CN115983625A - Project execution risk assessment system based on data analysis - Google Patents
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Abstract
The invention belongs to the field of project risk assessment, relates to a data analysis technology, and is used for solving the problem that the conventional project execution risk assessment system cannot perform deep analysis on a project of which a decision label is assumed and shared so as to achieve the purpose of minimizing risks, in particular to a project execution risk assessment system based on data analysis, which comprises a risk assessment platform, wherein the risk assessment platform is in communication connection with a risk assessment module, a decision analysis module, a risk simulation module and a storage module; the risk assessment module is configured to perform a project risk assessment analysis prior to execution of a project: marking the item for risk assessment as an assessment object, and acquiring authority data QX, volume data TL and sensitive data MG of the assessment object; the method and the system can perform project risk assessment analysis before project execution, are beneficial to risk decision making for users, record and store assessment coefficients, and provide data support for subsequent risk simulation.
Description
Technical Field
The invention belongs to the field of project risk assessment, relates to a data analysis technology, and particularly relates to a project execution risk assessment system based on data analysis.
Background
No matter products or enterprises, data are required to be collected through channels and analyzed in combination with current situations of the enterprises, quantitative risks are important components for making important business decisions, most enterprise organizations evaluate risks through previous experiences and business acuteness, and for the enterprises, the data analysis is used for risk evaluation.
The conventional project execution risk evaluation system can only evaluate the risk faced by project execution, but cannot perform decision analysis on the project execution according to the risk evaluation result, and cannot perform deep analysis on the project of which the decision tag is assumed and shared so as to achieve the purpose of minimizing the risk.
In view of the above technical solutions, the present application provides a solution.
Disclosure of Invention
The invention aims to provide a project execution risk assessment system based on data analysis, which is used for solving the problem that the conventional project execution risk assessment system cannot perform deep analysis on projects with decision tags being assumed and shared so as to achieve the purpose of minimizing risks;
the technical problems to be solved by the invention are as follows: how to provide a project execution risk assessment system for deeply analyzing the project borne and shared by the decision tags so as to achieve the purpose of minimizing the risk.
The purpose of the invention can be realized by the following technical scheme:
a project execution risk assessment system based on data analysis comprises a risk assessment platform, wherein the risk assessment platform is in communication connection with a risk assessment module, a decision analysis module, a risk simulation module and a storage module;
the risk assessment module is configured to perform a project risk assessment analysis prior to execution of a project: marking the item for risk assessment as an assessment object, and acquiring authority data QX, volume data TL and sensitive data MG of the assessment object; obtaining an evaluation coefficient PG of the evaluation object by carrying out numerical calculation on the authority data QX, the volume data TL and the sensitive data MG of the evaluation object; sending the evaluation coefficient PG of the evaluation object to a risk evaluation platform, and sending the received evaluation coefficient PG of the evaluation object to a decision analysis module by the risk evaluation platform;
the decision analysis module is used for processing decision analysis on the evaluation object through the evaluation coefficient PG: acquiring evaluation thresholds PGmin and PGmax through a storage module, wherein PGmin is a minimum evaluation threshold and PGmax is a maximum evaluation threshold, numerically comparing an evaluation coefficient PG with the evaluation thresholds PGmin and PGmax, and marking a decision tag according to a comparison result;
the risk simulation module is used for carrying out risk simulation analysis on the evaluation object.
In a preferred embodiment of the present invention, the authority data QX is the number of administrators with legal authority to access data in the evaluation object, the volume data TL is the total memory value of the management data in the evaluation object, and the sensitive data MG is the total memory value of the sensitive data in the evaluation object.
As a preferred embodiment of the present invention, the specific process of numerically comparing the evaluation coefficient PG with the evaluation thresholds PGmin and PGmax includes:
if PG is less than or equal to PGmin, judging that the risk evaluation of the evaluation object is qualified, and marking the decision label as undertaking;
if PGmin is less than PG and less than PGmax, judging that the risk evaluation of the evaluation object is unqualified, and marking the decision label as sharing;
if PG is larger than or equal to PGmax, judging that the risk evaluation of the evaluation object is unqualified, and marking the decision label as evasion;
and screening and analyzing the evaluation objects shared by the decision tags.
