CN115841275A - Physical examination method and device based on AI data management level - Google Patents
Physical examination method and device based on AI data management level Download PDFInfo
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Abstract
The invention relates to a physical examination method and a physical examination device based on AI data management level, wherein the method comprises the steps of physical examination of data to be detected to obtain a physical examination report; tracking the data to be detected according to the physical examination report to obtain a tracking report; evaluating the data to be detected by combining the physical examination report and the tracking report to obtain an evaluation result; analyzing the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations. The invention subdivides the index system of the data management level physical examination, so that the physical examination is more pertinent, the physical examination result is more accurate and effective, various AI algorithms are introduced, the evaluation process and the result are more scientific, meanwhile, the quantitative evaluation result can be visually compared with the results of the same line, the sustainability and the reusability of the data management level physical examination are improved, the manual consultation mode can be replaced, and the enterprise cost is effectively reduced.
Description
Technical Field
The invention belongs to the technical field of big data, and particularly relates to a physical examination method and device based on AI data management level.
Background
In recent years, the global digital economy is developed vigorously, the ratio of the digital economy in national economy is higher and higher, the construction of the digital economy taking data as a key element is the current trend, the data, land, labor force, capital and technology are combined into production elements in related researches, and the importance of the data, namely a novel and digital production element, is highlighted. On the basis, each enterprise and public institution attaches unprecedented importance to the data management level of the enterprise and public institutions.
In the related technology, at present, most enterprises and public institutions cannot know and improve the self data management level through a scientific and effective method, and although a few enterprises with high capital are used for solving the problem by engaging in professional consulting companies, the method is usually disposable, cannot be automatically executed, and has to continuously invest capital cost, so that the method has no universality. However, for the problem of understanding and improving the data management level, a data physical examination related technology is available on the market, which can assist enterprises to understand, but the technology can only solve a small part of the problem of finding data problem points, cannot comprehensively cover all links of data management capacity of the enterprises, cannot automatically find and evaluate the data management capacity, and further cannot provide a data management improvement strategy.
Disclosure of Invention
In view of the above, the present invention is to provide a physical examination method and apparatus for data management level based on AI to solve the problem that the data management level of the physical examination method and apparatus cannot be improved in the prior art.
In order to achieve the purpose, the invention adopts the following technical scheme: a physical examination method based on AI data management levels, comprising:
the data to be detected by physical examination is obtained to obtain a physical examination report;
tracking the data to be detected according to the physical examination report to obtain a tracking report;
evaluating the data to be detected by combining the physical examination report and the tracking report to obtain an evaluation result;
analyzing the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations.
Further, the data to be detected in the physical examination obtains a physical examination report, and the method comprises the following steps:
configuring a built-in business rule and a self-defined business rule;
creating physical examination task configuration, associating the service rule, designating a physical examination object and adding a physical examination task;
reading the physical examination task configuration, executing the physical examination task, and forming a physical examination result;
and analyzing the physical examination result to form a physical examination report.
Further, the tracking the data to be detected according to the physical examination report to obtain a tracking report, including:
creating a tracking task configuration and associating the physical examination tasks;
reading the tracking task configuration, and executing the tracking task to form a tracking result;
and analyzing the tracking result to form a tracking report.
Further, the evaluating the data to be tested by combining the physical examination report and the tracking report to obtain an evaluation result, including:
creating an evaluation task configuration, and associating the physical examination task with the tracking task;
and reading the configuration of the evaluation task by adopting a preset evaluation algorithm, executing the evaluation task and forming an evaluation result.
Further, the configuring of the built-in service rule includes configuring a common service rule, and setting the common service rule to be in an enabled state;
the self-defined business rule comprises a self-defined business rule name, a rule classification, a physical examination mode and a physical examination rule, wherein the physical examination rule supports keyword matching and regular expression matching on the field content, and supports testing the self-defined business rule and verifying the validity of the rule;
the physical examination task creating configuration comprises the steps of configuring task basic information, selecting a data source, selecting a physical examination target and reading the business rule; wherein the physical examination targets comprise data-scale physical examination, data-quality physical examination and data-use physical examination;
reading the physical examination task configuration, including reading physical examination task configuration information and performing pre-examination on the physical examination task configuration; the pre-checking comprises checking whether a data source, metadata, a data table and table fields exist and whether the types of the fields are matched;
the physical examination task execution method comprises the following steps:
creating a task queue for storing actuators of each physical examination subtask;
generating a task total check sum according to the physical examination indexes, splitting the total check sum to create each physical examination subtask, and placing a task executor into a task queue;
acquiring service rule configuration, completing rule matching, warehousing matching results, and executing a service physical examination task;
executing physical examination subtasks corresponding to the physical examination indexes;
the forming of the physical examination result comprises: storing the physical examination results of the data source, the metadata, the data table and the table field physical examination indexes into a database;
analyzing the physical examination result to form a physical examination report, comprising: and carrying out background processing on the physical examination index result, and displaying the physical examination index result through a front-end interface chart to form a physical examination report, wherein the physical examination report supports exporting and sharing in multiple formats.
