Low-income dynamic monitoring data analysis early warning implementation method and system

Abstract

The invention relates to the technical field of information technology and data analysis, and particularly provides a low-income dynamic monitoring data analysis early warning implementation method and system, and the method comprises the following steps: S1, building a sound and dynamically adjusted low-income population information base; s2, performing data analysis mining based on data resources; s3, constructing an income monitoring and early warning system by using a professional model; and S4, meeting various business scenes through multi-dimensional query. Compared with the prior art, the method has the advantages that the rescue object active discovery mechanism can be better implemented by checking data to identify and select rescue objects, pre-judge economic condition changes of difficult families, analyze rescue requirements and the like, so that the information advantage, the data advantage and the mechanism advantage can be better exerted.

Description

Technical Field

[0001] The present invention relates to the fields of information technology and data analysis technology, and specifically provides a method and system for realizing data analysis and early warning of low-income dynamic monitoring. Background Art

[0002] Currently, all districts and counties and sub-districts in the city rely on the municipal low-income family economic status verification system to comprehensively establish a cross-departmental, multi-level, and information-sharing verification mechanism for the economic status of families applying for assistance, and comprehensively carry out the verification work on the economic status of families applying for assistance, greatly improving work efficiency, enhancing business standardization and regularization, and making social assistance more accurate.

[0003] However, in the prior art, there are still deficiencies in data analysis, development and utilization of the city's verification data, and providing early warning and research and judgment according to different assistance types and application scenarios. Summary of the Invention

[0004] The present invention aims at the above-mentioned deficiencies of the prior art and provides a method for realizing data analysis and early warning of low-income dynamic monitoring with strong practicability.

[0005] A further technical task of the present invention is to provide a system for realizing data analysis and early warning of low-income dynamic monitoring with reasonable design, safety and applicability.

[0006] The technical solution adopted by the present invention to solve its technical problems is as follows: A method for realizing data analysis and early warning of low-income dynamic monitoring has the following steps: S1. Establish and improve a dynamically adjusted low-income population information database; S2. Rely on data resources for data analysis and mining; S3. Build an income monitoring and early warning system with professional models; S4. Meet various business scenarios through multi-dimensional queries.

[0007] Further, in step S1, the platform will rely on the data of the low-income population database, the economic status verification data of residents' families, and verify relevant business data for big data analysis and development and utilization, and build a basic platform for verification big data; Sort out the catalog of information-based data resources for verification according to the rules and attributes of various verification data, and extract relevant analysis and decision-making index items.

[0008] Further, in step S2, the relevant economic information data, the application data of users and the historical verification data gathered by the platform will be comprehensively analyzed, and the data mining analysis and decision-making application will be presented in a more intuitive way, and real-time supervision will be realized during the verification work through the analysis results.

[0009] Further, in step S3, through big data comparison, regular monitoring is carried out on special assistance recipients, unemployed persons, disadvantaged people with chronic diseases, patients receiving special treatment for major diseases, severely disabled persons, disaster victims, and temporary assistance recipients, to promptly detect situations where rigid expenditures are relatively large or incomes are significantly reduced due to illness, disaster, education, disability, or accidental incidents, and achieve dynamic early warning of income monitoring.

[0010] Further, in step S4, the multi-dimensional query function is a custom query mode realized by the low-income population dynamic monitoring information platform through associating and combining various types of data in the low-income population database and cross-comparing them.

[0011] A system for realizing data analysis and early warning of low-income dynamic monitoring. First, a low-income population information database with dynamic adjustment is established and improved. Based on data resources, data analysis and mining are carried out, and an income monitoring and early warning system is constructed with professional models. Finally, various business scenarios are satisfied through multi-dimensional queries.

[0012] Further, when establishing and improving a low-income population information database with dynamic adjustment, the platform will rely on the data of the low-income population database and the data of the verification of the economic status of resident families collected, and verify relevant business data for big data analysis and development and utilization, and build a basic platform for big data verification. Sort out the catalog of information data resources for verification according to the rules and attributes of various types of verification data, and extract relevant analysis and decision-making index items.

[0013] Further, when carrying out data analysis and mining based on data resources, comprehensive analysis will be carried out relying on the relevant economic information data, user application data, and historical verification data collected by the platform, and the data mining analysis and decision-making applications will be presented in a more intuitive way, and real-time supervision will be realized during the verification work process through the analysis results.

