Progress-visualized data governance optimization system

Abstract

The invention discloses a progress-visualized data governance optimization system, which comprises a problem data state acquisition module used for acquiring a data record label of problem data and a problem data state of each current unit; the data governance trend display module is used for generating a problem data rectification rate trend chart and a stage governance effect comparison chart based on the data governance progress trend analysis result; the governance state recognition module is used for recognizing the governance state of each unit and judging the lag reason of the lagging unit; the lagging unit reminding module is used for generating lagging reminding content of each lagging unit and sending the lagging reminding content to the corresponding business domain responsible person and the governance responsible person; and the rectification efficiency identification module is used for generating new lag reminding contents for units which do not reach the preset treatment standard. According to the invention, through optimizing the display of the data management condition, the management layer can comprehensively master the management progress of each unit, the real-time, dynamic and visual display of the information is realized, and the efficiency and quality of the data management work are obviously improved.

Description

Technical Field

[0001] The present invention relates to the field of data management and information visualization, and in particular to a data management optimization system with progress visualization. Background Art

[0002] In the data governance process of ultra-high voltage transmission companies, the display of data governance has always been a core issue to be optimized. With the increase in business complexity, the governance needs of various units in terms of equipment status, fault records, quality inspections, etc. have surged, and data governance tasks have gradually accumulated. However, the current data governance platform has problems with information lag, lack of real-time and intuitiveness in displaying the governance progress of various units. Due to the limitations of the platform in displaying data governance, it is difficult for management to grasp the governance status and progress of each unit in a timely manner, especially the governance effectiveness on different data types, resulting in the inability to fully evaluate the governance progress and affecting the reasonable allocation of governance resources. On the one hand, when displaying the governance situation, the existing data governance platform mostly only provides a single indicator, lacks dynamic governance progress charts and trend charts, and managers can only see basic data such as the current number of tasks and the number of rectified problems. It is impossible to intuitively understand the data governance trend of each unit through the data governance platform, nor can it compare the governance effects in stages, resulting in the difficulty in quantifying the effectiveness of governance progress at different stages. Details in the governance process, such as the specific causes of the lag problem and the degree of data backlog, cannot be deeply analyzed through existing display methods, resulting in a lack of accurate basis for management when formulating adjustment measures. In addition, the data governance platform cannot effectively display the governance status of upstream and downstream dependencies. Due to the linkage of governance tasks, there is often a dependency relationship between the governance tasks of various units, but the existing platform fails to intuitively present the lagging impact of upstream units to managers, resulting in the potential risks of downstream units not being identified in advance. Upstream dependency lags often cause governance delays for downstream units, but it is difficult for management to see the lag in the dependency chain in the existing display, and it is impossible to consider the connection between upstream and downstream when allocating governance resources, further delaying the overall governance progress. The current display mechanism also lacks a means of displaying dynamic feedback, making it difficult for management to evaluate whether lagging governance is effectively followed up. Therefore, in terms of the display of data governance, the existing data governance platform urgently needs to be optimized to improve the dynamic, intuitive and traceable nature of information, so that management can fully grasp the governance situation, identify problems in real time and adjust governance strategies in a timely manner, thereby improving the overall effect of data governance. Summary of the invention

[0003] To solve the problems existing in the above-mentioned prior art, the present invention provides a data management optimization system with progress visualization, which mainly includes:

[0004] The problem data status acquisition module is used to obtain the data record labels of the problem data through the data governance platform, determine the classification attributes of the problem data, and obtain the current problem data status of each unit;

[0005] The data governance trend display module is used to generate a problem data governance progress view based on the problem data status of each unit, and generate a problem data rectification rate trend chart and a stage governance effect comparison chart based on the data governance progress trend analysis results;

[0006] The governance status identification module is used to obtain the governance progress data of each unit, identify the governance status of each unit, and determine the reasons for the lag of the lagging units;

[0007] The lagging unit reminder module is used to generate the lagging reminder content of each lagging unit according to the lagging reason mark, lagging quantity and governance progress data of each lagging unit, and send it to the corresponding business domain person in charge and governance person in charge;

[0008] The rectification efficiency identification module is used to update the data governance progress trend chart based on the rectification status data of each unit after the delayed reminder, and generate new delayed reminder content for units that have not met the predetermined governance standards.

[0009] Furthermore, the problem data status acquisition module is used to obtain the data record label of the problem data through the data governance platform, determine the classification attribute of the problem data, and obtain the current problem data status of each unit, including:

[0010] Through the data governance platform of the ultra-high voltage transmission company, the key information fields of the current problem data of each unit are obtained. The key information fields include data record tags, timestamps and unit identification. The data record tags include but are not limited to monitoring equipment and line status monitoring systems; according to the data record tags, the problem data is mapped to the corresponding data type to obtain the classification attributes of each problem data, and the classification results of each problem data are stored in the additional fields of the data record. The data types include power line monitoring data, equipment status data, fault records, and quality inspection data; the classified problem data records are obtained, and different types of data are allocated to the corresponding partition databases for partition storage according to the classification attributes; according to the data stored in the partitions, the current problem data status of each unit is obtained, including the number of problem data, the number of data that has been rectified, and the number of new problems. The number of rectified data in the current cycle is compared with the changes in the previous data record to obtain the incremental information of the rectification quantity, and update it to the data governance record table of each unit.