As a preferred embodiment of the present invention, the specific process of performing screening analysis on the evaluation object whose decision tag is shared includes: marking a third-party platform which meets the sharing requirement as a screening object, and acquiring qualification data ZZ, registration data ZC and processing data CL of the screening object, wherein the qualification data ZZ is a registered capital value of the screening object and is in units of ten million, the registration data ZC is the number of registered employees of the screening object and is in units of hundred, and the processing data CL is the number of risk items processed by the screening object in the last L1 month; obtaining a recommendation coefficient TJ of the screening object by carrying out numerical calculation on qualification data ZZ, registration data ZC and processing data CL of the screening object;
and marking the L2 screening objects with the maximum recommendation coefficient TJ value as sharing objects, sending the sharing objects to a risk evaluation platform, and sending the sharing objects to a mobile phone terminal of a manager after the risk evaluation platform receives the sharing objects.
As a preferred embodiment of the present invention, the risk simulation module is configured to perform risk simulation analysis on the evaluation object: marking an evaluation object with a decision label as a bearing object, acquiring an evaluation coefficient executed by a historical project through a storage module, forming an evaluation range by the maximum value and the minimum value of the evaluation coefficient, dividing the evaluation range into a plurality of evaluation intervals, marking the evaluation interval corresponding to the evaluation coefficient of the bearing object as a matching interval, marking a historical execution project in the matching interval as a matching project, setting a simulation cycle, executing the project on the evaluation object in the simulation cycle, setting an analysis time point i, i =1,2, 8230, n, n is a positive integer in the simulation cycle, acquiring intrusion data RQI and leakage data Xli executed by the project at the analysis time point, and obtaining an execution coefficient ZXi of the project XLI at the analysis time point through numerical calculation of the intrusion data RQI and the leakage data; after the simulation period is finished, calling the execution coefficients of the matched items at each analysis time point in the simulation period and marking the execution coefficients as LSi, and obtaining the LSi through a formula
Obtaining a matching coefficient PP of a matching item, marking the matching item with the minimum value of the matching coefficient PP as a simulation object of an undertaking object, calling historical execution data of the simulation object and sending the historical execution data to a risk evaluation platform, and sending the historical execution data of the simulation object to a mobile phone terminal of a manager after the risk evaluation platform receives the historical execution data of the simulation object;
the historical execution data of the simulation object includes profit data, investment data, and maintenance data.
As a preferred embodiment of the present invention, the intrusion data RQi is the number of network intrusions received by the execution of the item before the analysis time point, and the leakage data XLi is the number of internal data leaks received by the execution of the item before the analysis time point.
As a preferred embodiment of the present invention, the method for operating a data analysis-based project execution risk assessment system includes the steps of:
the method comprises the following steps: project risk assessment analysis is performed prior to project execution: marking the item for risk evaluation as an evaluation object, acquiring authority data QX, volume data TL and sensitive data MG of the evaluation object, performing numerical calculation to obtain an evaluation coefficient PG of the evaluation object, and sending the evaluation coefficient PG to a decision analysis module;
step two: and (3) performing processing decision analysis on the evaluation object through the evaluation coefficient PG: obtaining evaluation threshold values PGmin and PGmax through a storage module, carrying out numerical comparison on the evaluation coefficient PG and the evaluation threshold values PGmin and PGmax, and marking the decision-making label as sharing, undertaking or avoiding through a comparison result;
step three: and after receiving the historical execution data of the simulation object, the risk evaluation platform sends the historical execution data of the simulation object to a mobile phone terminal of a manager.
