Project data management method and system

Abstract

The invention discloses a project data management method and system, and the method comprises the steps: collecting a project data set of a target project, dividing the project data set into a plurality of subitem data, the target project comprises a plurality of subitem data, and the subitem data comprises project cost data, project progress data and project completion quality data; storing the plurality of sub-item data in a distributed database based on cloud computing; and based on the sub-item data, calculating a cost health index, a progress health index, a quality health index and an overall health index of the target item to generate a visual data analysis report reflecting the health condition of the item so as to realize management of the item data. By utilizing the embodiment of the invention, real-time acquisition and efficient processing of the project data can be realized, and comprehensive support is provided for project decision through the comprehensive health index evaluation system, so that the project management efficiency and quality are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of project management, and in particular to a project data management method and system. Background Art

[0002] In today's rapidly developing project management field, enterprises and organizations are facing an increasingly complex project environment. Effective project management not only urges projects to be completed within the scheduled time, but also requires them to be carried out within the budget and ensure that the final delivered products or services meet quality standards. However, traditional project management methods often rely on manual records and a single data storage method, leading to data silos, that is, various data in the project are scattered in multiple systems and difficult to share and integrate. This not only affects the real-time and accuracy of the data, but also restricts the effectiveness of project decisions. Summary of the invention

[0003] The purpose of the present invention is to provide a project data management method and system to address the deficiencies in the prior art, to achieve real-time collection and efficient processing of project data, and to provide comprehensive support for project decision-making through a comprehensive health index evaluation system, thereby improving project management efficiency and quality.

[0004] An embodiment of the present application provides a project data management method, the method comprising:

[0005] Collecting a project data set of a target project, dividing the project data set into a plurality of sub-item data, wherein the target project includes a plurality of sub-projects, and the sub-item data includes: project cost data, project progress data, and project completion quality data;

[0006] Storing multiple sub-item data in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high-concurrency reading and writing;

[0007] Based on the sub-item data, the cost health index, schedule health index, quality health index and overall health index of the target project are calculated to generate a visual data analysis report reflecting the health status of the project and realize the management of project data.

[0008] Optionally, the calculation formula of the cost health index is:

[0009]

[0010] Among them, CHI is the cost health index, C_i is the actual cost of the i-th sub-project, B_i is the budget cost of the i-th sub-project, epsilon is a preset small positive number used to avoid division by zero errors, alpha and beta are corresponding adjustable parameters used to emphasize the nonlinear impact of cost overruns, and n is the total number of sub-projects.

[0011] Optionally, the calculation formula of the progress health index is:

[0012]

[0013] Among them, the SHI is the progress health index, the T_i is the actual completion time of the i-th sub-project, the P_i is the planned completion time of the i-th sub-project, and the w_i is the importance weight of the i-th sub-project.

[0014] Optionally, the calculation formula of the quality health index is:

[0015]

[0016] Among them, the QHI is the quality health index, the Q_i is the actual quality score of the i-th sub-project, the V_i is the value coefficient of the i-th sub-project, the T_i is the standard quality score of the i-th sub-project, the C is the total number of customer complaints of the target project, the R is the resource utilization rate of the target project, and the U is the customer satisfaction score of the target project.

[0017] Another embodiment of the present application provides a project data management system, the system comprising:

[0018] A collection module, used for collecting a project data set of a target project, and dividing the project data set into a plurality of sub-item data, wherein the target project includes a plurality of sub-projects, and the sub-item data includes: project cost data, project progress data, and project completion quality data;

[0019] A storage module, used to store multiple sub-item data in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high-concurrency reading and writing;

[0020] The management module is used to calculate the cost health index, progress health index, quality health index and overall health index of the target project based on the sub-item data, so as to generate a visual data analysis report reflecting the health status of the project and realize the management of project data.

[0021] Yet another embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, wherein the computer program is configured to execute any of the above methods when running.

[0022] Yet another embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any of the methods described above.