Further, the creating of the tracking task configuration comprises configuring a tracking task name, associating a physical examination task, selecting a tracking period and the execution frequency of the tracking task;
the reading of the tracking task configuration comprises executing the tracking task according to a specified period and frequency to form a tracking result;
and analyzing the tracking result, wherein the tracking result comprises the execution time, the running time length, the running result of the tracking task and the result corresponding to the tracking subtask.
Further, the creating an evaluation task configuration includes: self-defining a configuration evaluation task name, configuring and associating the physical examination task and the tracking task, and selecting an AI algorithm for evaluation;
the reading evaluation task configuration comprises: and calling the AI algorithm selected for evaluation by the background, and executing an evaluation task by the background to form an evaluation result.
Furthermore, the promotion strategy is divided into a system rule class and a manual processing class,
the system rule class is automatically added as a lifting task, the system finishes lifting and records results, and the manual processing class is automatically sent to related responsible persons and finishes lifting manually.
The embodiment of the application provides a physical examination device of data management level based on AI, includes:
the physical examination module is used for physical examination of the data to be detected to obtain a physical examination report;
the tracking module is used for tracking the data to be detected according to the physical examination report to obtain a tracking report;
the evaluation module is used for evaluating the data to be detected by combining the physical examination report and the tracking report to obtain an evaluation result;
the generating module is used for analyzing the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations.
An embodiment of the present application provides a computer device, including: a memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of any of the AI-based data management level physical examination methods.
By adopting the technical scheme, the invention can achieve the following beneficial effects:
(1) The technical scheme provided by the application has a closed-loop process of the data management level physical examination, covers all links of exploration, tracking, evaluation and promotion, and forms a complete technical solution of the data management level physical examination.
(2) The data management level physical examination index system is subdivided, so that the physical examination is more pertinent, and the physical examination result is more accurate and effective.
(3) The method is also provided with a data management level evaluation link.
(4) The whole process of the data management level physical examination method is executed through a computer program, the full automation of physical examination is realized, the sustainability and the reusability of the data management level physical examination are improved, an artificial consultation mode can be replaced, and the enterprise cost is effectively reduced.
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 embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic illustration of the steps of the AI-based data management level physical examination method of the present invention;
FIG. 2 is a schematic diagram of another step of the AI-based data management level physical examination method of the present invention;
FIG. 3 is a schematic diagram of another step of the AI-based data management level physical examination method of the present invention;
FIG. 4 is a schematic illustration of another step of the AI-based data management level physical examination method of the present invention;
FIG. 5 is a schematic diagram of the AI-based data management level physical examination apparatus of the present invention;
fig. 6 is a schematic hardware configuration diagram of an implementation environment of the physical examination method based on the AI data management level of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
A specific physical examination method and apparatus based on AI data management level provided in the embodiments of the present application will be described with reference to the accompanying drawings.
As shown in fig. 1, the physical examination method based on the AI data management level provided in the embodiment of the present application includes:
s101, physical examination to-be-detected data is obtained, and a physical examination report is obtained;
in some embodiments, as shown in fig. 2, the obtaining of the physical examination report from the data to be tested of the physical examination includes:
s1011, configuring a built-in business rule and a self-defined business rule;
the configuration of the built-in business rule comprises the steps of configuring a common business rule and setting the common business rule to be in an enabling state; the common service rule may be code value identification, code length, whether the name is empty, whether the name of Chinese and English is complete, whether the name is set, and the like.
The self-defined business rule comprises a self-defined business rule name, rule classification, a physical examination mode and a physical examination rule, wherein the physical examination rule supports keyword matching and regular expression matching on the field content, and supports testing the self-defined business rule and verifying the validity of the rule.