[0011] Furthermore, the data governance trend display module is used to generate a problem data governance progress view according to the problem data status of each unit, and generate a problem data rectification rate trend chart and a stage governance effect comparison chart based on the data governance progress trend analysis results, including:

[0012] According to the data stored in the partitions, the problem data status of each unit is obtained, including the number of problem data, the number of data that have been rectified, and the number of new problems; through the data visualization component, according to the number of problem data of each unit, the number of problem data that have been rectified, the number of problem data to be rectified, and the number of new problems, a problem data governance progress view is generated to monitor the data governance status of each unit in real time. If an update of the problem data status is detected, the problem data governance progress view is updated; according to the data governance record table of each unit in the data governance platform and the current problem data status, the problem data status of each unit at different time nodes is obtained; through the problem data rectification rate = number of rectified data / (number of rectified data + number of problems to be rectified + number of new problems), the problem data rectification rate of each unit at each time node is calculated, and arranged according to timestamps to form a time series problem data rectification rate data set; using the regression analysis algorithm, the problem data rectification rate of each unit is Regression modeling is performed on time series data to fit the data governance progress trend line of each unit. Based on the slope of each trend line, the data rectification speed and progress direction of each unit are obtained; by calculating the average problem data rectification rate of each unit in different time periods, the data governance effect at different stages of the governance progress is judged; through the data visualization component, based on the data governance progress trend analysis results, a problem data rectification rate trend chart is generated using a line chart to show the problem data rectification rate change trend of each unit, and a bar chart is used to generate a stage governance effect comparison chart to show the change in governance effect of each unit in different time periods; according to the data visualization rules, a multi-dimensional chart report containing a problem data rectification rate trend chart and a stage governance effect comparison chart is generated to form a graphical display of governance progress and trends; through the automatic report generation component, a textual summary of the governance progress, rectification rate trend and governance effect changes of each unit is generated, and a trend analysis report is generated in combination with the chart display, and the report is uploaded to the data governance platform.

[0013] Furthermore, the governance status identification module is used to obtain the governance progress data of each unit, identify the governance status of each unit, and determine the lagging reasons of the lagging units, including:

[0014] Through the data governance platform of the ultra-high voltage transmission company, the governance progress data of each unit is obtained in real time, including the number of problem data to be rectified, the number of data that have been rectified, and the rectification rate of problem data, and the data is recorded in time series and stored in the governance progress data table; the current problem data rectification rate of each unit is compared with the preset rectification rate threshold, and the number of problem data to be rectified is compared with the preset number threshold. If it is detected that the problem data rectification rate is lower than the preset rectification rate threshold or the number of problem data to be rectified is higher than the preset number threshold, the governance status of the unit is marked as lagging; according to the growth rate of the backlog of problem data of the lagging unit, it is judged whether it belongs to the problem data backlog type lag; if the problem data backlog is higher than the preset number threshold, the governance status of the unit is marked as lagging; according to the growth rate of the problem data backlog of the lagging unit, it is judged whether it belongs to the problem data backlog type lag. If the growth rate of the pressure quantity is greater than the preset growth rate threshold, the lag reason is marked as a backlog of problem data; according to the problem data rectification rate of each time node of the unit with a lagging governance status, it is judged whether it belongs to a low rectification rate. If the calculated problem data rectification rate is lower than the preset rectification rate threshold for several time periods, the lag reason is marked as a low rectification rate; if both the problem data backlog and the low rectification rate are met at the same time, the lag priority of the unit is marked as a high priority lag; through the dependency chain lag analysis unit, the dependency chain lag risk of the upstream dependent unit and the lag cause of the downstream unit are judged; the lag cause, lag priority and dependency chain lag risk of each unit are stored in the governance progress data table.

[0015] It also includes a dependency chain lag analysis unit, which is used to obtain dependency information of problem data governance tasks, determine the dependency chain lag risk of upstream dependent units and the lag reasons of downstream units, specifically including:

[0016] Through the data governance platform of the ultra-high voltage transmission company, the dependency information of the current problem data governance task is obtained and stored in the governance progress data table. The dependency information includes the upstream dependent units of each unit task, the data transmission timestamp and the data type; through the governance progress data table, the update status of the governance progress data of the upstream dependent unit is monitored in real time, the number of rectified data, the number of data to be rectified and the current problem data rectification rate of the upstream dependent unit are obtained, and it is judged whether the governance status of the upstream dependent unit is lagging; if the governance status of the upstream dependent unit is lagging, it is determined that the unit has a dependency chain lag risk, and the dependency chain lag risk is marked to the corresponding field of the governance progress data table; the governance progress data of the downstream unit is obtained. If the problem data rectification rate of the downstream unit continues to be lower than the expected rectification rate threshold after the upstream dependent unit data lags, it is judged that the governance status of the downstream unit is lagging because the progress is slow due to the upstream data lag; the lag reason of the downstream unit is marked as dependent lag, and the lag priority of the upstream dependent unit is marked as high priority lag, and updated to the lag reason field and lag priority field in the governance progress data table.

