Data cleaning system and method for enterprise sales and research and development expense details
By generating standard templates and using artificial intelligence algorithms to process detailed sales and R&D expense data, the problems of large data volume, poor data quality, and low processing efficiency have been solved, realizing automated and intelligent data processing and improving data accuracy and corporate financial management efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-13
- Publication Date
- 2026-03-20
AI Technical Summary
Existing technologies face challenges in processing detailed sales and R&D expense data for enterprises, including large and complex data volumes, data quality issues, low efficiency of manual processing, and a lack of intelligent tools. These shortcomings result in low data accuracy and efficiency, making it difficult to meet the real-time analysis and decision support needs of enterprises.
A data cleaning system and method for enterprise sales and R&D expense details are adopted. The system generates standard templates for users to fill in data, uses artificial intelligence algorithms to verify and clean the data, calculates the expense allocation according to preset rules, and generates expense detail reports, thereby achieving automated and intelligent data processing.
It improves data accuracy and processing efficiency, reduces enterprise costs, supports enterprise applications in financial management, cost control and decision support, and ensures data intelligence and consistency.
Smart Images
Figure CN121707752A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data processing and analysis technology, and in particular to a data cleaning system and method for enterprise sales and R&D expense details. Background Technology
[0002] In modern enterprise management, sales expenses and R&D expenses are two key financial indicators that directly impact a company's profitability, innovation capabilities, and market competitiveness. Companies need to manage these expenses meticulously to ensure effective resource utilization and cost control. Current expense management suffers from the following pain points: Large and complex data volume: A company's sales and R&D activities involve a large number of transaction records, invoices, contracts, and expense reports, resulting in massive data volumes and complex structures. Traditional data processing methods struggle to efficiently process and analyze this data.
[0003] Data quality issues: Due to data entry errors, system integration problems, and human negligence, financial data often contains errors, duplicates, missing information, or inconsistencies. These problems seriously affect the accuracy and reliability of the data, leading to biased analysis results.
[0004] Manual processing is inefficient: Traditional data cleaning methods rely heavily on manual processing, which is inefficient and prone to errors. Finance personnel need to spend a lot of time verifying data, correcting errors, and filling in missing values, making it difficult to meet the needs of enterprises for real-time data analysis and rapid decision support.
[0005] Lack of intelligent tools: Most existing financial data management tools lack intelligent and automated functions, making it difficult to effectively identify and correct errors in the data. Enterprises urgently need a tool that can automatically and efficiently perform data cleaning and optimization.
[0006] In summary, existing technologies have shortcomings in processing detailed data on enterprise sales expenses and R&D expenses, including large and complex data volume, data quality issues, low efficiency of manual processing, and a lack of intelligent tools. Summary of the Invention
[0007] The purpose of this invention is to provide a data cleaning system and method for enterprise sales and R&D expense details, aiming to improve the accuracy, processing efficiency and intelligence of data, reduce enterprise costs, and thus support enterprise applications in financial management, cost control and decision support.
[0008] To achieve the above objectives, the present invention employs a data cleaning method for enterprise sales and R&D expense details, comprising the following steps: Generate a standard template with personnel information field, time record field, and project information field for users to fill in; Receive data filled in by users according to the standard template; Data analysis and processing are performed on various data to generate cost allocation data.
[0009] In the step of generating a standard template with personnel information fields, time record fields, and project information fields: The personnel information fields include personnel name, salary, five social insurances, and housing provident fund; The time recording fields include the total check-in time for the month and the time occupied by each project for the month; The project information fields include project number and project name.
[0010] In the step of generating a standard template with personnel information fields, time record fields, and project information fields for users to fill in: The standard template requires the names of personnel and project names to be pre-filled.
[0011] In the step of analyzing and processing various data to generate cost allocation data: The system verifies all data, and prompts the user to correct any data that fails verification. Import the verified data into the database; Data is cleaned and structured using artificial intelligence algorithms; Based on the preset cost allocation rules, calculate the cost allocation for each participant in each project and generate a detailed cost report.
[0012] In the process of verifying various data and prompting the user to correct data that fails verification: The verification of each data item requires checking the consistency between the total check-in time and the sum of the time occupied by each item; detecting missing values, outliers, and duplicate records; and verifying whether the data format meets the preset standards.
[0013] In the step of calculating the cost allocation for each participant in each project according to the preset cost allocation rules and generating a detailed cost report, the cost allocation for a particular participant in a particular project is... C The calculation formula is: ; in, S This represents the person's salary. I The company pays the five social insurance premiums on his behalf. H The housing provident fund contributions paid on his behalf by the company. T i This represents the amount of time the person spends on the project in that month. T totalThis represents the total number of hours the person clocked in during the month.
