Accounting data management system and method based on big data application

Abstract

The invention relates to the technical field of accounting data management, and discloses an accounting data management system and method based on big data application. Comprising a data acquisition module, a data storage module, a data processing and analysis module, a report generation module, a budget management module, a cost accounting module, a risk management module, an internal control and auditing module, a data display module and a system management and security module, the data source comprises financial software, a service system and a spreadsheet, according to the accounting data management system and method based on the big data application, a user logs in the system through the system management and security module, logs in through a subordinate login module of the system management and security module, and confirms login user information; and the user is authorized to check the range according to the user permission level, so that the safety of the enterprise accounting data can be effectively ensured, and data leakage is effectively avoided.

Description

Technical Field

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

[0002] The application of big data technology in the accounting field has achieved remarkable results. It enables the efficient processing and analysis of massive accounting data, providing enterprises with more accurate and real-time financial information. This information helps enterprises make more informed strategic decisions, improve operating efficiency, and gain a favorable position in market competition. In addition, big data technology also helps enterprises realize the automation and intelligence of financial management, reduce the workload of financial personnel, and allow them to devote more energy to more valuable analytical work.

[0003] At present, the application of big data also has certain disadvantages. As the scale of data continues to expand, data is prone to leakage, which will cause irreparable losses to the company. When data is lost, it can only be replenished, and data security is difficult to guarantee. In addition, the current complex accounting data makes it difficult for non-professionals to understand it, and professionals need to check carefully when viewing it, which is inconvenient for users to view. For this reason, we propose an accounting data management system and method based on big data application. Summary of the invention

[0004] The purpose of the present invention is to provide an accounting data management system and method based on big data application to solve the problems raised in the above background technology.

[0005] To achieve the above purpose, the present invention provides the following technical solution: an accounting data management system based on big data application, comprising:

[0006] The data collection module is responsible for collecting accounting-related data from various data sources, which involves the development of data interfaces, data conversion, and data cleaning to ensure that the collected data is accurate, complete, and usable;

[0007] The data storage module is responsible for storing the collected accounting data. It uses big data storage technology and Hadoop distributed file system to effectively meet the needs of data storage and query;

[0008] Data processing and analysis module processes and analyzes the stored data, including data mining, statistical analysis, and predictive analysis. By using data analysis algorithms and models, it discovers potential patterns, trends, and associations in the data to provide support for decision-making;

[0009] The report generation module automatically generates financial reports based on the processed and analyzed data, and can support report output in different formats and standards, ensuring that users can view them more conveniently;

[0010] The budget management module is responsible for assisting in formulating financial budget plans, monitoring budget execution, conducting budget variance analysis, and providing corresponding early warnings and adjustments;

[0011] Cost accounting module, responsible for calculating the cost of enterprise products and services, including the allocation of direct and indirect costs, and providing data for cost control and pricing strategies;

[0012] The risk management module identifies potential financial risks through monitoring and analysis of financial data, and provides risk assessment and response strategies. Financial risks include credit risk, market risk, and liquidity risk.

[0013] The internal control and audit module is responsible for conducting internal audit processes, reviewing and supervising the accuracy, completeness and compliance of accounting data, and ensuring the standardization and transparency of financial management;

[0014] The data display module displays complex accounting data in the form of intuitive charts and graphs, effectively helping users understand the data more quickly and clearly, and making decisions more easily;

[0015] The system management and security module is responsible for user authority management, data backup and recovery, system configuration and maintenance, to ensure the overall stable operation of the system and data security.

[0016] Preferably, the statements include a balance sheet, an income statement and a cash flow statement.

[0017] Preferably, the data sources include financial software, business systems and electronic spreadsheets.

[0018] Preferably, the data acquisition module collects accounting-related data from various data sources, including internal enterprise financial software, ERP system, sales system, procurement system, and external bank transaction records and tax systems.

[0019] Preferably, the data interface development includes: selecting a suitable data connection method, such as API interface, database connection and file import, according to the type and technical architecture of the data source, and adjusting the configuration connection parameters, including the server address, user name, password and port number.

