Financial data-based optimization management system

Abstract

The invention discloses an optimization management system based on financial data, which comprises a design processing module, an analysis management module and a storage feedback module, and is characterized in that the design processing module is in network connection with the analysis management module, and the analysis management module is in network connection with the storage feedback module; the design processing module is used for carrying out design processing on financial data services, the analysis management module is used for carrying out financial data service optimization analysis management, and the storage feedback module is used for carrying out analysis feedback processing on financial data information. The design processing module comprises an architecture design module, an entity attribute module and a data source connection module, the architecture design module is in network connection with the entity attribute module, the entity attribute module is in network connection with the data source connection module, and the architecture design module is used for architecture design management of the financial data service management system. The system has the characteristics of intelligent analysis management and efficient control.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to an optimization management system based on financial data. Background Art

[0002] Finance is an economic activity in which market entities use financial instruments to transfer funds from the party with surplus funds to the party with scarce funds. As the lifeblood of the modern economy, finance undertakes important functions such as financing, market pricing, resource allocation, information provision, and structural adjustment. It is an important part of promoting high-quality development, building a modern economic system and national core competitiveness. The rapid and vigorous development of financial technology has made financial data an important productive force, prompting changes in the production relations of today's society. There is a lot of valuable information hidden in such a huge amount of financial data. The magnitude and growth rate of data generated in the development of various financial businesses are unimaginable. It is almost impossible to sort out the clues from the vast and complex data, simplify it, and then analyze its regular changes. In the face of massive data, if the key information cannot be clearly presented and the problems cannot be quickly discovered, it is difficult to make correct processing decisions in future business planning, management, and decision-making. Therefore, it is necessary to design an optimization management system based on financial data for intelligent analysis management and efficient control. Summary of the invention

[0003] The purpose of the present invention is to provide an optimization management system based on financial data to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: an optimization management system based on financial data, comprising: a design processing module, an analysis management module and a storage feedback module, the design processing module and the analysis management module are network-connected, the analysis management module and the storage feedback module are network-connected, the design processing module is used to perform design processing of financial data services, the analysis management module is used to perform optimization analysis and management of financial data services, and the storage feedback module is used to perform storage feedback processing of financial data information.

[0005] According to the above technical solution, the design processing module includes an architecture design module, an entity attribute module and a data source connection module. The architecture design module is connected to the entity attribute module through a network. The entity attribute module is connected to the data source connection module through a network. The architecture design module is used to perform architecture design management of the financial data business management system. The entity attribute module is used to perform entity attribute processing and control of financial data information. The data source connection module is used to perform management and analysis of financial data sources.

[0006] According to the above technical solution, the analysis and management module includes a data desensitizing module, a scaffolding implementation module and a parsing and compiling module. The data desensitizing module is network-connected to the scaffolding implementation module, and the scaffolding implementation module is network-connected to the parsing and compiling module. The data desensitizing module is used to perform desensitizing processing control of financial data, the scaffolding module is used to perform component scaffolding implementation management, and the parsing and compiling module is used to perform parsing and compilation management of financial data.

[0007] According to the above technical solution, the storage feedback module includes a storage management module and a statistical feedback module. The storage management module and the statistical feedback module are connected to the network. The storage management module is used to perform storage management and control of financial data, and the statistical feedback module is used to perform statistical feedback control of financial data information.

[0008] According to the above technical solution, the operation method of the optimization management system based on financial data includes the following steps: Step S1: During the process of financial data business management, the architecture design, management and control of the financial data business management system are performed; Step S2: After completing the management and control of the financial data business management system architecture design, perform management and control of the entity attributes and data source connection of the financial data; Step S3: further optimizing, analyzing and managing the financial data business management system; Step S4: store, statistically manage and control the financial data.

[0009] According to the above technical solution, step S1 further includes the following steps: The financial data business management system is designed and managed by the architecture, which includes the presentation layer, business layer, service layer and data storage layer. The presentation layer is the client that carries the interaction between users and the system. It is manifested in the system's recognition of user interaction instructions, requesting financial data from the server and displaying the returned results. The business layer is responsible for receiving user instructions for operating financial data, performing verification analysis on them, and ensuring the correctness of financial data. The service layer is used to complete the server-side business logic implementation and maintain the database connection pool to ensure continuous connection to the database, reduce system performance consumption, transform the data structure of the acquired financial data, and provide data service support for the client. The data storage layer is responsible for providing financial data query services for the service layer, which is divided into two parts: internal system data storage and external storage.

