Method for automatically processing data of statistical report

Abstract

The invention belongs to the technical field of data processing, and particularly relates to a statistical report automatic data processing method which comprises the following steps: S1, a task engine: analyzing a user historical operation record through a manual or machine learning algorithm, and coding a table operation mode commonly used by a user; s2, a real-time monitoring and feedback mechanism: when the system executes an automatic task, when an exception is found, the system automatically pauses or reminds a user to intervene, so that the accuracy and the safety of data processing are ensured; and S3, expansibility and compatibility: the system supports mainstream spreadsheet software and form files in different formats, and provides an API interface at the same time, so that integration with other office systems is facilitated, and wider application scene coverage is realized. According to the method, the form task mode defined by the user can be automatically identified, and the repeated operation can be automatically executed or assisted to be efficiently completed by the user, so that the office efficiency is remarkably improved, human errors are reduced, and the employees can put more energy into more creative and decisive work.

Description

Technical Field

[0001] The invention belongs to the technical field of data processing, and in particular is a method for automatically processing data in statistical reports. Background Art

[0002] In the modern office environment, spreadsheets (such as Excel, Google Sheets, etc.) have become an indispensable tool for data processing, analysis, and report generation.

[0003] However, many employees need to frequently perform a large number of repetitive and mechanical spreadsheet operations in their daily work, such as data entry, format adjustment, formula calculation, data filtering and sorting, etc. These operations are not only time-consuming and labor-intensive, but also prone to errors, which seriously affects work efficiency and accuracy. With the rapid development of artificial intelligence and automation technology, a method for automated data processing in statistical reports is proposed to address the above problems. Summary of the invention

[0004] In order to make up for the deficiencies of the prior art and solve at least one technical problem raised in the background technology, the present invention proposes a method for automatically processing data in statistical reports.

[0005] The technical solution adopted by the present invention to solve the technical problem is: a method for automatically processing data in a statistical report according to the present invention comprises the following steps:

[0006] S1: Task engine: Analyzes user historical operation records through manual or machine learning algorithms and encodes the user's commonly used form operation modes;

[0007] S2: Real-time monitoring and feedback mechanism: When the system is executing automated tasks, it will automatically pause or remind the user to intervene if an abnormality is found, ensuring the accuracy and security of data processing;

[0008] S3: Scalability and compatibility: The system supports mainstream spreadsheet software and spreadsheet files in different formats, and provides an API interface to facilitate integration with other office systems to achieve wider application scenario coverage.

[0009] Preferably, the table operation mode proposed in S1 includes specific format adjustment, common formula application and data screening conditions, and a task script library is constructed, so that the system can automatically execute tasks, including but not limited to batch data entry, automatic format adjustment, condition screening and sorting, and formula batch application.

[0010] Preferably, the machine learning proposed in S1 allows computers to learn patterns in data and make predictions or decisions without being explicitly programmed.

[0011] Preferably, the construction task script library is used to guide the computer to automatically perform a series of operations through a pre-written instruction set.

[0012] Preferably, the API interface proposed in S3 is an application programming interface, which allows data and functions to be exchanged between different software applications.

[0013] Preferably, the anomalies found in S2 include system anomalies and user operation anomalies. When the system anomaly occurs, the system will adopt an exception handling mechanism to handle it.

[0014] Preferably, the exception handling mechanism comprises the following steps:

[0015] A1: Production error report;

[0016] A2: Trigger the exception handler;

[0017] A3: Resource isolation;

[0018] A4: Rollback operation;

[0019] A5: Restart the service or process;

[0020] A6: Notify the administrator.

[0021] Preferably, when the user operation is abnormal, the system automatically pauses or reminds the user to intervene, thereby ensuring the accuracy and security of data processing.

[0022] Beneficial effects of the present invention:

[0023] The present invention provides a method for automatically processing data in statistical reports, which can automatically identify user-defined table task patterns, automatically execute or assist users to efficiently complete these repetitive operations, thereby significantly improving office efficiency, reducing human errors, and allowing employees to devote more energy to more creative and decision-making work. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings described herein are used to provide further understanding of the present invention and constitute a part of this application. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0025] In the attached picture:

[0026] Figure 1 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0027] 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.