[0017] Furthermore, the lagging unit reminder module is used to generate the lagging reminder content of each lagging unit according to the lagging reason mark, lagging quantity and governance progress data of each lagging unit, and send it to the corresponding business domain person in charge and governance person in charge, including:

[0018] Through the task reminder component of the data governance platform, the delay reminder content of each lagging unit is generated according to the delay reason mark, delay number and governance progress data of each lagging unit; through the data type of the problem data, the information of the business domain person in charge and the governance person in charge is matched to determine the recipient of each reminder content, and the matched responsible person information is attached to the reminder content; if the delay reason of the lagging unit is the backlog of problem data or the low rectification rate, the delay reminder content is sent by email; if the delay priority of the lagging unit is a high priority delay, the delay reminder content is sent by both SMS and email; obtain the sending confirmation receipt, and resend the reminder content that was not successfully sent according to the feedback of successful or failed sending until it is successfully sent; the elevator posture monitoring module is used to update the data governance progress trend chart according to the rectification status data of each unit after the delay reminder, and generate new delay reminder content for units that do not meet the predetermined governance standards.

[0019] Furthermore, the rectification efficiency identification module is used to update the data governance progress trend chart according to the rectification status data of each unit after the delayed reminder, and generate new delayed reminder content for units that fail to meet the predetermined governance standards, including:

[0020] Obtain the rectification status data of each unit after the delayed reminder, and update the data governance progress trend chart. The rectification status data includes the number of data that have been rectified, the number of problem data to be rectified, and the number of new problems; according to the updated data governance progress trend chart, obtain the governance progress data of each unit in real time, including the number of data that have been rectified, the number of problem data to be rectified, and the rectification rate of problem data, and judge whether the rectification progress of problem data meets the predetermined governance standards based on the preset rectification rate threshold and the preset quantity threshold; if the predetermined governance standards are not met, mark the rectification status of the unit as requiring another reminder, determine the reason for the delay of the unit, and generate new delay reminder content; send the new delay reminder content to the business domain manager and the governance manager through the delayed unit reminder module, and record the sending status.

[0021] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0022] The present invention provides a data governance optimization system with progress visualization. The present invention automatically acquires and classifies problem data, generates a governance progress view and a problem data rectification rate trend chart and a stage governance effect comparison chart, so that the management can intuitively understand the governance trends and effectiveness of each unit in different time periods. At the same time, the present invention has the functions of analyzing the reasons for lag and risk management of the dependency chain, which can identify the specific reasons for lag of the lagging unit and the governance impact of the upstream dependent unit, so that the management can identify and solve the bottleneck problems in data governance in advance. For the lagging unit, the present invention generates targeted reminder content and sends it to the responsible person, forming a closed-loop reminder and feedback mechanism to ensure the follow-up and implementation of the rectification, and updates the governance progress trend chart according to the rectification status data after the lagging reminder, so as to realize the dynamic tracking of the governance effect. The present invention optimizes the display of data governance, so that the management can fully grasp the governance progress of each unit, realize the real-time, dynamic and intuitive display of information, help the management to quickly identify problems and adjust strategies, and significantly improve the efficiency and quality of data governance work. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A flowchart of a data management optimization system with progress visualization according to the present invention;

[0024] Figure 2 A schematic diagram of a data management optimization system with progress visualization according to the present invention;

[0025] Figure 3 This is another schematic diagram of a data management optimization system with progress visualization according to the present invention. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical strategies and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] like Figure 1-3 In this embodiment, a data governance optimization system with progress visualization may specifically include:

[0028] Step S101, a problem data status acquisition module is used to obtain data record labels of problem data through a data governance platform, determine classification attributes of problem data, and obtain the current problem data status of each unit.

[0029] Through the data governance platform of the ultra-high voltage transmission company, the key information fields of the current problem data of each unit are obtained. The key information fields include data record tags, timestamps and unit identification. The data record tags include but are not limited to monitoring equipment and line status monitoring systems. According to the data record tags, the problem data is mapped to the corresponding data type to obtain the classification attributes of each problem data, and the classification results of each problem data are stored in the additional fields of the data record. The data types include power line monitoring data, equipment status data, fault records, and quality inspection data. Obtain the classified problem data records, and assign different types of data to the corresponding partition database for partition storage according to the classification attributes. According to the data stored in the partitions, obtain the current problem data status of each unit, including the number of problem data, the number of data that has been rectified, and the number of new problems. Compare the changes in the number of data that has been rectified in the current cycle with the changes in the previous data record, obtain the incremental information of the rectification quantity, and update it to the data governance record table of each unit.