S1012, creating physical examination task configuration, associating the business rules, designating physical examination objects and adding physical examination tasks;
the physical examination task creating configuration comprises configuring task basic information, selecting a data source, selecting a physical examination target and reading the business rule;
the physical examination target is a data management horizontal physical examination index system, and specifically comprises data-scale physical examination, data-quality physical examination and data-use physical examination. The data scale physical examination comprises a data type index, a data quantity index and a data position distribution index; the data quality check comprises a data quality problem index, a metadata quality problem index and a data standard index; the data use physical examination comprises a data calling frequency index, a data association node index and a data influence depth index.
S1013, reading the physical examination task configuration, executing the physical examination task, and forming a physical examination result;
reading the physical examination task configuration, including reading physical examination task configuration information and pre-checking the physical examination task configuration; the pre-checking comprises checking whether a data source, metadata, a data table and a table field exist and whether the types of the fields are matched.
The physical examination task execution comprises the following steps:
creating a task queue for storing actuators of each physical examination subtask;
generating a task total check sum according to the physical examination indexes, splitting the total check sum to create each physical examination subtask, and placing a task executor into a task queue;
acquiring service rule configuration, completing rule matching, warehousing matching results, and executing a service physical examination task;
executing physical examination subtasks corresponding to the physical examination indexes;
the forming of the physical examination result comprises: and storing the physical examination results of the data source, the metadata, the data table and the table field physical examination indexes in a database.
S1014, analyzing the physical examination result to form a physical examination report.
Wherein, the analysis of the physical examination result forms a physical examination report, which comprises: and carrying out background processing on the physical examination index result, and displaying the physical examination index result through a front-end interface chart to form a physical examination report, wherein the physical examination report supports exporting and sharing in multiple formats.
S102, tracking the data to be detected according to the physical examination report to obtain a tracking report;
in some embodiments, as shown in fig. 3, the tracking the data to be tested according to the physical examination report to obtain a tracking report includes:
s1021, establishing tracking task configuration and associating the physical examination tasks;
the tracking task configuration establishing comprises the steps of configuring a tracking task name, associating a physical examination task, selecting a tracking period and the execution frequency of the tracking task.
S1022, reading the configuration of the tracking task, executing the tracking task, and forming a tracking result;
and reading the tracking task configuration, wherein the tracking task is executed according to the specified period and frequency to form a tracking result.
And S1023, analyzing the tracking result to form a tracking report.
And analyzing the tracking result, wherein the tracking result comprises the execution time, the running time length, the running result of the tracking task and the result corresponding to the tracking subtask.
S103, evaluating the data to be tested by combining the physical examination report and the tracking report to obtain an evaluation result;
in some embodiments, as shown in fig. 4, the evaluating the data to be tested by combining the physical examination report and the tracking report to obtain an evaluation result includes:
s1031, creating an evaluation task configuration, and associating the physical examination task with the tracking task;
the creating of the evaluation task configuration comprises: self-defining and configuring an evaluation task name, configuring and associating the physical examination task and the tracking task, and selecting an AI algorithm for evaluation comprises the following steps: the system comprises a data envelope analysis model, a data management capability maturity model, a DAMA data management model and a data health degree evaluation model, wherein the data envelope analysis model is used for establishing an algorithm for comparing the improvement effects of the same object at different stages based on a DEA mathematical model; the data management capability maturity evaluation model is based on a DCMM data management capability maturity evaluation model, and an evaluation index system and a grading rule are constructed and used for quantitatively grading and grading the enterprise data management capability maturity; the DAMA data management model is based on a DAMA data management domain, and the constructed data maturity evaluation model is used for quantitatively scoring and grading the enterprise data management maturity; the data health assessment model is an assessment model constructed based on the data health degree index and an AHP analytic hierarchy process and used for assessing the data health condition. It will be appreciated that these AI algorithms are built into the evaluation module in the system and are selected when evaluating task configurations.
It should be noted that, in the present application, a plurality of AI algorithms are preset, and the AI algorithm for evaluation includes
S1032, reading the configuration of the evaluation task by adopting a preset evaluation algorithm, executing the evaluation task and forming an evaluation result.
The reading evaluation task configuration comprises: and calling the AI algorithm selected for evaluation by the background, and executing an evaluation task through the background to form an evaluation result.
S104, analyzing the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations.
In some embodiments, the promotion policies are divided into a system rules class and a manual processing class,
the system rule class is automatically added as a lifting task, the system finishes lifting and records results, and the manual processing class is automatically sent to related responsible persons and finishes lifting manually.
