, decomposing the potential heat value to the corresponding operation subtasks, and visually displaying it in the operation departments corresponding to the operation subtasks.

[0036] Through the above, this embodiment uses the visualization technology in the existing BI technology to realize the operation of generating the potential heat value from the operation potential index, and decomposes it to the operation subtasks for visual display, realizing the clear display and effective communication of operation potential. The potential heat value vividly reflects the potential size of the parallel objectives. After being decomposed to the operation subtasks and departments, it provides a clear development direction guidance for all levels of the enterprise. The visual display promotes the formation of a consensus on potential opportunities within the enterprise, facilitating the coordination of resources to promote the realization of potential objectives. This helps to stimulate the innovation vitality of the enterprise, optimize the operation layout, and enhance the overall operation efficiency and development potential.

[0037] Specifically, the method further includes: Based on the security level of the operation department corresponding to the operation exception report and the operation potential report, match the corresponding preset encryption method, and use the matched encryption method to visually display the operation exception report and the operation potential report on the devices of the corresponding administrators.

[0038] Through the above, this embodiment uses the encryption method matching based on the preset operation department security level to display the reports, achieving a balance between data security and effective information transmission. Selecting the appropriate existing encryption method according to the security levels of different departments ensures the confidentiality and integrity of sensitive information during transmission and display, preventing the risk of data leakage. At the same time, on the premise of ensuring security, the operation exception and potential reports are accurately transmitted to the administrators, enabling them to obtain key information in a timely manner and take actions. This method takes into account the data security requirements and the actual needs of enterprise operation management, enhancing the security and reliability of enterprise data management.

[0039] The second aspect of this embodiment discloses Figure 2 An enterprise operation data management system based on BI technology as shown in An operation target matching module, configured to: collect operation data and match operation targets using a preset operation knowledge graph; wherein, the operation data is used to characterize the operation situation of the enterprise, the operation knowledge graph is constructed based on BI technology and stores operation knowledge, and the operation knowledge at least includes the relationship between the operation data and its corresponding operation targets. The operation targets include a main target and parallel targets. The main target is the main operation target with the same time series as the operation data, and the parallel targets are the operation targets that can be executed in parallel with the main target and are matched using the operation data and the operation knowledge graph. An operation knowledge graph update module, configured to: update the operation knowledge graph based on the operation targets; wherein, the update of the operation knowledge graph is to update the priority of the corresponding knowledge in the operation knowledge graph based on the main purpose and the parallel purposes. A report generation module, configured to: process the operation data based on the updated operation knowledge graph to generate an operation exception report and an operation potential report; wherein, the processing of the operation data is to verify whether there are exceptions in the operation of the main target based on the updated operation knowledge graph and generate the corresponding operation exception report, and to verify whether there are potential operation parallel targets other than the operation main target based on the updated operation knowledge graph and generate the corresponding operation potential report. Visualization module, the visualization module is configured as follows: using the updated operation knowledge graph to visualize the operation exception report and the operation potential report; wherein, the visualization display of the operation exception report and the operation potential report is based on the updated operation knowledge graph to display the collaborative relationship between the corresponding operation departments, the operation department is the department in the enterprise that operates the operation objectives, the collaborative relationship is the relationship between the operation subtasks undertaken by each operation part to operate the operation objectives, and the operation objectives are composed of several operation subtasks.

[0040] It should be noted that the enterprise operation data management system based on BI technology of this embodiment corresponds to the aforementioned enterprise operation data management method based on BI technology. Therefore, the contents not specifically described in the enterprise operation data management system based on BI technology of this embodiment may include but are not limited to function definitions, working principles and technical effects, etc., and may refer to the records of the aforementioned enterprise operation data management method based on BI technology, and this text will not elaborate on them here.

[0041] In summary, the enterprise operation data management method and system based on BI technology in this embodiment collects operation data and uses the operation knowledge graph to accurately match operation goals, effectively integrates enterprise operation information, explores the intrinsic connection between data and goals, and improves the pertinence of decision-making; updates the knowledge graph priority based on operation goals, so that the knowledge system is closely aligned with the enterprise operation dynamics, ensuring the timeliness and accuracy of data processing, and then generates operation exception reports and potential reports to provide a strong basis for timely discovery of operation problems and potential opportunities and optimization of enterprise operations. The updated knowledge graph is used to visualize the report, clearly present the collaborative relationship between operation departments, promote efficient collaboration among various departments of the enterprise, comprehensively enhance the enterprise's operation management capabilities and competitiveness, and promote sustainable development of the enterprise.