[0023] Compared with the prior art, the present invention provides a project data management method, which collects a project data set of a target project, divides the project data set into multiple sub-item data, wherein the target project includes multiple sub-projects, and the sub-item data include: project cost data, project progress data and project completion quality data; stores the multiple sub-item data in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high concurrent reading and writing; based on the sub-item data, calculates the cost health index, progress health index and quality health index of the target project as well as the overall health index, so as to generate a visual data analysis report reflecting the health status of the project, realizes the management of project data, thereby enabling real-time collection and efficient processing of project data, and provides comprehensive support for project decision-making through a comprehensive health index evaluation system, thereby improving project management efficiency and quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A hardware structure block diagram of a computer terminal of a project data management method provided by an embodiment of the present invention;

[0025] Figure 2 A flowchart of a project data management method provided by an embodiment of the present invention;

[0026] Figure 3 A schematic diagram of the structure of a project data management system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, but should not be construed as limiting the present invention.

[0028] The embodiment of the present invention first provides a project data management method, which can be applied to electronic devices such as computer terminals, specifically ordinary computers, etc.

[0029] The following describes it in detail by taking running on a computer terminal as an example. Figure 1 The hardware structure block diagram of a computer terminal of a project data management method provided by an embodiment of the present invention. Figure 1As shown, the computer device includes a processor, a memory, and a network interface connected via a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0030] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any project data management method.

[0031] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0032] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any project data management method.

[0033] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0034] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0035] See also Figure 2 , an embodiment of the present invention provides a project data management method, which may include the following steps:

[0036] S201, collecting a project data set of a target project, and dividing the project data set into a plurality of sub-item data, wherein the target project includes a plurality of sub-projects, and the sub-item data includes: project cost data, project progress data, and project completion quality data;

[0037] The first step of this method is to collect the project data set of the target project and divide it into multiple sub-item data. The target project usually contains multiple sub-projects. For example, in a construction project, software development or other types of projects, sub-projects can be individual stages or tasks. This step ensures a comprehensive understanding of the project by systematically collecting various data related to the project. Including data such as project cost, schedule and completion quality allows project managers to break down complex projects into smaller and more manageable parts. This division not only helps to systematically organize and analyze data, but also provides an independent perspective for each sub-project in the subsequent analysis process, so as to better understand its impact on the entire target project.

[0038] By dividing the project data set into multiple sub-item data, this method achieves detailed management and detection of the project. This management method enables the project team to better monitor and analyze the performance of each sub-project, thereby identifying potential problems and risks in a timely manner. For example, if a sub-project has cost overruns or is behind schedule, the project manager can quickly find the cause and take remedial measures by analyzing the corresponding sub-item data. This fine-grained analysis can not only improve the execution efficiency of the overall project, but also make accurate decisions in terms of resource allocation, time management and quality control, thereby increasing the possibility of project success and customer satisfaction.

[0039] In the specific implementation process, first determine the scope and objectives of the target project, and then collect all project-related data through different data collection tools (such as sensors, data entry systems, automated monitoring systems, etc.). The project team needs to design a unified data collection standard to ensure that all subprojects have consistent data recording methods in terms of cost, progress and quality. According to the structure and needs of the project, the data can be classified and divided to form multiple sub-item data sets. Each sub-item data set should contain the corresponding project cost data, progress data and quality data for subsequent analysis. To improve data availability and visualization, the project team can use data analysis tools to integrate the collected sub-item data into a visual dashboard, so that managers can monitor the project status at any time. In addition, the team can regularly review and verify the data to ensure the accuracy and reliability of the data, thereby laying a solid foundation for the subsequent health index calculation. Through such an implementation process, the integrity, accuracy and timeliness of the project data are ensured, providing strong support for the subsequent health index evaluation and project decision-making.

[0040] S202, storing the plurality of sub-item data in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high-concurrency reading and writing;

[0041] The core of this step is to use the flexibility and scalability of cloud computing to ensure that project data can be stored and managed efficiently and securely. In this process, the distributed database system organizes and stores sub-item data in an orderly manner to optimize data access and processing efficiency. The use of data sharding technology means that sub-item data is divided and distributed to multiple storage units according to a certain strategy, thereby reducing the load of a single database node and improving the concurrent processing capability of the system. This design can not only effectively support multiple users to read and write data at the same time, but also ensure the stability and response speed of the system under high load conditions.