[0014] This invention also provides a data cleaning system for enterprise sales and R&D expense details, including a template generation module, a data receiving module, and a data processing module; wherein: The template generation module is used to generate a standard template with personnel information field, time record field and project information field for users to fill in; The data receiving module is used to receive various data filled in by the user according to the standard template; The data processing module is used to analyze and process various data to generate cost allocation data.
[0015] This invention discloses a data cleaning system and method for enterprise sales and R&D expense details. The system comprises a template generation module, a data receiving module, and a data processing module, which perform the following steps: generating a standard template with personnel information, time record, and project information fields for users to fill in; receiving the data filled in by users according to the standard template; performing data analysis and processing on the data to generate expense allocation data. Through these methods, the system improves data accuracy, processing efficiency, and intelligence, reduces enterprise costs, and supports enterprise applications in financial management, cost control, and decision support. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 This is a flowchart of the steps of the data cleaning method for enterprise sales and R&D expense details of the present invention.
[0018] Figure 2 This is a flowchart of steps S300 of the present invention.
[0019] Figure 3 This is a schematic diagram of the data cleaning system for enterprise sales and R&D expense details of the present invention.
[0020] Figure 4 This is a schematic diagram of the electronic device of the present invention.
[0021] 401 - Template generation module, 402 - Data receiving module, 403 - Data processing module. Detailed Implementation
[0022] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.
[0023] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.
[0024] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."
[0025] Please see Figures 1-2 This invention provides a data cleaning method for enterprise sales and R&D expense details, including the following steps: S100: Generates a standard template with personnel information field, time record field and project information field for users to fill in; In this embodiment, the personnel information field includes personnel name, salary, social insurance and housing provident fund; the time record field includes the total attendance time for the month and the time occupied by each project for the month; the project information field includes project number and project name; and the personnel name and project name need to be pre-filled in the standard template.
[0026] S200: Receives various data filled in by the user according to the standard template; S300: Performs data analysis and processing on various data points to generate cost allocation data.
[0027] In this embodiment, data analysis and processing are performed on various data points to generate cost allocation data. The specific process is as follows: S301: Verify all data. For data that fails verification, the system prompts the user to correct it. The verification process includes checking the consistency between the total check-in time and the sum of the time spent on each item; detecting missing values, outliers, and duplicate records; and verifying whether the data format conforms to preset standards.
[0028] S302: Import the verified data into the database; S303: Data cleaning and structuring based on artificial intelligence algorithms; S304: Calculate the cost allocation for each participant in each project according to the preset cost allocation rules, and generate a detailed cost report.
[0029] Specifically, for a particular individual, their cost-sharing amount for a particular project. C The calculation formula is: ; in, S This represents the person's salary. I The company pays the five social insurance premiums on his behalf. H The housing provident fund contributions paid on his behalf by the company. T i This represents the amount of time the person spends on the project in that month. T total This represents the total number of hours the person clocked in during the month.
[0030] Beneficial effects: 1. Improve data accuracy and standardize cost calculation methods. By leveraging artificial intelligence and machine learning technologies, errors, duplicates, missing information, or inconsistencies in financial data can be automatically identified and corrected, significantly improving data accuracy and reliability. This helps businesses make more accurate decisions in budget management, cost control, and performance evaluation.
[0031] 2. Improve processing efficiency Automating and maximizing the efficiency of financial data cleaning reduces manual intervention and improves data processing efficiency. Enterprises can quickly obtain accurate financial data to meet their needs for real-time data analysis and rapid decision support.
[0032] 3. Enhance the level of intelligence By leveraging technologies such as natural language processing, pattern recognition, and anomaly detection, intelligent cleaning and optimization of financial data can be achieved, improving the effectiveness and quality of data cleaning. Enterprises can process complex financial data more efficiently, enhancing their financial management capabilities.
[0033] 4. Reduce costs By using automated and intelligent data cleansing methods, businesses can reduce their labor and time costs. This allows them to allocate more resources to their core business, improving operational efficiency and competitiveness.
[0034] 5. Support R&D expense management Specifically targeting R&D expenses, through intelligent data cleaning and optimization, enterprises can more accurately collect and calculate R&D expenses, ensuring compliance with the R&D expense super-deduction policy, thereby saving taxes and improving the enterprise's profitability.