[0010] According to the above technical solution, step S2 further includes the following steps: Step S21: further perform entity attribute processing on the data information of the financial data business management system, specifically, user entity attributes include user unique identification, account number, password, role authority, department and user basic information; visualization application entity attributes include application unique identification, application name description, basic configuration information, component information, creation user identification, collaboration user identification and status, wherein the basic configuration information attribute can derive application resolution, background image, cover image information, component configuration information attribute can derive component size, relative position, custom configuration information; component entity attributes include component name, identification, component type, thumbnail, default configuration information, custom configuration information, status creation user identification, wherein the custom configuration information can derive the workspace identification and component information; Step S22: The user can configure the data source of the visualization application by uploading the remote data source. If the configured data source is a remote database, the IP address of the visualization screen is added to the whitelist of remote database access to ensure normal access. After obtaining the source data, the data is filtered out or formatted to ensure data integrity and standardization of the data format.

[0011] According to the above technical solution, step S3 further includes the following steps: Step S31: In the financial data business management system, the user name information is desensitized, and a weight table is established for all the surnames and corresponding names of the users in the system. The weight of each Chinese character in the table is the frequency of use of each surname in the data set. The higher the frequency of use, the greater the weight value. First, the name field in the source data is split, and the first two characters of the name are accurately queried from the set dictionary library to find the common double surname data table. If the return value is empty, it is a single-character surname, otherwise it is a double surname; Step S32: further perform scaffolding control and implementation management of the financial data business management system, register an npm account, upload the project developed by simulating built-in components to the git server, execute the npm init command in the command line, generate an npm package locally, and generate corresponding files by default in the package directory, configure the entry file, so that system managers can perform scaffolding control by simulating built-in components according to needs; Step S33: Verify and manage the components in the financial data business management system. Based on the Vue framework, the babel compilation tool is used to compile the financial component files into the set financial file data that can be recognized by the browser, effectively improving the analysis and processing efficiency of the system.

[0012] According to the above technical solution, step S4 further includes the following steps: Step S41: Perform distributed backup storage of the real-time data information of the financial data business management system on the blockchain to effectively ensure data information security; Step S42: After the data information that has been backed up and stored is counted in chronological order, it is transmitted and fed back to the workbench for display.

[0013] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention, by providing a design processing module, an analysis management module and a storage feedback module, effectively avoids problems such as failure to upload financial files or re-upload when the network environment is poor. After successful uploading, the data is converted according to data rules, non-standard data is filtered, and the security and accuracy of user data information are effectively guaranteed, and the management of financial data is made more efficient and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] See also Figure 1 The present invention provides a technical solution: an optimization management system based on financial data, including: a design processing module, an analysis management module and a storage feedback module, the design processing module is connected to the analysis management module through a network, the analysis management module is connected to the storage feedback module through a network, the design processing module is used to perform design processing of financial data services, the analysis management module is used to perform optimization analysis and management of financial data services, and the storage feedback module is used to perform storage feedback processing of financial data information.

[0017] The design processing module includes the architecture design module, the entity attribute module and the data source connection module. The architecture design module and the entity attribute module are connected via a network. The entity attribute module and the data source connection module are connected via a network. The architecture design module is used for architecture design management of the financial data business management system. The entity attribute module is used for entity attribute processing and control of financial data information. The data source connection module is used for management and analysis of financial data sources.

[0018] The analysis and management module includes a data desensitizing module, a scaffolding implementation module and a parsing and compiling module. The data desensitizing module is connected to the scaffolding implementation module through a network, and the scaffolding implementation module is connected to the parsing and compiling module through a network. The data desensitizing module is used to perform desensitizing processing control of financial data, the scaffolding module is used to perform component scaffolding implementation management, and the parsing and compiling module is used to perform parsing and compilation management of financial data.

[0019] The storage feedback module includes a storage management module and a statistical feedback module. The storage management module and the statistical feedback module are connected to each other through a network. The storage management module is used for storage management and control of financial data, and the statistical feedback module is used for statistical feedback control of financial data information.

[0020] A method for operating an optimization management system based on financial data comprises the following steps: Step S1: During the process of financial data business management, the architecture design, management and control of the financial data business management system are performed; Step S2: After completing the management and control of the financial data business management system architecture design, perform management and control of the entity attributes and data source connection of the financial data; Step S3: further optimizing, analyzing and managing the financial data business management system; Step S4: store, statistically manage and control the financial data.