[0042] Storing project data in a distributed database based on cloud computing, especially using data sharding technology, is of great significance. First, it significantly improves the efficiency and scalability of data processing, ensuring that data can be accessed and updated in real time during the project process, meeting the high-frequency data access needs. Secondly, the distributed architecture improves the fault tolerance of the system. Even if a node fails, other nodes can continue to operate, ensuring the high availability of project data. In addition, cloud computing solutions provide project teams with flexible storage options, which can dynamically adjust resources according to actual needs, thereby effectively responding to changes in data scale that may occur during project execution. All of this provides more powerful data support for project management, allowing project teams to focus on data analysis and decision-making, rather than being troubled by the complexity of data storage and management.

[0043] In the specific implementation process, it is first necessary to select a suitable cloud computing service provider to support the deployment of distributed databases. The project team should conduct a detailed demand analysis, including requirements for data storage capacity, access speed, and security. After selecting a service provider, the team can create a distributed database cluster and configure a data sharding strategy, such as sharding based on factors such as the category of project sub-items, data size, or access frequency. Next, the collected data of multiple sub-items is sorted and standardized to ensure the consistency of the data format for subsequent storage.

[0044] During the data storage process, data middleware is needed to shard and distribute sub-item data to different nodes in the cluster, so as to achieve load balancing and avoid overloading of a single node. At the same time, the team should implement a regular data backup mechanism to prevent data loss and provide data recovery capabilities. In addition, reasonable user permissions and security policies should be configured to protect sensitive data and ensure that only authorized personnel can access or modify the corresponding data. Through the above implementation steps, project data can be stored efficiently and securely in the distributed environment of cloud computing, and provide strong support for subsequent analysis and decision-making. Finally, the project team can use visualization tools to monitor the data status in real time, so as to flexibly adjust the management strategy according to the progress of the project and ensure the smooth realization of project goals.

[0045] S203, based on the sub-item data, calculate the cost health index, schedule health index, quality health index and overall health index of the target project to generate a visual data analysis report reflecting the health status of the project and realize the management of project data.

[0046] The key to this project data management method is to calculate the health index of the target project based on the collected sub-item data, including the cost health index, schedule health index and quality health index. These indexes reflect the comprehensive performance of the project in terms of cost control, schedule scheduling and quality control, and can provide a scientific basis for project management decisions. By analyzing data such as the actual cost, actual completion time and quality score of each sub-project and using specific calculation formulas, the project management team can quantify the health status of the project, identify potential problems in a timely manner and take corresponding measures to make adjustments, thereby ensuring that the project is effectively promoted according to the established goals. In addition, the generated visual data analysis report intuitively displays the health status of the project in a graphical form, which helps different stakeholders (such as project managers, customers and team members) quickly understand the current status of the project and promote information sharing and communication.

[0047] Through the above calculation method, the project management team can comprehensively monitor and evaluate the health of the target project, and promptly identify risks such as cost overruns, schedule delays, and substandard quality. This method not only improves the transparency and controllability of project management, but also provides data-based support for decision-making, allowing management to respond to various challenges in the project with higher efficiency and accuracy. In addition, the use of visual data analysis reports can effectively reduce cognitive errors in information transmission, fully mobilize the enthusiasm and sense of responsibility of the project team, and ensure that each sub-project can move towards the overall goal in a coordinated manner. Ultimately, the calculation and analysis of the project health index will promote the rational allocation of resources, enhance the flexibility of project management, and improve the overall success rate of the project.

[0048] To implement the above project data management method, first of all, the project team needs to conduct systematic data collection and summarize the relevant data of all sub-projects in the target project, including project cost, progress and quality information. These data should be organized according to the preset format to ensure the accuracy and consistency of subsequent calculations. Subsequently, the team can use data analysis tools to process the collected data and apply the corresponding formulas to calculate the cost health index (CHI), schedule health index (SHI) and quality health index (QHI). During the calculation process, the team needs to ensure that all parameters are set reasonably, such as the difference between budgeted cost and actual cost, the comparison between planned completion time and actual completion time, and the quality score and value coefficient of each sub-project.