[0035] Corresponding to the aforementioned embodiments of the data cleaning method for enterprise sales and R&D expense details, this application also provides embodiments of a data cleaning system for enterprise sales and R&D expense details.
[0036] Figure 3 This is a block diagram illustrating a data cleaning system for enterprise sales and R&D expense details, according to an exemplary embodiment. (Refer to...) Figure 3 The system may include: a template generation module 401, a data receiving module 402, and a data processing module 403; wherein: The template generation module 401 is used to generate a standard template with personnel information field, time record field and project information field for users to fill in; The data receiving module 402 is used to receive various data filled in by the user according to the standard template; The data processing module 403 is used to perform data analysis and processing on various data to generate cost allocation data.
[0037] In this embodiment, the template generation module 401 generates a standard template with personnel information field, time record field and project information field for the user to fill in; the data receiving module 402 receives the data filled in by the user according to the standard template; and the data processing module 403 performs data analysis and processing on the data to generate cost allocation data.
[0038] Regarding the system in the above embodiments, the specific ways in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.
[0039] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.
[0040] For example, the specific steps for calculating personnel labor costs in project R&D management are as follows: Step 1. Export Excel (personnel and project data and entry templates) Download Template: The system provides a standard Excel template that includes all the necessary fields, such as personnel information, time records, and project information.
[0041] Template content: Personnel information: Name, Salary (before tax), Five social insurances (company portion), Housing provident fund (company portion).
[0042] Time record: Total check-in time (hours) for the month, and time spent on each item (hours).
[0043] Project Information: Project Number, Project Name.
[0044] Objective: To ensure that users fill in data in a standard format to facilitate subsequent import and processing.
[0045] Related data: The data exported by the system should include information linking personnel to projects to ensure that users can accurately match the information when filling it out.
[0046] For example, the template can be pre-filled with personnel names and project numbers, and users only need to fill in the specific attendance times and cost information.
[0047] Step 2. Fill in the Excel spreadsheet (clock-in / out times, employee salaries, etc.) (1) User fills in Operators: Finance personnel or relevant responsible persons.
[0048] Function: Fill in the data: Fill in the Excel template based on the actual staff salaries, attendance records, and project occupancy.
[0049] Key fields: Personnel Information: Ensure that salary, social insurance, and housing provident fund information are accurate.
[0050] Time Record: Fill in the total attendance time and time spent on each project for each person in the current month, ensuring that the total does not exceed the total attendance time for the current month.
[0051] Project cost allocation: Based on the actual usage, fill in the cost allocation ratio for each project or the directly calculated cost value.
[0052] Precautions: Data accuracy: Ensure that the data entered is accurate and error-free to avoid errors affecting the calculation results.
[0053] Boundary cases: Handle special cases, such as when total_hours is 0 or when personnel are not involved in any projects.
[0054] (2) Data Validation After completing the form, users should check the completeness and accuracy of the data themselves to ensure that there are no omissions or errors.
[0055] Pay special attention to the reasonableness of total_hours and project_hours, and ensure that the sum of project_hours does not exceed total_hours.
[0056] Step 3. Import Excel (Analyze and process the data) (1) Data import Operators: System administrators or finance personnel.
[0057] Function: Upload file: Upload the completed Excel file to the system.
[0058] Data verification: System Validation: The system automatically validates the data format and integrity, checking for missing or incorrect data.
[0059] Error message: For data that failed verification, the system prompts the user to correct it.
[0060] Import data into the database: Personnel Table: Stores personnel names, salaries, social insurance and housing provident fund information.
[0061] Time record table: Stores personnel number, month, total clock-in time, project number, and project usage time.
[0062] Project table: Stores project number and project name.
[0063] Objective: To import data into a database to facilitate subsequent calculations and analysis.
[0064] (2) Data processing Calculate cost allocation: Project percentage calculation: \text{project_ratio}=\frac{\text{project_hours}}{\text{total_hours}} Project cost calculation: \text{project_cost}=(\text{salary}+\text{insurance}+\text{housing_fund})\times\text{project_ratio} Multi-project processing: Ensure that the sum of the cost percentages of all projects does not exceed 1, and calculate the cost allocation for each project separately.
[0065] Data validation: Boundary case handling: Handling special cases, such as when total_hours is 0 or when personnel are not involved in any project.
[0066] Policy compliance: Ensure that the allocation of expenses complies with relevant financial and tax policies.
[0067] Step 4. Generate R&D expense management (1) Summarize the calculation results Operators: System administrators or finance personnel.
[0068] Function: Total Costs: For each project, calculate the total cost for all participants.