The invention has the following beneficial effects:
1. the risk evaluation module can perform project risk evaluation analysis before project execution, obtain evaluation coefficients by performing comprehensive calculation processing on various parameters of project execution, perform visual feedback on project risks through the numerical value of the evaluation coefficients, facilitate risk decision making for users, record and store the evaluation coefficients and provide data support for subsequent risk simulation;
2. the decision analysis module can process and perform decision analysis on the evaluation object through the evaluation coefficient PG to mark a decision tag of the evaluation object, so that decision recommendation feedback is performed on project execution according to the decision tag, subjective judgment interference of managers is reduced, an objective decision scheme is given through data analysis, and meanwhile, a plurality of most suitable third party platforms are obtained as alternative targets directly through screening, analyzing and screening aiming at projects with the decision tag being shared, and the sharing and screening process is simplified;
3. the risk simulation module can be used for carrying out risk simulation analysis on the evaluation object, history items with the closest initial risk degree are screened for the undertaking object through the numerical value of the evaluation coefficient, so that the risk change process of the history items is analyzed in a simulation period, the history items with the closest risk change curve to the undertaking object in the simulation period are marked as simulation objects, and the execution risk of the undertaking object is predicted according to the execution risk curve of the simulation objects.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of a system according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a method according to a second embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described below clearly and completely in conjunction with the embodiments, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
As shown in fig. 1, a project execution risk assessment system based on data analysis includes a risk assessment platform, which is communicatively connected with a risk assessment module, a decision analysis module, a risk simulation module, and a storage module.
The risk assessment module is used for performing project risk assessment analysis before the project is executed: marking a project subjected to risk assessment as an assessment object, and acquiring authority data QX, volume data TL and sensitive data MG of the assessment object, wherein the authority data QX is the number of administrators who have legal data access authority in the assessment object, the volume data TL is the total memory value of management data in the assessment object, the sensitive data MG is the total memory value of sensitive data in the assessment object, and the sensitive data comprises a user account, a drawing and data needing encryption storage; obtaining an evaluation coefficient PG of an evaluation object through a formula PG = alpha 1 × MG + alpha 2 × QX + alpha 3 × TL, wherein the evaluation coefficient is a numerical value reflecting the high or low risk degree of the evaluation object, and the larger the numerical value of the evaluation coefficient is, the higher the risk degree of the evaluation object is, wherein alpha 1, alpha 2 and alpha 3 are proportional coefficients, and alpha 1 > alpha 2 > alpha 3 > 1; sending the evaluation coefficient PG of the evaluation object to a risk evaluation platform, and sending the received evaluation coefficient PG of the evaluation object to a decision analysis module by the risk evaluation platform; the method comprises the steps of performing project risk assessment analysis before project execution, performing comprehensive calculation processing on various parameters of the project execution to obtain an assessment coefficient, performing visual feedback on project risk through the numerical value of the assessment coefficient, facilitating risk decision of a user, recording and storing the assessment coefficient, and providing data support for subsequent risk simulation.
The decision analysis module is used for processing decision analysis on the evaluation object through the evaluation coefficient PG: obtaining evaluation threshold values PGmin and PGmax through a storage module, wherein PGmin is a minimum evaluation threshold value and PGmax is a maximum evaluation threshold value, and comparing the evaluation coefficient PG with the evaluation threshold values PGmin and PGmax by a numerical value: if PG is less than or equal to PGmin, judging that the risk assessment of the assessment object is qualified, and marking the decision label as undertaking; if PGmin is greater than PG and less than PGmax, judging that the risk evaluation of the evaluation object is unqualified, and marking the decision label as sharing; if PG is larger than or equal to PGmax, judging that the risk evaluation of the evaluation object is unqualified, and marking the decision label as evasion; and (3) screening and analyzing the decision label as a shared evaluation object: marking a third-party platform which meets sharing requirements as a screening object, and acquiring qualification data ZZ, registration data ZC and processing data CL of the screening object, wherein the qualification data ZZ is a registered fund numerical value of the screening object and is in the unit of ten million, the registration data ZC is the registered employee number of the screening object and is in the unit of hundred, the processing data CL is the number of risk items processed by the screening object in the last L1 month, L1 is a numerical constant, and the specific numerical value of L1 is set by a manager; obtaining a recommendation coefficient TJ of the screening object through a formula TJ = β 1 × zz + β 2 × zc + β 3 × cl, where it should be noted that the recommendation coefficient TJ is a numerical value reflecting a degree of risk sharing that the screening object is suitable for performing, and the larger the numerical value of the recommendation coefficient is, the higher the suitable degree of risk sharing that the screening object is corresponding to is; wherein beta 1, beta 2 and beta 3 are proportionality coefficients, and beta 1 is more than beta 2 and more than beta 3 is more than 1; marking the L2 screening objects with the maximum recommendation coefficient TJ value as sharing objects, wherein L2 is a value constant, and the specific value of L2 is set by a manager; sending the sharing object to a risk evaluation platform, and sending the sharing object to a mobile phone terminal of a manager after the risk evaluation platform receives the sharing object; the evaluation object is processed and subjected to decision analysis through the evaluation coefficient PG, a decision tag of the evaluation object is marked, so that decision recommendation feedback is performed on project execution according to the decision tag, subjective judgment interference of management personnel is reduced, an objective decision scheme is given through data analysis, meanwhile, the most suitable third party platforms are obtained directly through screening, analyzing and screening as alternative targets for projects with the decision tag being shared, and the sharing and screening process is simplified.