[0020] Preferably, the extracted raw data is format converted and standardized during the data conversion and data cleaning to make it conform to the data format and specifications of the accounting data management system, process outliers, missing values ​​and erroneous data in the data, remove duplicate data, correct inconsistencies and errors in the data, effectively improve the accuracy of the data, screen and filter the data, retain only data related to the accounting business and valid, and perform quality inspection and verification on the cleaned data to ensure the accuracy and completeness of the data.

[0021] Preferably, the cleaned data is quality checked and verified by comparison with source data, data logic verification and data statistical analysis.

[0022] Preferably, the system management and security module further includes a login module, wherein the login module is used to confirm the login user's identity information and determine whether the user is a trusted user, wherein the user identity information includes: user name, password, fingerprint and user authority level.

[0023] An accounting data management method based on big data application, the accounting data management method based on big data application comprising the following steps:

[0024] S1. Data source integration: comprehensively sort out the data sources inside and outside the enterprise, and establish a stable and reliable data connection method, understand the data storage method, field definition, data type and data volume in each data source, determine the data update frequency and timeliness requirements, select the data connection method of the API interface according to the type and technical architecture of the data source, and adjust the configuration connection parameters;

[0025] S2. Data collection: extract accounting-related data from various data sources according to certain rules and conditions, and convert, clean and verify the extracted accounting-related data to effectively ensure the quality of the data;

[0026] S3. Data storage and management. The data collection module stores the processed data in the data storage module. Meanwhile, the data processing and analysis module analyzes and processes the stored data, uses big data analysis technology and algorithms to mine the data value, and generates financial statements and analysis reports by the report generation module. At the same time, a data backup and recovery mechanism is established to effectively ensure data security.

[0027] S4. Risk monitoring and early warning: risk indicators and thresholds are set through the budget management module, data is monitored in real time, and the budget management module and cost accounting module are used to supplement and identify financial data, issue risk warnings in a timely manner, and make adjustments;

[0028] S5. Internal control and audit: Establish a sound internal control system and conduct regular data audits to ensure compliance and data accuracy;

[0029] S6. Data display: The data display module cooperates with the report generation module to display the data in the form of charts and graphs. The user logs in to the system through the system management and security module, and logs in through the login module under the system management and security module. The login user information is confirmed and the user is authorized to view the scope according to the user's authority level, which can effectively ensure the security of the company's accounting data.

[0030] Compared with the prior art, the present invention provides an accounting data management system and method based on big data application, which has the following beneficial effects:

[0031] 1. The accounting data management system and method based on big data application, the user logs in to the system through the system management and security module, and logs in through the login module under the system management and security module, confirms the login user information, and authorizes the user to view the scope according to the user's authority level, which can effectively ensure the security of the company's accounting data and effectively prevent data leakage.

[0032] 2. In the accounting data management system and method based on big data application, the data acquisition module stores the processed data in the data storage module, while the data processing and analysis module analyzes and processes the stored data, uses big data analysis technology and algorithms to mine the data value, and generates financial statements and analysis reports by the report generation module, and at the same time establishes a data backup and recovery mechanism, which can effectively ensure the security of the data.

[0033] 3. The accounting data management system and method based on big data application, through the set data display module and report generation module, displays complex accounting data in the form of intuitive charts and graphs, effectively helping users to understand the data more quickly and clearly, and facilitate decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic diagram of the management system of the present invention;

[0035] Figure 2 It is a schematic diagram of the management method of the present invention. DETAILED DESCRIPTION

[0036] like Figure 1-Figure 2 As shown, the present invention provides a technical solution: an accounting data management system based on big data application, comprising:

[0037] The data collection module is responsible for collecting accounting-related data from various data sources, including financial software, business systems, and spreadsheets. This involves the development of data interfaces, data conversion, and data cleaning to ensure that the collected data is accurate, complete, and usable;

[0038] The data storage module is responsible for storing the collected accounting data. It uses big data storage technology and Hadoop distributed file system to effectively meet the needs of data storage and query;

[0039] Data processing and analysis module processes and analyzes the stored data, including data mining, statistical analysis, and predictive analysis. By using data analysis algorithms and models, it discovers potential patterns, trends, and associations in the data to provide support for decision-making;

[0040] The report generation module automatically generates financial reports based on the processed and analyzed data, including balance sheets, income statements and cash flow statements. It also supports report output in different formats and standards, ensuring that users can view them more conveniently.