[0028] Specific examples are given below.

[0029] The present invention provides a method for automatically processing data in statistical reports, comprising the following steps:

[0030] S1: Task engine: Analyzes user historical operation records through manual or machine learning algorithms and encodes the user's commonly used form operation modes;

[0031] S2: Real-time monitoring and feedback mechanism: When the system is executing automated tasks, it will automatically pause or remind the user to intervene if an abnormality is found, ensuring the accuracy and security of data processing;

[0032] When an abnormality is detected, the system will take the following measures:

[0033] Real-time monitoring system

[0034] Data flow monitoring: Monitor the flow of data in automated tasks and perform real-time calculations with big data learning models to ensure that every step from data input to output meets expectations.

[0035] Performance indicator monitoring: Set key performance indicators and monitor the changes of these indicators in real time to evaluate the efficiency and stability of task execution.

[0036] Anomaly detection: Use machine learning algorithms or preset rules to automatically identify abnormal patterns and run corresponding solutions in a timely manner to ensure stable system operation.

[0037] Automatic pause mechanism

[0038] Threshold triggering: When the monitored abnormal indicators exceed the preset threshold, the system automatically triggers the pause mechanism to stop the execution of the current task to avoid the expansion of errors.

[0039] Intelligent judgment: Combine contextual information and historical data to intelligently judge the severity and impact of the anomaly through big data models, and decide whether to suspend the task or take other measures.

[0040] Log recording: When a task is paused, detailed log information is recorded, including the time, location, and cause of the exception, providing a basis for subsequent analysis.

[0041] User intervention mechanism

[0042] Instant notification: Instantly notify users of abnormal situations and task suspension information through email, SMS, in-app notification, etc., to ensure that users can understand the situation in a timely manner.

[0043] Intervention interface: Provides a user-friendly intervention interface where users can view exception details, adjust parameter settings, restart tasks, or perform other operations.

[0044] Operation guide: Provide operation guides or FAQs in the intervention interface to help users solve problems quickly.

[0045] S3: Scalability and compatibility: The system supports mainstream spreadsheet software and spreadsheet files in different formats, and provides an API interface to facilitate integration with other office systems to achieve wider application scenario coverage.

[0046] The table operation mode proposed in S1 includes specific format adjustment, common formula application and data screening conditions. By building a task script library, the system can automatically perform tasks, including but not limited to batch data entry, automatic format adjustment, condition screening and sorting, and batch application of formulas.

[0047] Machine learning, as proposed in S1, allows computers to learn patterns in data and make predictions or decisions without being explicitly programmed.

[0048] Build a task script library, which is a pre-written set of instructions used to instruct the computer to automatically perform a series of operations.

[0049] The API interface proposed in S3 is an application programming interface that allows the exchange of data and functions between different software applications.

[0050] Abnormalities found in S2 include system abnormalities and user operation abnormalities. When a system abnormality occurs, the system will adopt an abnormality handling mechanism to handle it:

[0051] The exception handling mechanism includes the following steps:

[0052] A1: Production error report;

[0053] A2: Trigger the exception handler;

[0054] A3: Resource isolation;

[0055] A4: Rollback operation;

[0056] A5: Restart the service or process;

[0057] A6: Notify the administrator.

[0058] Generate error report: The operating system records specific information of the exception, including error code, occurrence time, possible cause, etc. This information is usually recorded in the system log for analysis by system administrators or developers.

[0059] Trigger exception handler: According to the triggered exception situation, the operating system automatically triggers the corresponding exception handler for processing through the predefined exception handler. For some exceptions that do not have corresponding methods, a specific error report is generated and recorded in the system log for developers to make corresponding repairs and add to the exception handler database.

[0060] Resource isolation: To prevent exceptions from spreading and affecting other normally running programs or services, the operating system may take resource isolation measures, such as limiting or cutting off the resource access rights of abnormal processes and isolating them to run in a sandbox environment.