[0030] Exemplarily, through the data governance platform of the ultra-high voltage transmission company, the problem data of unit A is obtained, and the key information fields include the data record label as monitoring equipment, the timestamp as 2021-10-1508:30:00, and the unit identification as unit A. According to the data record label monitoring equipment, the problem data is mapped to the power line monitoring data type, and the classification result is stored in the additional field of the data record. If there are 50 power line monitoring data, 30 equipment status data, 10 fault records and 20 quality inspection data in the data of unit A. After classification processing, these different types of data are respectively allocated to the power line monitoring data, equipment status data, fault record and quality inspection data partition database for partition storage. According to the partitioned stored data, the current problem data status of unit A is obtained, of which the total number of problem data is 110, the number of data that has been rectified is 40, and the number of newly added problem data is 15. If the number of data completed in the previous cycle is 30, the number of rectified data in the current cycle is compared with the change in the previous data record, and the increment of the rectification number is 10. The incremental information is updated in the data governance record table of Unit A to track governance progress and support decision-making.

[0031] Step S102, the data governance trend display module is used to generate a problem data governance progress view according to the problem data status of each unit, and generate a problem data rectification rate trend chart and a stage governance effect comparison chart based on the data governance progress trend analysis results.

[0032] According to the data stored in the partition, the problem data status of each unit is obtained, including the number of problem data, the number of data that have been rectified, and the number of new problems. Through the data visualization component, according to the number of problem data of each unit, the number of problem data that have been rectified, the number of problem data to be rectified, and the number of new problems, a problem data governance progress view is generated to monitor the data governance status of each unit in real time. If the problem data status is detected to be updated, the problem data governance progress view is updated. According to the data governance record table of each unit in the data governance platform and the current problem data status, the problem data status of each unit at different time nodes is obtained. The problem data rectification rate of each unit at each time node is calculated by problem data rectification rate = number of data that have been rectified / (number of data that have been rectified + number of problems to be rectified + number of new problems), and the problem data rectification rate data set is formed by arranging them according to timestamps. The time series data of the problem data rectification rate of each unit is regressed and modeled by regression analysis algorithm, and the data governance progress trend line of each unit is fitted. Based on the slope of each trend line, the data rectification speed and progress direction of each unit are obtained. By calculating the average problem data rectification rate of each unit in different time periods, the data governance effect at different stages of the governance progress can be judged. Through the data visualization component, based on the results of the data governance progress trend analysis, a line chart is used to generate a problem data rectification rate trend chart to show the trend of the problem data rectification rate of each unit, and a bar chart is used to generate a stage governance effect comparison chart to show the changes in the governance effect of each unit in different time periods. According to the data visualization rules, a multi-dimensional chart report containing a problem data rectification rate trend chart and a stage governance effect comparison chart is generated to form a graphical display of governance progress and trends. Through the automatic report generation component, a text summary of the governance progress, rectification rate trend, and governance effect changes of each unit is generated, and a trend analysis report is generated in combination with the chart display, and the report is uploaded to the data governance platform.

[0033] Exemplarily, the problem data status of unit B is obtained through the data stored in the partitions, where the total number of problem data is 120, the number of data that has been rectified is 50, and the number of new problems is 20. Using the data visualization component, based on the number of 50 problem data that have been rectified, 70 problem data to be rectified, and 20 new problems of unit B, a problem data governance progress view of unit B is generated. The data change detection algorithm is used to monitor the data governance status of unit B in real time. When it is detected that the number of new problems increases from 20 to 25, the chart refresh operation is automatically triggered to update the problem data governance progress view. In the data governance platform, the problem data status of unit C at different time nodes is obtained. For example, at the first time node, early January, the number of rectified data of unit C is 40, the number of problems to be rectified is 60, and the number of new problems is 10. According to the formula problem data rectification rate = number of rectified data / (number of rectified data + number of problems to be rectified + number of new problems), the problem data rectification rate of unit C at the beginning of January is calculated as

[0034] 40 / (40+60+10)=0.4, i.e. 40%. At the next time node, early February, the number of data that has been rectified in C unit is updated to 70, the number of problems to be rectified is reduced to 40, and the number of new problems is increased to 15. The rectification rate at the beginning of February is calculated to be 70 / (70+40+15)=0.54, i.e. 54%. The rectification rate calculation results are arranged according to the timestamp to form a time series data set of the problem data rectification rate of C unit. Subsequently, the regression analysis algorithm is used to perform regression modeling on the rectification rate time series data of C unit, and the data governance progress trend line of C unit is fitted. According to the slope of the trend line, it is concluded that the data rectification speed of C unit increases by about 0.14 per month, i.e. 14%, showing a trend of gradual improvement in the governance progress of C unit. By calculating the average rectification rate of problem data in different time periods, it is judged that the average rectification rate of C unit in January is 40%, while the average rectification rate in February is increased to 54%, indicating that the data governance effect in February has been significantly improved. Based on the data visualization component, a trend chart of the problem data rectification rate of C unit was generated, and a line chart was used to show the increase in the rectification rate from early January to early February. At the same time, a comparison chart of the governance effect of each stage was generated, and a bar chart was used to compare the average rectification rates in January and February to show the changes in the governance effect at each stage. Through the automatic report generation component, a textual summary of the governance progress, rectification rate trend and governance effect changes of C unit was generated. For example, the rectification rate of C unit increased from 40% in January to 54% in February, showing a clear trend of improvement in governance progress. This summary was combined with the trend chart and comparison chart to generate a complete trend analysis report and upload it to the data governance platform for management to review and evaluate.