[0041] The budget management module is responsible for assisting in formulating financial budget plans, monitoring budget execution, conducting budget variance analysis, and providing corresponding early warnings and adjustments;

[0042] Cost accounting module, responsible for calculating the cost of enterprise products and services, including the allocation of direct and indirect costs, and providing data for cost control and pricing strategies;

[0043] The risk management module identifies potential financial risks through monitoring and analysis of financial data, and provides risk assessment and response strategies. Financial risks include credit risk, market risk, and liquidity risk.

[0044] The internal control and audit module is responsible for conducting internal audit processes, reviewing and supervising the accuracy, completeness and compliance of accounting data, and ensuring the standardization and transparency of financial management;

[0045] The data display module displays complex accounting data in the form of intuitive charts and graphs, effectively helping users understand the data more quickly and clearly, and making decisions more easily;

[0046] The system management and security module is responsible for user authority management, data backup and recovery, system configuration and maintenance, to ensure the overall stable operation of the system and data security.

[0047] The data collection module collects accounting-related data from various data sources, including internal financial software, ERP system, sales system, procurement system, and external bank transaction records and tax systems.

[0048] Data interface development includes: selecting appropriate data connection methods such as API interface, database connection and file import according to the type and technical architecture of the data source, and adjusting the configuration connection parameters, including server address, user name, password and port number.

[0049] During data conversion and data cleaning, the extracted raw data will be format converted and standardized to make it conform to the data format and specifications of the accounting data management system, handle outliers, missing values ​​and erroneous data in the data, remove duplicate data, correct inconsistencies and errors in the data, effectively improve the accuracy of the data, screen and filter the data, and only retain the data that is relevant and valid to the accounting business. The cleaned data will be quality checked and verified to ensure the accuracy and completeness of the data.

[0050] The cleaned data is quality checked and verified by comparing it with the source data, performing data logic verification, and conducting data statistical analysis.

[0051] The system management and security module also includes a login module, which is used to confirm the login user's identity information and determine whether the user is a trusted user. The user's identity information includes: user name, password, fingerprint and user authority level.

[0052] An accounting data management method based on big data application, the accounting data management method based on big data application comprises the following steps:

[0053] S1. Data source integration: comprehensively sort out the data sources inside and outside the enterprise, and establish a stable and reliable data connection method, understand the data storage method, field definition, data type and data volume in each data source, determine the data update frequency and timeliness requirements, select the data connection method of the API interface according to the type and technical architecture of the data source, and adjust the configuration connection parameters;

[0054] S2. Data collection: extract accounting-related data from various data sources according to certain rules and conditions, and convert, clean and verify the extracted accounting-related data to effectively ensure the quality of the data;

[0055] S3. Data storage and management. The data collection module stores the processed data in the data storage module. Meanwhile, the data processing and analysis module analyzes and processes the stored data, uses big data analysis technology and algorithms to mine the data value, and generates financial statements and analysis reports by the report generation module. At the same time, a data backup and recovery mechanism is established to effectively ensure data security.

[0056] S4. Risk monitoring and early warning: risk indicators and thresholds are set through the budget management module, data is monitored in real time, and the budget management module and cost accounting module are used to supplement and identify financial data, issue risk warnings in a timely manner, and make adjustments;

[0057] S5. Internal control and audit: Establish a sound internal control system and conduct regular data audits to ensure compliance and data accuracy;

[0058] S6. Data display: The data display module cooperates with the report generation module to display the data in the form of charts and graphs. The user logs in to the system through the system management and security module, and logs in through the login module under the system management and security module. The login user information is confirmed and the user is authorized to view the scope according to the user's authority level. This can effectively ensure the security of the company's accounting data and effectively prevent data leakage.

[0059] The above generally describes the present invention in detail, but it is obvious to a person skilled in the art that some modifications or improvements can be made to the present invention. Therefore, modifications or improvements that do not depart from the spirit of the present invention are within the scope of protection of the present invention.