[0049] After the calculation is completed, the specific values ​​of each health index will be obtained, which will then be integrated into the overall health index, for example, the weighted sum of each health index is used to obtain the overall health index to comprehensively reflect the management status of the project. The project team should use data visualization tools to generate graphical reports and present the calculation results in an easy-to-understand way. The report can contain a variety of graphics such as trend charts and bar charts to help stakeholders intuitively understand the health status of the project. In addition, a regular report generation mechanism must be set up to ensure that the project team keeps up with the changes in the project. In this way, dynamic monitoring of the health status of the project can be achieved, problems can be discovered and adjusted in a timely manner, thereby optimizing the project management strategy and improving the project implementation effect. In combination with the implementation of project management software, the team can also set up automated reminders so that when key indicators are abnormal, relevant personnel can be notified in time to intervene to ensure the smooth achievement of project goals.

[0050] Specifically, a calculation formula for the cost health index can be:

[0051]

[0052] The Cost Health Index (CHI) is designed to comprehensively reflect the cost control ability of a project by quantifying the actual expenditure of the project cost compared with the budget. The formula not only focuses on the absolute value of cost overruns, but also introduces nonlinear parameters to more accurately reflect the impact of cost overruns on project health. By combining multiple factors, CHI can provide project managers with a clear view of cost health, helping them identify potential financial risks and take appropriate measures to intervene.

[0053] Wherein, CHI is the cost health index, C_i is the actual cost of the ith sub-project, B_i is the budget cost of the ith sub-project, epsilon is a preset small positive number used to avoid zero division errors, alpha and beta are corresponding adjustable parameters, alpha is used to emphasize the nonlinear impact of cost overruns. By adjusting this parameter, the project manager's attention to the degree of overruns can be flexibly reflected. Beta adjusts the weight of the overrun impact in the whole formula, allowing managers to adjust the sensitivity to cost health according to different project needs. n is the total number of sub-projects.

[0054] Specifically, a calculation formula for the progress health index can be:

[0055]

[0056] The design of the Schedule Health Index (SHI) aims to comprehensively consider the difference between the actual progress and the planned progress of each sub-project of the project to quantitatively evaluate the efficiency and effectiveness of the project in time management. The formula maximizes the ratio of the degree of lag to the planned completion time, combined with the importance weight of each sub-project, to ensure that the evaluation not only focuses on the deviation of the progress, but also considers the contribution of each sub-project to the overall project success, thus providing a comprehensive schedule health assessment tool.

[0057] Among them, SHI is the schedule health index, T_i is the actual completion time of the ith subproject, P_i is the planned completion time of the ith subproject, and w_i is the importance weight of the ith subproject, which reflects the relative importance of each subproject in the overall project schedule. Different subprojects may have different impacts on project success, so by assigning importance weights to each subproject, it helps to highlight the schedule impact of key projects in the calculation.

[0058] Specifically, a calculation formula for the quality health index can be:

[0059]

[0060] The design of the Quality Health Index (QHI) is to comprehensively evaluate the gap between the actual quality and expected quality of each sub-item of the project, while taking into account external factors such as customer feedback and satisfaction. The formula comprehensively reflects the quality control level and customer satisfaction of the project by combining quality scores, value coefficients and customer complaints, thus providing a strong basis for the quality management decision of the project.

[0061] Among them, the QHI is the quality health index, the Q_i is the actual quality score of the ith subproject, which directly reflects the delivery quality of the subproject and is an important basis for evaluating the health of the project. The V_i is the value coefficient of the ith subproject, which represents the value brought by the subproject to the overall project and reflects the importance of the quality score in the project. The T_i is the standard quality score of the ith subproject, which is used as a benchmark for quality assessment to compare the gap between actual quality and expected quality. The C is the total number of customer complaints for the target project, which reflects the direct feedback from customers on the quality of the project and is an important indicator for project managers to judge whether the quality meets customer expectations. The R is the resource utilization rate of the target project, which refers to the proportion of resources consumed by the project in the process of completing the quality target, affecting the efficiency and benefits of the project. The U is the customer satisfaction score of the target project, indicating the overall evaluation of the project by the customer, which brings together customer feedback on quality, progress, service and other aspects, and is a key dimension reflecting the success of the project.