The risk simulation module is used for carrying out risk simulation analysis on the evaluation object: marking an evaluation object with a decision label as a bearing object, obtaining an evaluation coefficient executed by a historical project through a storage module, forming an evaluation range by the maximum value and the minimum value of the evaluation coefficient, dividing the evaluation range into a plurality of evaluation intervals, marking the evaluation interval corresponding to the evaluation coefficient of the bearing object as a matching interval, marking the historical execution project in the matching interval as a matching project, setting a simulation period, executing the project on the evaluation object in the simulation period, setting an analysis time point i, i =1,2, 8230, n, n is a positive integer in the simulation period, obtaining intrusion data RQI and leakage data Xli executed by the project at the analysis time point, and intruding data RQI and leakage data XliData RQi is the number of network intrusions received by the execution of the item before the analysis time point, leakage data XLi is the number of internal data leakage received by the execution of the item before the analysis time point, an execution coefficient ZXi of the item execution at the analysis time point is obtained through a formula ZXi = γ 1 × RQi + γ 2 × XLi, it is noted that the execution coefficient is a risk degree reflecting the execution of the item at the analysis time point, and the larger the value of the execution coefficient is, the higher the risk degree of the item execution at the corresponding analysis point is; wherein gamma 1 and gamma 2 are both proportionality coefficients, and gamma 1 is more than gamma 2 and more than 1; after the simulation period is finished, calling the execution coefficients of the matched items at each analysis time point in the simulation period and marking the execution coefficients as LSi, and obtaining the LSi through a formula
Obtaining a matching coefficient PP of a matching item, marking the matching item with the minimum matching coefficient PP value as a simulation object bearing the object, calling historical execution data of the simulation object and sending the historical execution data to a risk evaluation platform, sending the historical execution data of the simulation object to a mobile phone terminal of a manager after the risk evaluation platform receives the historical execution data of the simulation object, wherein the historical execution data of the simulation object comprises profit data, investment data and maintenance data; and performing risk simulation analysis on the evaluation object, screening the historical items closest to the initial risk degree for the undertaking object according to the numerical value of the evaluation coefficient, analyzing the risk change process of the historical items in a simulation period, marking the historical items closest to the risk change curve of the undertaking object in the simulation period as simulation objects, and predicting the execution risk of the undertaking object according to the execution risk curve of the simulation objects.
Example two
A method for performing risk assessment based on a project for data analysis, comprising the steps of:
the method comprises the following steps: project risk assessment analysis is performed prior to project execution: marking the item subjected to risk evaluation as an evaluation object, acquiring authority data QX, volume data TL and sensitive data MG of the evaluation object, performing numerical calculation to obtain an evaluation coefficient PG of the evaluation object, sending the evaluation coefficient PG to a decision analysis module, performing visual feedback on the item risk through the numerical value of the evaluation coefficient, facilitating risk decision of a user, recording and storing the evaluation coefficient, and providing data support for subsequent risk simulation;
step two: and (3) performing processing decision analysis on the evaluation object through the evaluation coefficient PG: acquiring evaluation thresholds PGmin and PGmax through a storage module, carrying out numerical comparison on the evaluation coefficient PG and the evaluation thresholds PGmin and PGmax, marking decision tags as sharing, undertaking or avoiding through a comparison result, directly screening, analyzing and screening a plurality of most suitable third party platforms as alternative targets aiming at the items of which the decision tags are shared, and simplifying the sharing and screening process;
step three: the risk simulation analysis is carried out on the evaluation object to obtain a simulation object, historical execution data of the simulation object is called and sent to a risk evaluation platform, the risk evaluation platform receives the historical execution data of the simulation object and sends the historical execution data of the simulation object to a mobile phone terminal of a manager, a historical item which is closest to a risk change curve of the undertaking object in a simulation period is marked as the simulation object, and therefore the execution risk of the undertaking object is predicted according to the execution risk curve of the simulation object.