[0061] Rollback operation: When the exception handling mechanism is running, the system records the specific processing location and creates a log. If the exception cannot be handled, the system will try to roll back to the state before the exception occurred to maintain data consistency and integrity. The rollback operation is an important mechanism to ensure that the system can be restored to a known good state when an exception occurs. Whether it is a database transaction or a file system operation, the rollback operation undoes the executed operation and restores it to the state before the transaction started, thereby ensuring data consistency and system stability.

[0062] Restarting services or processes: For some services or processes that can be automatically restored, the operating system attempts to restart the service or process to restore normal operation. When the abnormal situation is more serious and threatens the overall stability and security of the system, the operating system will safely shut down or restart the system to prevent more serious consequences.

[0063] Notify administrators: When the system is restarted, the system will record specific information about the exception, including the specific reasons that caused the system to restart, and send it to administrators and developers.

[0064] When user operations are abnormal, the system automatically pauses or reminds the user to intervene, ensuring the accuracy and security of data processing.

[0065] Task engine: Analyze user historical operation records through manual or machine learning algorithms, encode users' commonly used table operation modes, such as specific format adjustments, common formula applications, data filtering conditions, etc., build a task script library, and the system can automatically execute tasks, including but not limited to batch data entry, automatic format adjustment, conditional filtering and sorting, formula batch application, etc.

[0066] Real-time monitoring and feedback mechanism: When the system is executing automated tasks, it will automatically pause or remind users to intervene if an abnormality is found, ensuring the accuracy and security of data processing.

[0067] Scalability and compatibility: The system supports mainstream spreadsheet software and spreadsheet files in different formats, and provides an API interface to facilitate integration with other office systems to achieve wider application scenario coverage.

[0068] Advantages of the present invention:

[0069] Significantly improve efficiency: automate repetitive operations and significantly reduce working time.

[0070] Reduce errors: Avoid human error by precisely executing pre-set tasks.

[0071] Enhanced flexibility: Users can customize automated tasks according to their needs to meet personalized office requirements.

[0072] Easy to use: double-click to run, no learning cost.

[0073] Wide compatibility: supports a variety of spreadsheet software and formats, facilitating cross-platform applications.

[0074] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A method for automatically processing data in statistical reports, characterized in that: The following steps are involved: S1: Task engine: Analyzes user historical operation records through manual or machine learning algorithms and encodes the user's commonly used form operation modes; S2: Real-time monitoring and feedback mechanism: When the system is executing automated tasks, it will automatically pause or remind the user to intervene if an abnormality is found, ensuring the accuracy and security of data processing; S3: Scalability and compatibility: The system supports mainstream spreadsheet software and spreadsheet files in different formats, and provides an API interface to facilitate integration with other office systems to achieve wider application scenario coverage.

2. The method for automatically processing data in statistical reports according to claim 1, characterized in that: The table operation mode proposed in S1 includes specific format adjustment, common formula application and data screening conditions. By building a task script library, the system can automatically execute tasks, including but not limited to batch data entry, automatic format adjustment, condition screening and sorting, and formula batch application.

3. The method for automatically processing data in statistical reports according to claim 1, characterized in that: Machine learning, as proposed in S1, allows computers to learn patterns in data and make predictions or decisions without being explicitly programmed.

4. The method for automatically processing data in statistical reports according to claim 2, characterized in that: The construction task script library is used to instruct the computer to automatically perform a series of operations through a pre-written instruction set.

5. The method for automatically processing data in statistical reports according to claim 1, characterized in that: The API interface proposed in the S3 is an application programming interface that allows data and functions to be exchanged between different software applications.

6. The method for automatically processing data in statistical reports according to claim 1, characterized in that: The abnormalities found in S2 include system abnormalities and user operation abnormalities. When the system is abnormal, the system will adopt an abnormality handling mechanism to handle it.

7. The method for automatically processing data in statistical reports according to claim 6, characterized in that: The exception handling mechanism includes the following steps: A1: Production error report; A2: Trigger the exception handler; A3: Resource isolation; A4: Rollback operation; A5: Restart the service or process; A6: Notify the administrator.

8. The method for automatically processing data in statistical reports according to claim 6, characterized in that: When the user operation is abnormal, the system automatically pauses or reminds the user to intervene, thereby ensuring the accuracy and security of data processing.

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