[0035] Step S103, a governance status identification module is used to obtain the governance progress data of each unit, identify the governance status of each unit, and determine the lagging reasons of the lagging units.

[0036] Through the data governance platform of the ultra-high voltage transmission company, the governance progress data of each unit is obtained in real time, including the number of problem data to be rectified, the number of data that have been rectified, and the rectification rate of problem data, and the data is recorded in time series and stored in the governance progress data table. The current problem data rectification rate of each unit is compared with the preset rectification rate threshold, and the number of problem data to be rectified is compared with the preset number threshold. If it is detected that the problem data rectification rate is lower than the preset rectification rate threshold or the number of problem data to be rectified is higher than the preset number threshold, the governance status of the unit is marked as lagging. According to the growth rate of the backlog of problem data of the lagging unit, it is judged whether it belongs to the problem data backlog type lag. If the growth rate of the problem data backlog is greater than the preset growth rate threshold, the cause of the lag is marked as the problem data backlog. According to the problem data rectification rate of each time node of the unit with a lagging governance status, it is judged whether it belongs to the low rectification rate. If the calculated problem data rectification rate is lower than the preset rectification rate threshold for several time periods, the cause of the lag is marked as low rectification rate. If the problem data backlog and the low rectification rate are met at the same time, the lag priority of the unit is marked as high priority lag. Through the dependency chain lag analysis unit, the dependency chain lag risk of the upstream dependent unit and the lag cause of the downstream unit are determined. The lag cause, lag priority and dependency chain lag risk of each unit are stored in the governance progress data table.

[0037] For example, through the data governance platform of the ultra-high voltage transmission company, the governance progress data of the D unit is obtained in real time, and the number of problem data to be rectified in the current D unit is 80, the number of data that have been rectified is 40, and the problem data rectification rate is calculated as 40 / (40+80)=0.33, that is, 33%. These data are recorded in the governance progress data table in time series. The current problem data rectification rate of the D unit is compared with the preset rectification rate threshold of 50%, and it is found that the problem data rectification rate of 33% is lower than the preset threshold of 50%. At the same time, the number of problem data to be rectified in the D unit is 80, which is higher than the preset threshold of 60. Therefore, the governance status of the D unit is marked as lagging, and the data progress status of the D unit in the problem data rectification rate trend chart is marked with color, green indicates smooth governance progress, red indicates lagging progress, where the rectification rate>50% means smooth governance progress, and the rectification rate<50% means slow governance progress. According to the problem data backlog of D unit, the growth rate of the number of problem data is calculated. It is found that the number of problem data to be rectified in D unit has increased at a rate of 10 per week in the past three weeks, which is greater than the preset growth rate threshold of 5 per week. Therefore, the reason for the lag is marked as the backlog of problem data. According to the problem data rectification rate of D unit at different time nodes, it is judged whether there is a problem of low rectification rate. If the problem data rectification rate of D unit in the past three time nodes, that is, in three weeks, is 30%, 32% and 33% respectively, which are all lower than the preset 50% rectification rate threshold, the reason for the lag is further marked as low rectification rate. Since D unit meets both the problem data backlog standard and the low rectification rate condition, the lag priority of the unit is marked as high priority lag. Through the dependency chain lag analysis unit, the dependency chain lag risk of the upstream dependent unit and the lag cause of the downstream unit are judged. The lag cause, lag priority and dependency chain lag risk of each unit are stored in the governance progress data table for subsequent reminders and key follow-up.

[0038] Among them, the dependency chain lag analysis unit is used to obtain the dependency information of the problem data governance task, determine the dependency chain lag risk of the upstream dependent unit and the lag reasons of the downstream unit.

[0039] Through the data governance platform of the ultra-high voltage transmission company, the dependency information of the current problem data governance task is obtained and stored in the governance progress data table. The dependency information includes the upstream dependent units of each unit task, the data transfer timestamp and the data type. Through the governance progress data table, the update status of the governance progress data of the upstream dependent unit is monitored in real time, the number of rectified data, the number of data to be rectified and the current problem data rectification rate of the upstream dependent unit are obtained, and the governance status of the upstream dependent unit is judged to be lagging. If the governance status of the upstream dependent unit is lagging, it is determined that the unit has a dependency chain lag risk, and the dependency chain lag risk is marked to the corresponding field of the governance progress data table. The governance progress data of the downstream unit is obtained. If the problem data rectification rate of the downstream unit continues to be lower than the expected rectification rate threshold after the upstream dependent unit data lags, it is judged that the governance status of the downstream unit is lagging because the progress is slow due to the upstream data lag. The lag reason of the downstream unit is marked as dependent lag, and the lag priority of the upstream dependent unit is marked as high priority lag, and updated to the lag reason field and lag priority field in the governance progress data table.