[0062] It can be seen that the project data set of the target project is collected, and the project data set is divided into multiple sub-item data, wherein the target project contains multiple sub-projects, and the sub-item data include: project cost data, project progress data and project completion quality data; the multiple sub-item data are stored in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high concurrent reading and writing; based on the sub-item data, the cost health index, progress health index and quality health index of the target project and the overall health index are calculated to generate a visual data analysis report reflecting the health status of the project, realize the management of project data, thereby realizing real-time collection and efficient processing of project data, and providing comprehensive support for project decision-making through a comprehensive health index evaluation system, thereby improving project management efficiency and quality.

[0063] Another embodiment of the present invention provides a project data management system, see Figure 3 , the system may include:

[0064] The collection module 301 is used to collect a project data set of a target project, and divide the project data set into a plurality of sub-item data, wherein the target project includes a plurality of sub-projects, and the sub-item data includes: project cost data, project progress data, and project completion quality data;

[0065] A storage module 302 is used to store multiple sub-item data in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high-concurrency reading and writing;

[0066] The management module 303 is used to calculate the cost health index, progress health index, quality health index and overall health index of the target project based on the sub-item data, so as to generate a visual data analysis report reflecting the health status of the project and realize the management of project data.

[0067] It can be seen that the project data set of the target project is collected, and the project data set is divided into multiple sub-item data, wherein the target project contains multiple sub-projects, and the sub-item data include: project cost data, project progress data and project completion quality data; the multiple sub-item data are stored in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high concurrent reading and writing; based on the sub-item data, the cost health index, progress health index and quality health index of the target project and the overall health index are calculated to generate a visual data analysis report reflecting the health status of the project, realize the management of project data, thereby realizing real-time collection and efficient processing of project data, and providing comprehensive support for project decision-making through a comprehensive health index evaluation system, thereby improving project management efficiency and quality.

[0068] An embodiment of the present invention further provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0069] Specifically, in this embodiment, the above storage medium may be configured to store a computer program for performing the following steps:

[0070] S201, converting an input large data set into a quantized data set at a communication transmitting end;

[0071] S202, extracting chaotic features from the quantized data set to generate an initial symmetric key;

[0072] S203, performing deep chaotic transformation enhancement on the initial symmetric key to obtain an enhanced symmetric key;

[0073] S204, performing an encryption operation on the quantized data set using the enhanced symmetric key to obtain an encrypted data set;

[0074] S205, encoding the encrypted data set into a quantum bit carrier, and transmitting it to a communication receiving end through quantum entanglement, so that the communication receiving end can decrypt and calculate a data integrity index to verify the integrity and consistency of the data.

[0075] It can be seen that the project data set of the target project is collected, and the project data set is divided into multiple sub-item data, wherein the target project contains multiple sub-projects, and the sub-item data include: project cost data, project progress data and project completion quality data; the multiple sub-item data are stored in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high concurrent reading and writing; based on the sub-item data, the cost health index, progress health index and quality health index of the target project and the overall health index are calculated to generate a visual data analysis report reflecting the health status of the project, realize the management of project data, thereby realizing real-time collection and efficient processing of project data, and providing comprehensive support for project decision-making through a comprehensive health index evaluation system, thereby improving project management efficiency and quality.

[0076] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0077] Specifically, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0078] Specifically, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0079] S201, converting an input large data set into a quantized data set at a communication transmitting end;

[0080] S202, extracting chaotic features from the quantized data set to generate an initial symmetric key;

[0081] S203, performing deep chaotic transformation enhancement on the initial symmetric key to obtain an enhanced symmetric key;

[0082] S204, performing an encryption operation on the quantized data set using the enhanced symmetric key to obtain an encrypted data set;

[0083] S205, encoding the encrypted data set into a quantum bit carrier, and transmitting it to a communication receiving end through quantum entanglement, so that the communication receiving end can decrypt and calculate a data integrity index to verify the integrity and consistency of the data.