In summary, the physical examination method based on the AI data management level provided by the application has the following characteristics,
(1) The closed loop process of the data management level physical examination covers all links of exploration, tracking, assessment and promotion, forms a complete technical solution of the data management level physical examination, and compared with the prior art which can only discover and cannot assist in solving problems in the prior art, the method and the device have higher practicability.
(2) The data management level physical examination index system is subdivided, so that the physical examination is more pertinent, and the physical examination result is more accurate and effective.
(3) The method and the device increase an evaluation link on the data management level.
(4) The whole process of the data management level physical examination is executed through a computer program, the full automation of the physical examination is realized, the sustainability and the reusability of the data management level physical examination are improved, an artificial consultation mode can be replaced, and the enterprise cost is effectively reduced.
As shown in fig. 5, an embodiment of the present application provides a physical examination apparatus for AI-based data management level, including:
the physical examination module 501 is used for physical examination of the data to be detected to obtain a physical examination report;
a tracking module 502, configured to track the data to be detected according to the physical examination report to obtain a tracking report;
an evaluation module 503, configured to evaluate the to-be-detected data by combining the physical examination report and the tracking report to obtain an evaluation result;
a generating module 504, configured to parse the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations.
The working principle of the physical examination device based on the AI data management level is that the physical examination module 501 is used for physical examination of data to be detected to obtain a physical examination report; the tracking module 502 tracks the data to be detected according to the physical examination report to obtain a tracking report; the evaluation module 503 evaluates the data to be tested by combining the physical examination report and the tracking report to obtain an evaluation result; the generating module 504 analyzes the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations.
The present application provides a computer device comprising: a memory, which may include volatile memory in a computer-readable medium, random Access Memory (RAM), and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The computer device stores an operating system, and the memory is an example of a computer-readable medium. The computer program, when executed by the processor, causes the processor to perform a physical examination method based on the AI data management level, the structure shown in fig. 6 is a block diagram of only a portion of the structure associated with the aspects of the present application and does not constitute a limitation on the computer apparatus to which the aspects of the present application are applied, and a particular computer apparatus may include more or less components than shown in the drawings, or combine certain components, or have a different arrangement of components.
In one embodiment, the AI-based data management level physical examination method provided herein can be implemented in the form of a computer program that can be run on a computer device as shown in fig. 6.
In some embodiments, the computer program, when executed by the processor, causes the processor to perform the steps of: the data to be detected by physical examination is obtained to obtain a physical examination report; tracking the data to be detected according to the physical examination report to obtain a tracking report; evaluating the data to be detected by combining the physical examination report and the tracking report to obtain an evaluation result; analyzing the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations.
The present application also provides a computer storage medium, examples of which include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassette tape storage or other magnetic storage devices, or any other non-transmission medium, that can be used to store information that can be accessed by a computing device.
In some embodiments, the present invention further provides a computer-readable storage medium storing a computer program, where the computer program, when executed by a processor, performs a physical examination on data to be tested to obtain a physical examination report; tracking the data to be detected according to the physical examination report to obtain a tracking report; evaluating the data to be detected by combining the physical examination report and the tracking report to obtain an evaluation result; analyzing the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations.
In summary, the invention provides a physical examination method and device based on AI data management level, the method includes physical examination of data to be detected, obtaining a physical examination report; tracking the data to be detected according to the physical examination report to obtain a tracking report; evaluating the data to be detected by combining the physical examination report and the tracking report to obtain an evaluation result; analyzing the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations. The invention subdivides the index system of the data management level physical examination, so that the physical examination is more pertinent, the physical examination result is more accurate and effective, various AI algorithms are introduced, the evaluation process and the result are more scientific, meanwhile, the quantitative evaluation result can be visually compared with the results of the same line, the sustainability and the reusability of the data management level physical examination are improved, the manual consultation mode can be replaced, and the enterprise cost is effectively reduced.
It is to be understood that the method embodiments provided correspond to the apparatus embodiments, and corresponding specific contents may be referred to each other, which is not described herein again.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A physical examination method based on AI data management level is characterized by comprising the following steps:
the data to be detected by physical examination is obtained to obtain a physical examination report;
tracking the data to be detected of the physical examination according to the physical examination report to obtain a tracking report;
the data to be detected of the physical examination is evaluated by combining the physical examination report and the tracking report to obtain an evaluation result;
analyzing the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations.