[0040] For example, on the data governance platform of the ultra-high voltage transmission company, the dependency information of the problem data governance task of unit F is obtained, showing that its upstream dependent unit is unit E, the last timestamp of data transmission is 2020-02-0112:00:00, and the data type is power line monitoring data. This dependency information is stored in the governance progress data table. Through the governance progress data table, it is monitored that the number of rectified data of unit E is 60, the number of data to be rectified is 90, and the current problem data rectification rate is 40%, which is lower than the set rectification rate threshold of 50%. Since the rectification rate of unit E continues to be lower than 50%, its governance status is judged to be lagging, and it is judged that unit E has a dependency chain lag risk, and this risk is updated to the governance progress data table. At the same time, the governance progress data of the downstream F unit is obtained. Analysis shows that since the data lag of E unit, the rectification rate of F unit's problem data has been around 35%, while the expected rectification rate threshold is 50%. Therefore, it is judged that the slow progress of F unit is affected by the data lag of E unit, and the lag reason of F unit is marked as dependent lag, and the lag priority of E unit is marked as high priority lag. This information is updated to the lag reason field and lag priority field in the governance progress data table.

[0041] Step S104, the lagging unit reminder module is used to generate the lagging reminder content of each lagging unit according to the lagging reason mark, lagging quantity and governance progress data of each lagging unit, and send it to the corresponding business domain person in charge and governance person in charge.

[0042] Through the task reminder component of the data governance platform, the delayed reminder content of each lagging unit is generated according to the delay reason mark, delay quantity and governance progress data of each lagging unit. According to the data type of the problem data, the information of the business domain person in charge and the governance person in charge is matched to determine the recipient of each reminder content, and the matched responsible person information is attached to the reminder content. If the delay reason of the lagging unit is the backlog of the number of problem data or the low rectification rate, the delay reminder content will be sent by email. If the delay priority of the lagging unit is a high priority delay, the delay reminder content will be sent by SMS and email. Obtain the sending confirmation receipt, and resend the reminder content that was not successfully sent according to the feedback of successful or failed sending until it is successfully sent.

[0043] Exemplarily, the delayed reminder content of Unit G is generated through the task reminder component of the data governance platform. The delayed reason of Unit G is marked as low rectification rate, the number of delayed problem data is 50, and the current governance progress data shows that the rectification rate is only 40%. According to the problem data type device status number of Unit G, its business domain person in charge is matched to N, and the governance person in charge is M. The recipients of the reminder content are determined to be N and M, and the responsible person data table is automatically queried to obtain the name, position and contact information of the relevant person in charge, and the information of the two is attached to the reminder content. Since the delayed reason of Unit G is the low rectification rate, choose to send the reminder content by email. The content of the email reminder includes that the delayed reason of Unit G is low rectification rate, the number of delayed is 50, and the current problem data rectification rate is 40%, and it is sent to the mailboxes of M and N. In another example, the delay priority of H unit is high priority, and the delay reason is the backlog of problem data and the low rectification rate. The delay reminder is sent to the responsible person of H unit by SMS and email. The SMS content includes that the number of delays is 80, the growth rate of backlog problems is 15 new problems per week, and the current problem data rectification rate is 35%. According to the receipt of successful sending, it is recorded in the sending log for subsequent tracking.

[0044] Step S105, a rectification efficiency identification module is used to update the data governance progress trend chart according to the rectification status data of each unit after the delayed reminder, and generate new delayed reminder content for units that have not reached the predetermined governance standards.

[0045] Obtain the rectification status data of each unit after the delayed reminder, and update the data governance progress trend chart. The rectification status data includes the number of data that have been rectified, the number of problem data to be rectified, and the number of new problems. According to the updated data governance progress trend chart, obtain the governance progress data of each unit in real time, including the number of data that have been rectified, the number of problem data to be rectified, and the rectification rate of problem data, and judge whether the rectification progress of problem data meets the predetermined governance standards based on the preset rectification rate threshold and the preset quantity threshold. If the predetermined governance standards are not met, the rectification status of the unit is marked as requiring another reminder, the reason for the delay of the unit is determined, and new delayed reminder content is generated. Through the delayed unit reminder module, the new delayed reminder content is sent to the business domain person in charge and the governance person in charge, and the sending status is recorded.