A project execution risk assessment system based on data analysis, operative to perform a project risk assessment analysis prior to project execution: marking the item subjected to risk evaluation as an evaluation object, acquiring authority data QX, volume data TL and sensitive data MG of the evaluation object, performing numerical calculation to obtain an evaluation coefficient PG of the evaluation object, sending the evaluation coefficient PG to a decision analysis module, performing visual feedback on the item risk through the numerical value of the evaluation coefficient, facilitating risk decision of a user, recording and storing the evaluation coefficient, and providing data support for subsequent risk simulation; and (3) performing processing decision analysis on the evaluation object through the evaluation coefficient PG: obtaining evaluation thresholds PGmin and PGmax through a storage module, carrying out numerical comparison on the evaluation coefficient PG and the evaluation thresholds PGmin and PGmax, marking a decision tag as sharing, undertaking or avoiding through a comparison result, directly obtaining a plurality of most suitable third party platforms as alternative targets through screening, analyzing and screening aiming at projects with the decision tag as sharing, and simplifying a sharing and screening process; the risk simulation analysis is carried out on the evaluation object to obtain a simulation object, historical execution data of the simulation object is called and sent to a risk evaluation platform, the risk evaluation platform receives the historical execution data of the simulation object and sends the historical execution data of the simulation object to a mobile phone terminal of a manager, a historical item which is closest to a risk change curve of the undertaking object in a simulation period is marked as the simulation object, and therefore the execution risk of the undertaking object is predicted according to the execution risk curve of the simulation object.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
The formulas are obtained by acquiring a large amount of data and performing software simulation, and the coefficients in the formulas are set by the technicians in the field according to actual conditions; such as: the formula TJ = β 1 × zz + β 2 × zc + β 3 × cl; collecting multiple groups of sample data and setting a corresponding recommendation coefficient for each group of sample data by a person skilled in the art; substituting the set recommendation coefficient and the acquired sample data into formulas, forming a ternary linear equation set by any three formulas, screening the calculated coefficients and taking the mean value to obtain values of alpha 1, alpha 2 and alpha 3 which are 3.74, 2.97 and 2.65 respectively;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and a corresponding recommendation coefficient is preliminarily set for each group of sample data by a person skilled in the art; it is sufficient if the proportional relationship between the parameters and the quantized values is not affected, for example, the recommendation coefficients are proportional to the values of the qualification data.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (7)
1. A project execution risk assessment system based on data analysis comprises a risk assessment platform, and is characterized in that the risk assessment platform is in communication connection with a risk assessment module, a decision analysis module, a risk simulation module and a storage module;
the risk assessment module is configured to perform a project risk assessment analysis prior to execution of a project: marking the item for risk evaluation as an evaluation object, and acquiring authority data QX, volume data TL and sensitive data MG of the evaluation object; obtaining an evaluation coefficient PG of the evaluation object by carrying out numerical calculation on authority data QX, volume data TL and sensitive data MG of the evaluation object; sending the evaluation coefficient PG of the evaluation object to a risk evaluation platform, and sending the received evaluation coefficient PG of the evaluation object to a decision analysis module by the risk evaluation platform;
the decision analysis module is used for processing decision analysis on the evaluation object through the evaluation coefficient PG: acquiring evaluation thresholds PGmin and PGmax through a storage module, wherein PGmin is a minimum evaluation threshold and PGmax is a maximum evaluation threshold, numerically comparing an evaluation coefficient PG with the evaluation thresholds PGmin and PGmax, and marking a decision tag according to a comparison result;
the risk simulation module is used for carrying out risk simulation analysis on the evaluation object.
2. The system of claim 1, wherein the authority data QX is the number of administrators with legal authority to access data in the evaluation object, the quantum data TL is the total memory value of the management data in the evaluation object, and the sensitive data MG is the total memory value of the sensitive data in the evaluation object.