[0042] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, or other electronic units designed to implement the functions described herein, or a combination thereof. For software implementation, part or all of the processes of the embodiments can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. The computer-readable storage medium includes computer storage media and communication media, where the communication media includes any medium that facilitates the transmission of a computer program from one place to another. The storage media can be any available medium that can be accessed by a computer. The computer-readable storage medium can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer.

[0043] Finally, it should be noted that the above are only the preferred embodiments of the present application and are not used to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for managing enterprise operation data based on BI technology, characterized in that: The method includes: Collecting operation data and matching operation goals with a preset operation knowledge graph; wherein the operation data is used to characterize the operation status of the enterprise, the operation knowledge graph is constructed based on BI technology and stores operation knowledge, the operation knowledge at least includes the relationship between the operation data and its corresponding operation goals, the operation goals include main goals and parallel goals, the main goal is the main operation goal with the same time series as the operation data, and the parallel goal is the operation goal matched with the operation data and the operation knowledge graph and can be executed in parallel with the main goal; The operation knowledge graph is updated based on the operation goal; wherein the update of the operation knowledge graph is to update the priority of the corresponding knowledge in the operation knowledge graph based on the main purpose and the parallel purpose; The operation data is processed based on the updated operation knowledge graph to generate an operation abnormality report and an operation potential report; wherein the operation data is processed by verifying whether there is an abnormality in the operation of the main target based on the updated operation knowledge graph and generating a corresponding operation abnormality report, and verifying whether there is potential to operate a parallel target in addition to the main operation target based on the updated operation knowledge graph and generating a corresponding operation potential report; The operation exception report and the operation potential report are visualized using the updated operation knowledge graph; wherein the visualization of the operation exception report and the operation potential report is based on the updated operation knowledge graph to display the collaborative relationship between the corresponding operation departments, the operation department is the department in the enterprise that operates the operation target, the collaborative relationship is the relationship between the operation subtasks undertaken by each operation part to operate the operation target, and the operation target is composed of several operation subtasks.

2. The enterprise operation data management method based on BI technology according to claim 1 is characterized in that: The collection of the operational data includes: The corresponding data are collected from different operation departments using a preset data source adapter, and the collected data are normalized using a preset data normalization algorithm to obtain the corresponding operation data.

3. The enterprise operation data management method based on BI technology according to claim 1 is characterized in that: The matching of the operational objectives includes: Calculate the similarity between the operation data and the operation target by using the operation knowledge, determine the operation target that meets a preset similarity threshold with the operation data as a candidate operation target, calculate the timing matching degree and dependency matching degree between the candidate operation target and the operation data, determine the candidate operation target that meets the preset timing matching degree threshold as the main target, and determine the candidate operation target that meets the preset dependency matching degree as the parallel target; The calculation of the timing matching degree is: in, Corresponding elements for operational data The time series value of Corresponding elements for the operation knowledge graph The time series value of is the absolute value operator, is the number of time series elements, is the calculated timing matching degree; The calculation of the dependency matching degree is: in, The default main target and candidate operational targets No. The weight of the dependency, Main Target and candidate operational targets No. The degree of satisfaction of a dependency relationship, is the number of dependencies, Main Target and candidate operational targets The normalized value of the predicted simultaneous operation time, is the calculated dependency matching degree.

4. The enterprise operation data management method based on BI technology according to claim 1 is characterized in that: The update of the operation knowledge graph includes: The updated priority of the corresponding knowledge is calculated using the preset initial priority of the knowledge, the predicted time deviation for operation completion, the predicted cost deviation for operation completion, the quality index corresponding to the knowledge, the number of common entities in the operation knowledge graph before and during the update, and the total number of entities in the operation knowledge graph before the update.