[0069] Generate a detailed list: Project Name: Displays the project name.
[0070] Participants: List the people who participated in the project.
[0071] Project cost allocation for personnel: Displays the cost allocation for each person in the project.
[0072] Total project cost: Calculate the total cost of the project.
[0073] Objective: To generate detailed cost allocation information for users to view and analyze.
[0074] (2) Results Export Function: Export to Excel: Export the calculation results to an Excel file for easy archiving and further analysis by users.
[0075] Data presentation: Month and Project Selection: Users can select specific months and projects to view as needed.
[0076] Data validation: Display each employee's salary, social insurance, housing provident fund, and cost allocation for each project, calculate the differences, and ensure data consistency.
[0077] Objective: To provide flexible viewing and export functions to meet different user needs. Specific implementation examples: Taking personnel R&D expenses as an example, a technology company specializing in software development has multiple R&D projects and needs to record, manage, and report R&D expenses in detail every month. Traditional expense management methods rely on manual operations, which are inefficient and prone to errors. The company urgently needs an efficient and intelligent expense management solution.
[0079] System Application The company decided to adopt an AI-based R&D expense data cleaning and allocation system to improve the efficiency and accuracy of expense management. The following is a detailed description of the system's application process and results: 1. System Deployment and Training The company collaborated with the system vendor to complete the system deployment and initial setup.
[0080] The system vendor provided detailed user manuals and training materials to ensure that company employees could quickly get started. The company organized a half-day training session covering system usage, data import and export operations, cost calculation principles, and troubleshooting for common problems.
[0081] The training is for finance personnel, project managers, and some R&D personnel, ensuring that employees in different positions can master how to use the system.
[0082] 2. Data Import and Processing Data preparation: Based on the templates provided by the system, the finance staff collected and organized the employee salary information, attendance records, and project occupancy time for the current month.
[0083] The data includes: Personnel information: name, salary, social insurance and housing provident fund.
[0084] Time record: Total check-in time for the month, and time spent on each project.
[0085] Project Information: Project Number and Project Name.
[0086] Data import: The finance staff uploaded the prepared Excel file through the system interface.
[0087] The system automatically verified the data format and integrity, and prompted the correction of several minor errors.
[0088] The validated data was successfully imported into the database.
[0089] Data processing: The cost calculation engine automatically reads the imported data and calculates the cost allocation for each person in each project.
[0090] The system uses intelligent algorithms to process text data, identify personnel activities, and detect anomalies, ensuring the accuracy of cost allocation.
[0091] The calculation results show that Zhang San, a research and development staff member, has an allocation of 8,000 yuan for project RD08 and 6,000 yuan for project RD09. Results are displayed and exported.
[0092] Results Display: The finance staff viewed the expense allocation details through the system interface, including: Project names: RD08, RD09, RD10.
[0093] Participants: Zhang San, Li Si, Wang Wu.
[0094] Project expenses allocated to personnel: Zhang San's expense in RD08 is 8000 yuan, and his expense in RD09 is 6000 yuan; the expense allocation for Li Si and Wang Wu is also clearly shown.
[0095] Total project cost: 20,000 yuan for RD08, 15,000 yuan for RD09, and 18,000 yuan for RD10.
[0096] Data export: The finance staff exported the calculation results to an Excel file, which contained detailed expense allocation data.
[0097] The exported files were used for monthly financial reporting and project management analysis.
[0098] 4. Monthly Report and Analysis Monthly Report: The finance staff used the exported data to create a detailed monthly financial report, which clearly showed the cost allocation and total cost of each project.
[0099] The report was submitted to management for decision support and budget management.
[0100] Project Management Analysis: Project managers used cost allocation data to analyze the cost structure of each project and optimize resource allocation.
[0101] For example, it was discovered that the cost of project RD08 was high. Further analysis revealed that this was due to the development of a certain technology. The project team then decided to optimize the development process to reduce costs.
[0102] Improve efficiency: Automated processing: The system automatically completes data import, cost calculation and result export, greatly reducing the time spent on manual operations.
[0103] Quick start: After a short training session, even non-professionals can become proficient in using the system, improving work efficiency.
[0104] Improve accuracy: Intelligent Algorithm: The system uses artificial intelligence technology to process data, reducing human error and improving the accuracy of cost allocation.
[0105] Anomaly detection: The system automatically detects and corrects anomalies to ensure data consistency and accuracy.
[0106] Clear Records and Management: Detailed breakdown: The system generates a detailed breakdown of expense allocations, making it easy for companies to clearly record and manage R&D expenses.