[0021] Step S1 further comprises the following steps: The architecture design and management of the financial data business management system are divided into the presentation layer, business layer, service layer and data storage layer. The presentation layer is the client that carries the interaction between users and the system. It is manifested as the system's recognition of user interaction instructions, requesting financial data from the server and displaying the returned results. The role of the business layer is to receive user instructions for operating financial data, perform verification analysis on them, and ensure the correctness of financial data. The service layer is used to complete the server-side business logic implementation and maintain the database connection pool to ensure continuous connection to the database, reduce system performance consumption, convert the data structure of the acquired financial data, and provide data service support for the client. The role of the data storage layer is to provide financial data query services for the service layer, which is divided into two parts: internal data storage and external storage. The internal storage provides storage services for the large screen and component data in the system, and the external storage provides data in the visualization component for the external database configured by the data source.

[0022] Step S2 further comprises the following steps: Step S21: further perform entity attribute processing on the data information of the financial data business management system, specifically, user entity attributes include user unique identification, account number, password, role authority, department and user basic information; visualization application entity attributes include application unique identification, application name description, basic configuration information, component information, creation user identification, collaboration user identification and status, wherein the basic configuration information attributes can derive application resolution, background image, cover image information, component configuration information attributes can derive component size, relative position, custom configuration information; component entity attributes include component name, identification, component type, thumbnail, default configuration information, custom configuration information, status creation user identification, wherein custom configuration information can derive workspace identification and component information; in this step, workspace entity attributes include workspace identification, workspace name, space manager identification, collaboration member identification; data source entity attributes include unique identification, name, classification, configuration parameters, wherein the configuration information can derive database connection information, file address, API information, JSON data, sub-data source mapping relationship; Step S22: The user can configure the data source of the visualization application by uploading and configuring the remote data source. If the configured data source is a remote database, the IP address of the visualization screen is added to the whitelist of remote database access to ensure that the access can proceed normally. After obtaining the source data, the data is filtered or formatted for invalid data to ensure the integrity of the data and the standardization of the data format. In the process of uploading data files, large-capacity data files are sliced, and the breakpoint resume function is used to ensure the integrity of the files. The sliced ​​files are numbered and offsets are set, and the file content summary is calculated through the crypto plug-in in NODE as the unique identifier of the sliced ​​file. The server locates the file through this identifier, sorts the files according to the slice number and offset of the file, and merges the files. The use of the file slicing breakpoint resume method to upload data files reduces bandwidth consumption and effectively avoids problems such as file upload failure or re-upload when the network environment is poor. After the upload is successful, the data is converted according to the data rules and non-standard data is filtered.

[0023] Step S3 further comprises the following steps: Step S31: In the financial data business management system, the user name information is desensitized, and a weight table is established for all the surnames and corresponding names of the users in the system. The weight of each Chinese character in the table is the frequency of use of each surname in the data set. The higher the frequency of use, the greater the weight value. First, the name field in the source data is split, and the first two characters of the name are accurately queried from the set dictionary library to find the common double surname data table. If the return is empty, it is a single-character surname, otherwise it is a double surname. In this step, after the name is successfully disassembled, the disassembled surname is used as the query condition to query the weight table, and the surname is replaced by the surname within the weight range in the weight library according to the jitter idea. For the name part, each Chinese character is randomly selected in the weight table in turn to replace the corresponding Chinese character within the weight range. Through this process, it is ensured that the surname part of the double name is still a common surname before and after desensitization, and the name length is consistent with the source name. Some double names are still double surnames after data desensitization, which effectively ensures the security and accuracy of user data information. Step S32: further perform scaffolding control and implementation management of the financial data business management system, register an npm account, upload the project developed by simulating built-in components to the git server, execute the npm init command in the command line, generate an npm package locally, and generate corresponding files by default in the package directory, configure the entry file, so that system managers can implement scaffolding control by simulating built-in components according to needs; through this step, managers only need to implement the development logic of new components in accordance with the rules of the framework, so that custom components can be better parsed and run by the system; Step S33: Verify and manage the components in the financial data business management system. Based on the Vue framework, the babel compilation tool is used to compile the financial component files into the set financial file data that can be recognized by the browser, effectively improving the analysis and processing efficiency of the system.

[0024] Step S4 further comprises the following steps: Step S41: Perform distributed backup storage of the real-time data information of the financial data business management system on the blockchain to effectively ensure data information security; Step S42: After the data information that has been backed up and stored is counted in chronological order, it is transmitted and fed back to the workbench for display.

[0025] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0026] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An optimization management system based on financial data, comprising: The design processing module, the analysis management module and the storage feedback module are characterized in that: the design processing module is connected to the analysis management module through a network, the analysis management module is connected to the storage feedback module through a network, the design processing module is used for design processing of financial data services, the analysis management module is used for optimizing analysis and management of financial data services, and the storage feedback module is used for storage feedback processing of financial data information.