[0014] Further, when constructing an income monitoring and early warning system with professional models, regular monitoring is carried out on special assistance recipients, unemployed persons, disadvantaged people with chronic diseases, patients receiving special treatment for major diseases, severely disabled persons, disaster victims, and temporary assistance recipients through big data comparison, to promptly detect situations where rigid expenditures are relatively large or incomes are significantly reduced due to illness, disaster, education, disability, or accidental incidents, and achieve dynamic early warning of income monitoring.

[0015] Further, when satisfying various business scenarios through multi-dimensional queries, the multi-dimensional query function is a custom query mode realized by the low-income population dynamic monitoring information platform through associating and combining various types of data in the low-income population database and cross-comparing them.

[0016] Compared with the prior art, a method and system for realizing data analysis and early warning of low-income dynamic monitoring of the present invention have the following prominent beneficial effects: The present invention realizes the identification and selection of relief recipients by checking data, predicting changes in the economic status of needy families, analyzing relief needs, etc., better implementing the active discovery mechanism for relief recipients, and thus better leveraging the information advantages, data advantages, and mechanism advantages of this system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0018] Attached Figure 1 is a flowchart showing a method for realizing data analysis and early warning of low-income dynamic monitoring. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to enable those in the technical field to better understand the solution of the present invention, the following will further elaborate on the present invention in combination with specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0020] The following gives a best embodiment: As Figure 1 shown, a method for realizing data analysis and early warning of low-income dynamic monitoring in this embodiment has the following steps: S1. Establish and improve a dynamically adjusted low-income population information database; The platform will rely on the data of the low-income population database and the data of the verification of the economic status of residents' families collected, check relevant business data for big data analysis and development and utilization, build a basic platform for check big data, sort out the directory of check information data resources according to the laws and attributes of various check data, extract relevant analysis and decision-making index items, and provide services such as income monitoring and early warning, statistical decision-making, and data research and judgment for the city's social assistance and check work according to different relief types and application scenarios.

[0021] S2. Rely on data resources for data analysis and mining; The project will conduct comprehensive analysis based on relevant economic information data, user application data, historical verification data, etc. gathered by the platform, create data mining analysis and decision-making applications such as intelligent comparison and personnel profiling, and present them in a more intuitive way, providing rich visual analysis algorithms and analysis functions, mainly including multi-dimensional analysis, visual dashboards, etc. Through the analysis results, real-time supervision will be achieved during the verification process to ensure that the verified data accurately covers the entire population and provides support for decision-making.

[0022] S3. Build an income monitoring and early warning system with a professional model; Through means such as big data comparison, conduct regular monitoring on special assistance recipients, unemployed people, poor people with chronic diseases, patients with special major disease treatment, severely disabled people, disaster victims, temporary assistance recipients, etc., and promptly discover situations where their rigid expenditures are relatively large or their incomes are significantly reduced due to illness, disaster, education, disability, accidental accidents, etc., to achieve dynamic early warning of income monitoring.

[0023] S4. Meet various business scenarios through multi-dimensional queries; The multi-dimensional query function is a custom query mode implemented by the dynamic monitoring information platform for low-income populations according to the personalized assistance needs of departments, by associating and combining various types of data in the low-income population database and cross-comparing them.

[0024] Based on the above method, in this embodiment, a system for realizing data analysis and early warning of low-income dynamic monitoring first establishes and improves a dynamically adjusted low-income population information database, relies on data resources for data analysis and mining, builds an income monitoring and early warning system with a professional model, and finally meets various business scenarios through multi-dimensional queries.

[0025] Among them, when establishing and improving a dynamically adjusted low-income population information database, the platform will rely on the data in the low-income population database, the data of the verification of residents' family economic status, and the relevant business data of the verification to conduct big data analysis and development and utilization, and build a basic platform for verification big data; Sort out the catalog of information resources for verification informatization according to the laws and attributes of various verification data, and extract relevant analysis and decision-making index items.

[0026] When relying on data resources for data analysis and mining, it will conduct comprehensive analysis based on the relevant economic information data, user application data, and historical verification data gathered by the platform, present the data mining analysis and decision-making applications in a more intuitive way, and achieve real-time supervision during the verification process through the analysis results.

[0027] When building an income monitoring and early warning system with a professional model, through big data comparison, regular monitoring is carried out on special assistance recipients, unemployed people, disadvantaged people with chronic diseases, patients receiving special treatment for major diseases, severely disabled people, disaster victims, and temporary assistance recipients, so as to timely detect situations where rigid expenditures are relatively large or income is significantly reduced due to illness, disaster, education, disability, or accidental accidents, and achieve dynamic early warning of income monitoring.