2. The AI-based data management level physical examination method of claim 1, wherein the physical examination data to be tested, resulting in a physical examination report, comprises:
configuring a built-in business rule and a self-defined business rule;
creating physical examination task configuration, associating the built-in business rule of the configuration with a user-defined business rule, designating a physical examination object, and adding a physical examination task;
reading the physical examination task configuration, executing the physical examination task, and forming a physical examination result;
and analyzing the physical examination result to form a physical examination report.
3. The AI-based data management level physical examination method of claim 2, wherein tracking the physical examination to-be-tested data according to the physical examination report to obtain a tracking report comprises:
creating a tracking task configuration and associating the physical examination tasks;
reading the tracking task configuration, and executing the tracking task to form a tracking result;
and analyzing the tracking result to form a tracking report.
4. The AI-based data management level physical examination method of claim 3, wherein the evaluating the physical examination data in combination with the physical examination report and the follow-up report to obtain an evaluation result comprises:
creating an evaluation task configuration, and associating the physical examination task with the tracking task;
and reading the configuration of the evaluation task by adopting a preset evaluation algorithm, executing the evaluation task and forming an evaluation result.
5. The AI-based data management level physical examination method of claim 2,
the configuration of the built-in business rules comprises the configuration of common business rules and the setting of the common business rules to an enabling state;
the self-defined business rule comprises the steps of configuring a self-defined business rule name, rule classification, a physical examination mode and a physical examination rule, wherein the physical examination rule supports keyword matching and regular expression matching on field content, and supports testing the self-defined business rule and verifying the validity of the rule;
the physical examination task creating configuration comprises the steps of configuring task basic information, selecting a data source, selecting a physical examination target and reading the self-defined business rule; wherein the physical examination targets comprise data-scale physical examination, data-quality physical examination and data-use physical examination;
reading the physical examination task configuration, including reading physical examination task configuration information and pre-checking the physical examination task configuration; the pre-checking comprises checking whether a data source, metadata, a data table and table fields exist and whether the types of the fields are matched;
the physical examination task execution comprises the following steps:
creating a task queue for storing actuators of each physical examination subtask;
generating a task total checksum according to the physical examination indexes, splitting the total checksum to create each physical examination subtask, and placing a task executor into a task queue;
acquiring service rule configuration, completing rule matching, warehousing matching results, and executing a service physical examination task;
executing physical examination subtasks corresponding to the physical examination indexes;
the forming of the physical examination result comprises: storing the physical examination results of the data source, the metadata, the data table and the table field physical examination indexes into a database;
analyzing the physical examination result to form a physical examination report, comprising: and carrying out background processing on the physical examination index result, and displaying the physical examination index result through a front-end interface chart to form a physical examination report, wherein the physical examination report supports exporting and sharing in multiple formats.
6. The AI-based data management level physical examination method of claim 3,
the tracking task configuration is created, and comprises the steps of configuring a tracking task name, associating a physical examination task, selecting a tracking period and the execution frequency of the tracking task;
the reading of the tracking task configuration comprises executing the tracking task according to a specified period and frequency to form a tracking result;
and analyzing the tracking result, wherein the tracking result comprises the execution time, the running time length, the running result of the tracking task and the result corresponding to the tracking subtask.
7. The AI-based data management level physical examination method of claim 4,
the creating of the evaluation task configuration comprises: self-defining a configuration evaluation task name, configuring and associating the physical examination task and the tracking task, and selecting an AI algorithm for evaluation;
the reading evaluation task configuration comprises: and calling the AI algorithm selected for evaluation by the background, and executing an evaluation task by the background to form an evaluation result.
8. The AI-based data management level physical examination method of claim 1, wherein the escalation strategy is divided into a system rules class and a manual processing class,
the system rule class is automatically added as a lifting task, the system finishes lifting and records results, and the manual processing class is automatically sent to related responsible persons and finishes lifting manually.
9. An AI-based data management level physical examination apparatus, comprising:
the physical examination module is used for physical examination of the data to be detected to obtain a physical examination report;
the tracking module is used for tracking the data to be detected of the physical examination according to the physical examination report to obtain a tracking report;
the evaluation module is used for evaluating the data to be tested of the physical examination by combining the physical examination report and the tracking report to obtain an evaluation result;
the generating module is used for analyzing the evaluation result to generate an evaluation report; the assessment report includes overall scores for data management, industry mean comparisons, current advantages, current disadvantages, lifting directions, lifting strategies, and recommendations.
10. A computer device, comprising: a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the AI-based data management level physical examination method of any one of claims 1 to 8.
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