2. The optimization management system based on financial data according to claim 1, characterized in that: The design processing module comprises an architecture design module, an entity attribute module and a data source connection module. The architecture design module is connected to the entity attribute module through a network. The entity attribute module is connected to the data source connection module through a network. The architecture design module is used to perform architecture design management of the financial data business management system. The entity attribute module is used to perform entity attribute processing control of financial data information. The data source connection module is used to perform management and analysis of financial data sources.

3. The optimization management system based on financial data according to claim 1, characterized in that: The analysis and management module includes a data desensitizing module, a scaffolding implementation module and a parsing and compiling module. The data desensitizing module is network-connected to the scaffolding implementation module, and the scaffolding implementation module is network-connected to the parsing and compiling module. The data desensitizing module is used to perform desensitizing processing control of financial data, the scaffolding module is used to perform component scaffolding implementation management, and the parsing and compiling module is used to perform parsing and compilation management of financial data.

4. The optimization management system based on financial data according to claim 1, characterized in that: The storage feedback module includes a storage management module and a statistical feedback module. The storage management module and the statistical feedback module are connected to a network. The storage management module is used to perform storage management control of financial data, and the statistical feedback module is used to perform statistical feedback control of financial data information.

5. The optimization management system based on financial data according to claim 1, characterized in that: The operating method of the optimization management system based on financial data comprises the following steps: Step S1: During the process of financial data business management, the architecture design, management and control of the financial data business management system are performed; Step S2: After completing the management and control of the financial data business management system architecture design, perform management and control of the entity attributes and data source connection of the financial data; Step S3: further optimizing, analyzing and managing the financial data business management system; Step S4: store, statistically manage and control the financial data.

6. The optimization management system based on financial data according to claim 5, characterized in that: The step S1 further comprises the following steps: The financial data business management system is designed and managed by the architecture, which includes the presentation layer, business layer, service layer and data storage layer. The presentation layer is the client that carries the interaction between users and the system. It is manifested in the system's recognition of user interaction instructions, requesting financial data from the server and displaying the returned results. The business layer is responsible for receiving user instructions for operating financial data, performing verification analysis on them, and ensuring the correctness of financial data. The service layer is used to complete the server-side business logic implementation and maintain the database connection pool to ensure continuous connection to the database, reduce system performance consumption, transform the data structure of the acquired financial data, and provide data service support for the client. The data storage layer is responsible for providing financial data query services for the service layer, which is divided into two parts: internal system data storage and external storage.

7. The optimization management system based on financial data according to claim 5, characterized in that: The step S2 further comprises the following steps: Step S21: further perform entity attribute processing on the data information of the financial data business management system, specifically, user entity attributes include user unique identification, account number, password, role authority, department and user basic information; visualization application entity attributes include application unique identification, application name description, basic configuration information, component information, creation user identification, collaboration user identification and status, wherein the basic configuration information attribute can derive application resolution, background image, cover image information, component configuration information attribute can derive component size, relative position, custom configuration information; component entity attributes include component name, identification, component type, thumbnail, default configuration information, custom configuration information, status creation user identification, wherein the custom configuration information can derive the workspace identification and component information; Step S22: The user can configure the data source of the visualization application by uploading the remote data source. If the configured data source is a remote database, the IP address of the visualization screen is added to the whitelist of remote database access to ensure normal access. After obtaining the source data, the data is filtered out or formatted to ensure data integrity and standardization of the data format.

8. The optimization management system based on financial data according to claim 5, characterized in that: The step S3 further comprises the following steps: Step S31: In the financial data business management system, the user name information is desensitized, and a weight table is established for all the surnames and corresponding names of the users in the system. The weight of each Chinese character in the table is the frequency of use of each surname in the data set. The higher the frequency of use, the greater the weight value. First, the name field in the source data is split, and the first two characters of the name are accurately queried from the set dictionary library to find the common double surname data table. If the return value is empty, it is a single-character surname, otherwise it is a double surname; Step S32: further perform scaffolding control and implementation management of the financial data business management system, register an npm account, upload the project developed by simulating built-in components to the git server, execute the npm init command in the command line, generate an npm package locally, and generate corresponding files by default in the package directory, configure the entry file, so that system managers can perform scaffolding control by simulating built-in components according to needs; Step S33: Verify and manage the components in the financial data business management system. Based on the Vue framework, the financial component files are compiled into the set financial file data that can be recognized by the browser through the babel compilation tool, effectively improving the analysis and processing efficiency of the system.

9. The optimization management system based on financial data according to claim 5, characterized in that: The step S4 further comprises the following steps: Step S41: Perform distributed backup storage of the real-time data information of the financial data business management system on the blockchain to effectively ensure data information security; Step S42: After the data information that has been backed up and stored is counted in chronological order, it is transmitted and fed back to the workbench for display.

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