[0028] When meeting various business scenarios through multi-dimensional queries, the multi-dimensional query function is a custom query mode realized by the dynamic monitoring information platform for low-income populations through associating and combining various types of data in the low-income population database and cross-comparing them.

[0029] The above specific implementation manners are only specific cases of the present invention. The patent protection scope of the present invention includes but is not limited to the above specific implementation manners. Any technical solution that conforms to the above specific implementation manners of the present invention and any appropriate changes or substitutions made by any person of ordinary skill in the relevant technical field shall fall within the patent protection scope of the present invention.

[0030] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for realizing low-income dynamic monitoring data analysis and early warning, characterized in that: The steps are as follows: S1. Establish and improve a dynamically adjusted low-income population information database; S2. Conduct data analysis and mining based on data resources; S3. Construct an income monitoring and early warning system with professional models; S4. Satisfy various business scenarios through multi-dimensional query.

2. A method for realizing low-income dynamic monitoring data analysis and early warning according to claim 1, characterized in that: In step S1, the platform will rely on the collected low-income population database data and household economic status verification data to verify the relevant business data for big data analysis and development and utilization, and build a basic platform for verification of big data; According to the rules and attributes of various verification data, the information data resource directory is sorted and verified, and relevant analysis and decision-making indicators are extracted.

3. A method for realizing low-income dynamic monitoring data analysis and early warning according to claim 2, characterized in that: In step S2, a comprehensive analysis is conducted on the relevant economic information data, user application data and historical verification data gathered by the platform, and data mining and analysis decision-making applications are presented in a more intuitive manner. Real-time supervision is achieved during the verification process through the analysis results.

4. A method for realizing low-income dynamic monitoring data analysis and early warning according to claim 3, characterized in that: In step S3, regular monitoring is carried out on special relief recipients, unemployed persons, people in need with chronic diseases, patients receiving special treatment for serious diseases, severely disabled persons, disaster victims, and temporary relief recipients through big data comparison, so as to promptly discover situations in which rigid expenditures are large or income is substantially reduced due to illness, disaster, education, disability, or accidents, and realize dynamic early warning of income monitoring.

5. A method for realizing low-income dynamic monitoring data analysis and early warning according to claim 4, characterized in that: In step S4, the multi-dimensional query function is a custom query mode achieved by the low-income population dynamic monitoring information platform by associating, combining and cross-comparing various types of data in the low-income population database.

6. A low-income dynamic monitoring data analysis and early warning implementation system, characterized in that: First, establish and improve a dynamically adjusted low-income population information database, rely on data resources to conduct data analysis and mining, build an income monitoring and early warning system with professional models, and finally meet various business scenarios through multi-dimensional queries.

7. A low-income dynamic monitoring data analysis and early warning implementation system according to claim 6, characterized in that: When establishing and improving a dynamically adjusted low-income population information database, the platform will rely on the collected low-income population database data and household economic status verification data to verify relevant business data for big data analysis and development and utilization, and build a basic platform for verifying big data; According to the rules and attributes of various verification data, the information data resource directory is sorted and verified, and relevant analysis and decision-making indicators are extracted.

8. A low-income dynamic monitoring data analysis and early warning implementation system according to claim 7, characterized in that: When conducting data analysis and mining based on data resources, a comprehensive analysis will be conducted on the relevant economic information data, user application data and historical verification data gathered by the platform, and the data mining analysis decision-making applications will be presented in a more intuitive way, achieving real-time supervision during the verification process through the analysis results.

9. A low-income dynamic monitoring data analysis and early warning implementation system according to claim 8, characterized in that: When constructing an income monitoring and early warning system with professional models, regular monitoring is carried out on special relief recipients, unemployed people, people in difficulty with chronic diseases, patients receiving special treatment for serious diseases, severely disabled people, disaster victims, and temporary relief recipients through big data comparison, so as to promptly discover situations where rigid expenditures are large or income is sharply reduced due to illness, disaster, education, disability, or accidents, and realize dynamic early warning of income monitoring.

10. A low-income dynamic monitoring data analysis and early warning implementation system according to claim 9, characterized in that: When multi-dimensional query is used to meet various business scenarios, the multi-dimensional query function is a custom query mode achieved by the low-income population dynamic monitoring information platform by associating, combining and cross-comparing various types of data in the low-income population database.

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