Claims

1. An accounting data management system based on big data application, characterized by: include: The data collection module is responsible for collecting accounting-related data from various data sources, which involves the development of data interfaces, data conversion, and data cleaning; The data storage module is responsible for storing the collected accounting data, using big data storage technology and Hadoop distributed file system; Data processing and analysis module processes and analyzes the stored data, including data mining, statistical analysis, and predictive analysis. By using data analysis algorithms and models, it discovers potential patterns, trends, and associations in the data to provide support for decision-making; The report generation module automatically generates financial reports based on the processed and analyzed data, and can support report output in different formats and standards; The budget management module is responsible for assisting in formulating financial budget plans, monitoring budget execution, conducting budget variance analysis, and providing corresponding early warnings and adjustments; Cost accounting module, responsible for calculating the cost of enterprise products and services, including the allocation of direct and indirect costs, and providing data for cost control and pricing strategies; The risk management module identifies potential financial risks through monitoring and analysis of financial data, and provides risk assessment and response strategies. Financial risks include credit risk, market risk, and liquidity risk. The internal control and audit module is responsible for conducting internal audit processes, reviewing and supervising the accuracy, completeness and compliance of accounting data, and ensuring the standardization and transparency of financial management; The data display module displays complex accounting data in the form of intuitive charts and graphs, effectively helping users understand the data more quickly and clearly, and making decisions more easily; The system management and security module is responsible for user authority management, data backup and recovery, system configuration and maintenance, to ensure the overall stable operation of the system and data security.

2. The accounting data management system based on big data application according to claim 1 is characterized by: The statements include the balance sheet, income statement and cash flow statement.

3. The accounting data management system based on big data application according to claim 1 is characterized by: The data sources include financial software, business systems, and electronic spreadsheets.

4. The accounting data management system based on big data application according to claim 1 is characterized by: The data acquisition module collects accounting-related data from various data sources, including internal enterprise financial software, ERP system, sales system, procurement system, and external bank transaction records and tax systems.

5. The accounting data management system based on big data application according to claim 1 is characterized by: The data interface development includes: selecting a suitable data connection method, such as API interface, database connection and file import, according to the type and technical architecture of the data source, and adjusting the configuration connection parameters, including the server address, user name, password and port number.

6. The accounting data management system based on big data application according to claim 1 is characterized by: The data conversion and data cleaning process involves format conversion and standardization of the extracted raw data to make it conform to the data format and specifications of the accounting data management system, process outliers, missing values ​​and erroneous data in the data, remove duplicate data, correct inconsistencies and errors in the data, screen and filter the data, retain only data that is relevant to the accounting business and valid, and perform quality checks and verifications on the cleaned data.

7. The accounting data management system based on big data application according to claim 6 is characterized by: The cleaned data is quality checked and verified by comparing it with the source data, performing data logic verification, and performing data statistical analysis.

8. The accounting data management system based on big data application according to claim 1 is characterized by: The system management and security module also includes a login module. The login module is used to confirm the login user's identity information and determine whether he is a trusted user. The user's identity information includes: user name, password, fingerprint and user authority level.

9. An accounting data management method based on big data application, characterized in that: The accounting data management method based on big data application includes the following steps: S1. Data source integration: comprehensively sort out the data sources inside and outside the enterprise, and establish a stable and reliable data connection method, understand the data storage method, field definition, data type and data volume in each data source, determine the data update frequency and timeliness requirements, select the data connection method of the API interface according to the type and technical architecture of the data source, and adjust the configuration connection parameters; S2. Data collection: extract accounting-related data from various data sources according to the determined rules and conditions, and perform data conversion, cleaning and verification on the extracted accounting-related data; S3, data storage and management. The data collection module stores the processed data in the data storage module. At the same time, the data processing and analysis module analyzes and processes the stored data, uses big data analysis technology and algorithms to mine the data value, and the report generation module generates financial statements and analysis reports, and establishes a data backup and recovery mechanism at the same time; S4. Risk monitoring and early warning: risk indicators and thresholds are set through the budget management module, data is monitored in real time, and the budget management module and cost accounting module are used to supplement and identify financial data, issue risk warnings in a timely manner, and make adjustments; S5. Internal control and audit: Establish a sound internal control system and conduct data audits regularly; S6. Data display: The data display module cooperates with the report generation module to display the data in the form of charts and graphs. The user logs in to the system through the system management and security module, and logs in through the login module under the system management and security module. The login user information is confirmed and the user is authorized to view the scope according to the user's authority level.

Images