5. The enterprise operation data management method based on BI technology according to claim 1 is characterized in that: The generation of the operational abnormality report includes: Obtain key indicators in the operation data, calculate statistical indicators corresponding to the key indicators, obtain a preset abnormality threshold, calculate the operation abnormality index, and determine that there is an operation abnormality when the operation abnormality index is greater than the preset operation abnormality index threshold. Output the key indicators corresponding to the statistical indicators that do not meet the abnormality threshold as the report content in the operation abnormality report; wherein, the operation abnormality index is calculated as follows: in, Indicates key indicators The corresponding mean The standard deviation corresponding to the difference The corresponding abnormal threshold after taking the quotient For comparison, When the value is , otherwise it is assigned to , is the number of key indicators, is the calculated operation abnormality index.

6. The enterprise operation data management method based on BI technology according to claim 1 is characterized in that: The generation of the operational potential report includes: Acquire the market potential of the parallel targets , cost saving value , Resource Utilization Efficiency Improvement Value , Risk Index and implementation difficulty , calculate the operational potential index of the parallel target , the operational potential index The calculation is: For different parallel targets , based on its operational potential index Sort and prioritize parallel targets with high operational potential index.

7. The enterprise operation data management method based on BI technology according to claim 5 is characterized in that: The visualization of the operational exception report includes: Based on the operation abnormality index, a corresponding abnormal thermal value is generated, and the operation target corresponding to the operation abnormality index is deconstructed to obtain the corresponding operation department and its operation subtasks. The abnormal thermal value is decomposed into the corresponding operation subtasks, and the operation department corresponding to the operation subtask is visualized.

8. The enterprise operation data management method based on BI technology according to claim 6 is characterized in that: Visualizations of the operational potential report include: Based on the operation potential index, a corresponding potential thermal value is generated, and the operation target corresponding to the operation potential index is deconstructed to obtain the corresponding operation department and its operation subtasks. The potential thermal value is decomposed into the corresponding operation subtasks, and the operation department corresponding to the operation subtask is visualized.

9. The enterprise operation data management method based on BI technology according to claim 1, characterized in that: The method further includes: Based on the confidentiality level of the operation department corresponding to the operation exception report and the operation potential report, the corresponding preset encryption method is matched, and the operation exception report and the operation potential report are visualized on the corresponding administrator's device using the matched encryption method.

10. An enterprise operation data management system based on BI technology, the system is applicable to the enterprise operation data management method based on BI technology as described in any one of claims 1 to 9, characterized in that: The system includes: An operation target matching module, wherein the operation target matching module is configured to: collect operation data and match operation targets using a preset operation knowledge graph; wherein the operation data is used to characterize the operation status of the enterprise, the operation knowledge graph is constructed based on BI technology and stores operation knowledge, and the operation knowledge at least includes the relationship between the operation data and its corresponding operation targets, the operation targets include a main target and a parallel target, the main target is a main operation target having the same time series as the operation data, and the parallel target is an operation target matched using the operation data and the operation knowledge graph and can be executed in parallel with the main target; An operation knowledge graph updating module, wherein the operation knowledge graph updating module is configured to: update the operation knowledge graph based on the operation target; wherein the update of the operation knowledge graph is to update the priority of the corresponding knowledge in the operation knowledge graph based on the main purpose and the parallel purpose; A report generation module, wherein the report generation module is configured to: process the operation data based on the updated operation knowledge graph to generate an operation abnormality report and an operation potential report; wherein the operation data processing includes verifying whether there is an abnormality in the operation of the main target based on the updated operation knowledge graph and generating a corresponding operation abnormality report, and verifying whether there is potential to operate a parallel target in addition to the main operation target based on the updated operation knowledge graph and generating a corresponding operation potential report; A visualization module, wherein the visualization module is configured to: utilize an updated operation knowledge graph to visualize the operation anomaly report and the operation potential report; wherein the visualization display of the operation anomaly report and the operation potential report is based on the updated operation knowledge graph to display the collaborative relationship between the corresponding operation departments, wherein the operation department is a department in an enterprise that operates the operation target, and the collaborative relationship is the relationship between the operation subtasks undertaken by each operation part to operate the operation target, and the operation target is composed of a number of the operation subtasks.

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