[0046] Exemplarily, after the delayed reminder, the rectification status data of J unit is obtained, in which the number of data that has been rectified is 60, the number of data to be rectified is reduced to 40, and the number of newly added problems is 10. The rectification increment of J unit before and after the delayed reminder is calculated, and it is found that the number of data that has been rectified has increased from the previous 40 to the current 60, with an increment of 20, indicating that the rectification effect after the delayed reminder is 20, and this increment is updated to the data governance progress trend chart to reflect the latest governance progress. Through the updated data governance progress trend chart, the current governance progress data of J unit is obtained in real time. The data shows that the number of problems to be rectified is 40, the number of problems that have been rectified is 60, and the rectification rate of problem data is 60 / (60+40+10)=0.54, that is, 54%. The calculated problem data rectification rate is compared with the preset rectification rate threshold of 70%, and the number of problems to be rectified 40 is compared with the preset number threshold of 30. It is found that the rectification rate reaches the preset rectification rate threshold of 50% or more, but the number of rectification problems is higher than the preset value of 30. Therefore, the rectification status of J unit is marked as requiring another reminder, the reason for the delay of J unit is identified, and it is determined that its main problem is the backlog of problem data. Then a new delay reminder content is generated, which includes J unit’s current rectification rate of 54%, 40 problems to be rectified, and a specific explanation of the delay reason. It is sent to K, the business domain manager, and L, the governance manager of J unit, and the sending status is recorded after the sending is completed to facilitate subsequent tracking of the rectification effect.

[0047] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the concept of the present application. For example, the above features are replaced with the technical features with similar functions disclosed in the present application (but not limited to) to form a technical solution.

Claims

1. A data management optimization system with progress visualization, characterized in that: The system comprises: The problem data status acquisition module is used to obtain the data record labels of the problem data through the data governance platform, determine the classification attributes of the problem data, and obtain the current problem data status of each unit; The data governance trend display module is used to generate a problem data governance progress view based on the problem data status of each unit, and generate a problem data rectification rate trend chart and a stage governance effect comparison chart based on the data governance progress trend analysis results; The governance status identification module is used to obtain the governance progress data of each unit, identify the governance status of each unit, and determine the reasons for the lag of the lagging units; The lagging unit reminder module is used to generate the lagging reminder content of each lagging unit according to the lagging reason mark, lagging quantity and governance progress data of each lagging unit, and send it to the corresponding business domain person in charge and governance person in charge; The rectification efficiency identification module is used to update the data governance progress trend chart based on the rectification status data of each unit after the delayed reminder, and generate new delayed reminder content for units that have not met the predetermined governance standards.

2. The system according to claim 1, wherein: The problem data status acquisition module is used to obtain the data record label of the problem data through the data governance platform, determine the classification attribute of the problem data, and obtain the current problem data status of each unit, including: Through the data governance platform of the ultra-high voltage transmission company, the key information fields of the current problem data of each unit are obtained. The key information fields include data record tags, timestamps and unit identification. The data record tags include but are not limited to monitoring equipment and line status monitoring systems; according to the data record tags, the problem data is mapped to the corresponding data type to obtain the classification attributes of each problem data, and the classification results of each problem data are stored in the additional fields of the data record. The data types include power line monitoring data, equipment status data, fault records, and quality inspection data; the classified problem data records are obtained, and different types of data are allocated to the corresponding partition databases for partition storage according to the classification attributes; according to the data stored in the partitions, the current problem data status of each unit is obtained, including the number of problem data, the number of data that has been rectified, and the number of new problems. The number of rectified data in the current cycle is compared with the changes in the previous data record to obtain the incremental information of the rectification quantity, and update it to the data governance record table of each unit.

3. The system according to claim 1, wherein: The data governance trend display module is used to generate a problem data governance progress view according to the problem data status of each unit, and generate a problem data rectification rate trend chart and a stage governance effect comparison chart based on the data governance progress trend analysis results, including: According to the data stored in the partitions, the problem data status of each unit is obtained, including the number of problem data, the number of data that have been rectified, and the number of new problems; through the data visualization component, according to the number of problem data of each unit, the number of problem data that have been rectified, the number of problem data to be rectified, and the number of new problems, a problem data governance progress view is generated to monitor the data governance status of each unit in real time. If an update of the problem data status is detected, the problem data governance progress view is updated; according to the data governance record table of each unit in the data governance platform and the current problem data status, the problem data status of each unit at different time nodes is obtained; through the problem data rectification rate = number of rectified data / (number of rectified data + number of problems to be rectified + number of new problems), the problem data rectification rate of each unit at each time node is calculated, and arranged according to timestamps to form a time series problem data rectification rate data set; using the regression analysis algorithm, the problem data rectification rate of each unit is Regression modeling is performed on time series data to fit the data governance progress trend line of each unit. Based on the slope of each trend line, the data rectification speed and progress direction of each unit are obtained; by calculating the average problem data rectification rate of each unit in different time periods, the data governance effect at different stages of the governance progress is judged; through the data visualization component, based on the data governance progress trend analysis results, a problem data rectification rate trend chart is generated using a line chart to show the problem data rectification rate change trend of each unit, and a bar chart is used to generate a stage governance effect comparison chart to show the change in governance effect of each unit in different time periods; according to the data visualization rules, a multi-dimensional chart report containing a problem data rectification rate trend chart and a stage governance effect comparison chart is generated to form a graphical display of governance progress and trends; through the automatic report generation component, a textual summary of the governance progress, rectification rate trend and governance effect changes of each unit is generated, and a trend analysis report is generated in combination with the chart display, and the report is uploaded to the data governance platform.