[0084] It can be seen that the project data set of the target project is collected, and the project data set is divided into multiple sub-item data, wherein the target project contains multiple sub-projects, and the sub-item data include: project cost data, project progress data and project completion quality data; the multiple sub-item data are stored in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high concurrent reading and writing; based on the sub-item data, the cost health index, progress health index and quality health index of the target project and the overall health index are calculated to generate a visual data analysis report reflecting the health status of the project, realize the management of project data, thereby realizing real-time collection and efficient processing of project data, and providing comprehensive support for project decision-making through a comprehensive health index evaluation system, thereby improving project management efficiency and quality.

[0085] The above describes in detail the structure, features and effects of the present invention based on the embodiments shown in the drawings. The above is only a preferred embodiment of the present invention, but the present invention is not limited to the scope of implementation shown in the drawings. Any changes made according to the concept of the present invention, or modifications to equivalent embodiments with equivalent changes, which still do not exceed the spirit covered by the description and drawings, should be within the protection scope of the present invention.

Claims

1. A project data management method, characterized in that: The method comprises: Collecting a project data set of a target project, dividing the project data set into a plurality of sub-item data, wherein the target project includes a plurality of sub-projects, and the sub-item data includes: project cost data, project progress data, and project completion quality data; Storing multiple sub-item data in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high-concurrency reading and writing; Based on the sub-item data, the cost health index, schedule health index, quality health index and overall health index of the target project are calculated to generate a visual data analysis report reflecting the health status of the project and realize the management of project data.

2. The method according to claim 1, characterized in that The calculation formula of the cost health index is: Among them, CHI is the cost health index, C_i is the actual cost of the i-th sub-project, B_i is the budget cost of the i-th sub-project, epsilon is a preset small positive number used to avoid division by zero errors, alpha and beta are corresponding adjustable parameters used to emphasize the nonlinear impact of cost overruns, and n is the total number of sub-projects.

3. The method according to claim 2, characterized in that The calculation formula of the progress health index is: Among them, the SHI is the progress health index, the T_i is the actual completion time of the i-th sub-project, the P_i is the planned completion time of the i-th sub-project, and the w_i is the importance weight of the i-th sub-project.

4. The method according to claim 3, characterized in that The calculation formula of the quality health index is: Among them, the QHI is the quality health index, the Q_I is the actual quality score of the i-th sub-project, the V_i is the value coefficient of the i-th sub-project, the T_i is the standard quality score of the i-th sub-project, the C is the total number of customer complaints of the target project, the R is the resource utilization rate of the target project, and the U is the customer satisfaction score of the target project.

5. A project data management system, characterized in that: The system comprises: A collection module, used for collecting a project data set of a target project, and dividing the project data set into a plurality of sub-item data, wherein the target project includes a plurality of sub-projects, and the sub-item data includes: project cost data, project progress data, and project completion quality data; A storage module, used to store multiple sub-item data in a distributed database based on cloud computing, wherein the distributed database adopts data sharding technology to achieve high-concurrency reading and writing; The management module is used to calculate the cost health index, progress health index, quality health index and overall health index of the target project based on the sub-item data, so as to generate a visual data analysis report reflecting the health status of the project and realize the management of project data.

6. The system according to claim 5, characterized in that The calculation formula of the cost health index is: Among them, CHI is the cost health index, C_i is the actual cost of the i-th sub-project, B_i is the budget cost of the i-th sub-project, epsilon is a preset small positive number used to avoid division by zero errors, alpha and beta are corresponding adjustable parameters used to emphasize the nonlinear impact of cost overruns, and n is the total number of sub-projects.

7. The system according to claim 6, characterized in that The calculation formula of the progress health index is: Among them, the SHI is the progress health index, the T_i is the actual completion time of the i-th sub-project, the P_i is the planned completion time of the i-th sub-project, and the w_i is the importance weight of the i-th sub-project.

8. The system according to claim 7, characterized in that The calculation formula of the quality health index is: Among them, the QHI is the quality health index, the Q_i is the actual quality score of the i-th sub-project, the V_i is the value coefficient of the i-th sub-project, the T_i is the standard quality score of the i-th sub-project, the C is the total number of customer complaints of the target project, the R is the resource utilization rate of the target project, and the U is the customer satisfaction score of the target project.

9. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 4 when executed.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 4.

Images