3. The system of claim 1, wherein the comparing the evaluation coefficient PG with the evaluation thresholds PGmin and PGmax comprises:
if PG is less than or equal to PGmin, judging that the risk assessment of the assessment object is qualified, and marking the decision label as undertaking;
if PGmin is less than PG and less than PGmax, judging that the risk evaluation of the evaluation object is unqualified, and marking the decision label as sharing;
if PG is larger than or equal to PGmax, judging that the risk evaluation of the evaluation object is unqualified, and marking the decision label as evasion;
and screening and analyzing the evaluation objects shared by the decision tags.
4. The system of claim 1, wherein the screening analysis of the shared evaluation target by the decision tag comprises: marking a third-party platform meeting sharing requirements as a screening object, and acquiring qualification data ZZ, registration data ZC and processing data CL of the screening object, wherein the qualification data ZZ is a registered capital value of the screening object and is in the unit of ten million, the registration data ZC is the number of registered employees of the screening object and is in the unit of hundred, and the processing data CL is the number of risk items processed by the screening object in the last L1 month; obtaining a recommendation coefficient TJ of the screening object by carrying out numerical calculation on qualification data ZZ, registration data ZC and processing data CL of the screening object;
and marking the L2 screening objects with the maximum recommendation coefficient TJ value as sharing objects, sending the sharing objects to a risk evaluation platform, and sending the sharing objects to a mobile phone terminal of a manager after the risk evaluation platform receives the sharing objects.
5. The data analysis-based project execution risk assessment system according to claim 1, wherein the risk simulation module is configured to perform a risk simulation analysis on the assessment object: marking an evaluation object with a decision label as a bearing object, acquiring an evaluation coefficient executed by a historical item through a storage module, forming an evaluation range by the maximum value and the minimum value of the evaluation coefficient, dividing the evaluation range into a plurality of evaluation sections, marking the evaluation section corresponding to the evaluation coefficient of the bearing object as a matching section, marking a historical execution item in the matching section as a matching item, setting a simulation period, executing the item on the evaluation object in the simulation period, setting an analysis time point i, i =1,2, \8230, n, n is a positive integer in the simulation period, acquiring intrusion data RQI and leakage data Xli executed by the item at the analysis time point, and performing numerical calculation on the intrusion data RQI and the leakage data I to obtain an execution coefficient ZXi executed by the item Xli at the analysis time point; after the simulation period is finished, calling the execution coefficients of the matched items at each analysis time point in the simulation period and marking the execution coefficients as LSi, and obtaining the LSi through a formula
Obtaining a matching coefficient PP of a matching item, marking the matching item with the minimum value of the matching coefficient PP as a simulation object of an undertaking object, calling historical execution data of the simulation object and sending the historical execution data to a risk evaluation platform, and sending the historical execution data of the simulation object to a mobile phone terminal of a manager after the risk evaluation platform receives the historical execution data of the simulation object;
the historical execution data of the simulation object includes profit data, investment data, and maintenance data.
6. The system of claim 1, wherein the intrusion data RQi is a number of network intrusions into the project before the analysis time point, and the leakage data XLi is a number of internal data leaks from the project before the analysis time point.
7. The data analysis-based project execution risk assessment system according to claim 1, wherein the working method of the data analysis-based project execution risk assessment system comprises the following steps:
the method comprises the following steps: project risk assessment analysis is performed prior to project execution: marking the item for risk evaluation as an evaluation object, acquiring authority data QX, volume data TL and sensitive data MG of the evaluation object, performing numerical calculation to obtain an evaluation coefficient PG of the evaluation object, and sending the evaluation coefficient PG to a decision analysis module;
step two: and (3) carrying out processing decision analysis on the evaluation object through the evaluation coefficient PG: obtaining evaluation threshold values PGmin and PGmax through a storage module, carrying out numerical comparison on the evaluation coefficient PG and the evaluation threshold values PGmin and PGmax, and marking the decision-making label as sharing, undertaking or avoiding through a comparison result;
step three: and after receiving the historical execution data of the simulation object, the risk evaluation platform sends the historical execution data of the simulation object to a mobile phone terminal of a manager.
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Application publication date: 20230418 |