4. The system according to claim 1, wherein: The governance status identification module is used to obtain the governance progress data of each unit, identify the governance status of each unit, and determine the lagging reasons of the lagging units, including: Through the data governance platform of the ultra-high voltage transmission company, the governance progress data of each unit is obtained in real time, including the number of problem data to be rectified, the number of data that have been rectified, and the rectification rate of problem data, and the data is recorded in time series and stored in the governance progress data table; the current problem data rectification rate of each unit is compared with the preset rectification rate threshold, and the number of problem data to be rectified is compared with the preset number threshold. If it is detected that the problem data rectification rate is lower than the preset rectification rate threshold or the number of problem data to be rectified is higher than the preset number threshold, the governance status of the unit is marked as lagging; according to the growth rate of the backlog of problem data of the lagging unit, it is judged whether it belongs to the problem data backlog type lag; if the problem data backlog is higher than the preset number threshold, the governance status of the unit is marked as lagging; according to the growth rate of the problem data backlog of the lagging unit, it is judged whether it belongs to the problem data backlog type lag. If the growth rate of the pressure quantity is greater than the preset growth rate threshold, the lag reason is marked as a backlog of problem data; according to the problem data rectification rate of each time node of the unit with a lagging governance status, it is judged whether it belongs to a low rectification rate. If the calculated problem data rectification rate is lower than the preset rectification rate threshold for several time periods, the lag reason is marked as a low rectification rate; if both the problem data backlog and the low rectification rate are met at the same time, the lag priority of the unit is marked as a high priority lag; through the dependency chain lag analysis unit, the dependency chain lag risk of the upstream dependent unit and the lag cause of the downstream unit are judged; the lag cause, lag priority and dependency chain lag risk of each unit are stored in the governance progress data table.

5. The system according to claim 4, wherein: The dependency chain lag analysis unit is used to obtain dependency information of the problem data governance task, determine the dependency chain lag risk of the upstream dependent unit and the lag cause of the downstream unit, including: Through the data governance platform of the ultra-high voltage transmission company, the dependency information of the current problem data governance task is obtained and stored in the governance progress data table. The dependency information includes the upstream dependent units of each unit task, the data transmission timestamp and the data type; through the governance progress data table, the update status of the governance progress data of the upstream dependent unit is monitored in real time, the number of rectified data, the number of data to be rectified and the current problem data rectification rate of the upstream dependent unit are obtained, and it is judged whether the governance status of the upstream dependent unit is lagging; if the governance status of the upstream dependent unit is lagging, it is determined that the unit has a dependency chain lag risk, and the dependency chain lag risk is marked to the corresponding field of the governance progress data table; the governance progress data of the downstream unit is obtained. If the problem data rectification rate of the downstream unit continues to be lower than the expected rectification rate threshold after the upstream dependent unit data lags, it is judged that the governance status of the downstream unit is lagging because the progress is slow due to the upstream data lag; the lag reason of the downstream unit is marked as dependent lag, and the lag priority of the upstream dependent unit is marked as high priority lag, and updated to the lag reason field and lag priority field in the governance progress data table.

6. The system according to claim 1, wherein: The lagging unit reminder module is used to generate the lagging reminder content of each lagging unit according to the lagging reason mark, lagging quantity and governance progress data of each lagging unit, and send it to the corresponding business domain person in charge and governance person in charge, including: Through the task reminder component of the data governance platform, the delayed reminder content of each delayed unit is generated according to the delayed reason mark, delayed quantity and governance progress data of each delayed unit; through the data type of the problem data, the information of the business domain person in charge and the governance person in charge is matched to determine the recipient of each reminder content, and the matched responsible person information is attached to the reminder content; If the reason for the lag of the lagging unit is a backlog of problematic data or a low rectification rate, a lag reminder will be sent via email; If the delay unit delay priority is a high priority delay, the delay reminder content is sent by SMS and email; Get the sending confirmation receipt, and resend the reminder content that was not successfully sent according to the feedback of sending success or failure until it is successfully sent; The elevator posture monitoring module is used to update the data management progress trend chart according to the rectification status data of each unit after the delayed reminder, and generate new delayed reminder content for units that fail to meet the predetermined management standards.

7. The system according to claim 1, wherein: The rectification efficiency identification module is used to update the data governance progress trend chart according to the rectification status data of each unit after the delayed reminder, and generate new delayed reminder content for units that fail to meet the predetermined governance standards, including: Obtain the rectification status data of each unit after the delayed reminder, and update the data governance progress trend chart. The rectification status data includes the number of data that have been rectified, the number of problem data to be rectified, and the number of new problems; according to the updated data governance progress trend chart, obtain the governance progress data of each unit in real time, including the number of data that have been rectified, the number of problem data to be rectified, and the rectification rate of problem data, and judge whether the rectification progress of problem data meets the predetermined governance standard based on the preset rectification rate threshold and the preset quantity threshold; if the predetermined governance standard is not met, mark the rectification status of the unit as requiring another reminder, determine the reason for the delay of the unit, and generate new delayed reminder content; Through the delayed unit reminder module, new delayed reminder content is sent to the business domain manager and governance manager, and the sending status is recorded.

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