[0107] Data traceability: The system records every step of the operation and data change, which facilitates traceability and auditing.
[0108] For ease of reporting and analysis: Standardized reporting: The system generates standardized financial reports, making it easier for companies to report to management and manage budgets.
[0109] Data analysis: Project managers can use cost allocation data to conduct cost analysis and resource optimization, thereby improving project management.
[0110] Reduce costs: Reduced labor costs: The system reduces the time and manpower required for manual operations, thereby lowering the company's operating costs.
[0111] Optimize resource allocation: Through cost analysis, companies can optimize resource allocation and reduce unnecessary expenses.
[0112] By applying this system, the technology company significantly improved the efficiency and accuracy of its expense management. Even non-professionals can quickly get started and clearly record and manage R&D expenses. The detailed expense allocation breakdown and standardized financial reports generated by the system facilitate monthly reporting and project management analysis, optimizing resource allocation and reducing operating costs. This example fully demonstrates the system's significant advantages in improving enterprise expense management and reducing costs.
[0113] Accordingly, this application also provides an electronic device, including: one or more processors; a memory for storing one or more programs; and when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the data cleaning method for enterprise sales and R&D expense details as described above. Figure 4 The diagram shown is a hardware structure diagram of any device with data processing capabilities, used in a data cleaning system for enterprise sales and R&D expense details provided by an embodiment of the present invention. (Except for...) Figure 4In addition to the processor, memory, and network interface shown, any data processing device in the embodiment may also include other hardware depending on the actual function of the data processing device, which will not be described in detail here.
[0114] Accordingly, this application also provides a computer-readable storage medium storing computer instructions, which, when executed by a processor, implement the data cleaning method for enterprise sales and R&D expense details as described above. The computer-readable storage medium can be an internal storage unit of any data-processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data-processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data-processing device, and can also be used to temporarily store data that has been output or will be output.
[0115] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.
[0116] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.
Claims
1. A data cleaning method for enterprise sales and R&D expense details, characterized in that, Includes the following steps: Generate a standard template with personnel information field, time record field, and project information field for users to fill in; Receive data from users based on a standard template; Data analysis and processing are performed on various data to generate cost allocation data.
2. The data cleaning method for enterprise sales and R&D expense details as described in claim 1, characterized in that, In the steps of generating a standard template with personnel information field, time record field, and project information field: The personnel information fields include personnel name, salary, five social insurances, and housing provident fund; The time recording fields include the total check-in time for the month and the time occupied by each project for the month. The project information fields include project number and project name.
3. The data cleaning method for enterprise sales and R&D expense details as described in claim 2, characterized in that, In the step of generating a standard template with personnel information fields, time record fields, and project information fields for users to fill in: The standard template requires the names of personnel and project names to be pre-filled.
4. The data cleaning method for enterprise sales and R&D expense details as described in claim 3, characterized in that, In the steps of analyzing and processing various data to generate cost allocation data: The system verifies all data and prompts the user to correct any data that fails verification. Import the verified data into the database; Data is cleaned and structured using artificial intelligence algorithms; Based on the preset cost allocation rules, calculate the cost share for each participant in each project and generate a detailed cost report.
5. The data cleaning method for enterprise sales and R&D expense details as described in claim 4, characterized in that, During the data verification process, and in the steps where the system prompts the user to correct any data that fails verification: The verification of each data item requires checking the consistency between the total check-in time and the sum of the time occupied by each item; detecting missing values, outliers, and duplicate records; and verifying whether the data format meets the preset standards.
6. The data cleaning method for enterprise sales and R&D expense details as described in claim 5, characterized in that, In the steps of calculating the cost allocation for each participant in each project according to the preset cost allocation rules and generating a detailed cost report, for a certain person, their cost allocation for a certain project is... C The calculation formula is: ; in, S This represents the person's salary. I The company pays the five social insurance premiums on his behalf. H The housing provident fund contributions paid on his behalf by the company. T i This represents the amount of time the person spends on the project in that month. T total This represents the total number of hours the person clocked in during the month.
7. A data cleaning system for enterprise sales and R&D expense details, employing the data cleaning method for enterprise sales and R&D expense details as described in claim 1, characterized in that... It includes a template generation module, a data receiving module, and a data processing module; among which: The template generation module is used to generate a standard template with personnel information field, time record field and project information field for users to fill in; The data receiving module is used to receive various data filled in by the user according to the standard template; The data processing module is used to analyze and process various data to generate cost allocation data.