Report data quality checking method and device and computer equipment

Abstract

The application discloses a report data quality checking method and device and computer equipment. The method comprises the following steps: obtaining a to-be-verified report included in a report set; performing report quality checking on each to-be-verified report to determine a report checking result of the to-be-verified report; if there is a problem report with an abnormal report checking result, determining a source object of the problem report, and sending a generated report abnormality report to the source object. The method judges whether the data in the to-be-verified report is correct by performing report quality checking on the to-be-verified report, generates a detailed report abnormality report for the problem report, and sends the report abnormality report to the source object, so that the source object can query the position of abnormal data in the report and detailed information such as abnormal conditions according to the report abnormality report, and provides an explicit problem solving scheme for the source object. The automatic checking of the report is realized, and the accuracy of the report checking is improved.

Description

Technical Field

[0001] The present invention relates to the field of information processing, and in particular to a report data quality verification method, device and computer equipment. Background Art

[0002] In a multi-level organization, the reporting data required by the headquarters must be aggregated and reported by subordinate units. Reports submitted by subordinate units may contain logical errors and abnormal fluctuations, which will be passed to the upper level reporting level.

[0003] The existing technology often uses manual verification, which is time-consuming and labor-intensive, and there is also a possibility of inspection errors. Summary of the Invention

[0004] The present invention provides a report data quality checking method, device and computer equipment to realize the verification and management of reports.

[0005] According to a first aspect of the present invention, a method for checking report data quality is provided, comprising:

[0006] Get the reports to be verified contained in the report set;

[0007] Performing report quality verification on each report to be verified, and determining the report verification result of the report to be verified;

[0008] If there is a problem report whose report verification result is a report exception, the source object of the problem report is determined, and the generated report exception report is sent to the source object.

[0009] According to a second aspect of the present invention, there is provided a report data quality checking device, comprising:

[0010] The acquisition module is used to obtain the reports to be verified contained in the report set;

[0011] A determination module, configured to perform report quality verification on each report to be verified and determine a report verification result of the report to be verified;

[0012] The sending module is used to determine the source object of the problem report if there is a problem report whose report verification result is a report abnormality, and send the generated report abnormality report to the source object.

[0013] According to a third aspect of the present invention, there is provided a computer device, comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can execute the report data quality checking method according to any embodiment of the present invention.

[0017] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the report data quality verification method described in any embodiment of the present invention when executed.

[0018] The technical solution of the embodiment of the present invention performs report quality verification on the report to be verified, determines whether the data in the report to be verified is correct, generates a detailed report exception report for the problematic report, and sends the report exception report to the source object. The source object can query the report exception report for detailed information such as the location of the abnormal data in the report and the abnormal situation, thereby providing the source object with a clear problem solution. This achieves automated report verification and improves the accuracy of report verification.

[0019] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 This is a flow chart of a report data quality verification method provided in accordance with the first embodiment of the present invention;

[0022] Figure 2 This is a flow chart of a report data quality verification method provided in accordance with the second embodiment of the present invention;

[0023] Figure 3 This is a schematic structural diagram of a report data quality checking device provided according to a third embodiment of the present invention;

[0024] Figure 4 The present invention is a schematic diagram of a computer device for implementing the report data quality checking method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described 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 making creative efforts should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Example 1

[0028] Figure 1 A flowchart of a report data quality verification method is provided for the first embodiment of the present invention. This embodiment is applicable to verifying and managing reports. The method can be executed by a report data quality verification device. The report data quality verification device can be implemented in the form of hardware and / or software. The report data quality verification device can be configured in a computer device.

[0029] like Figure 1 As shown, the method includes:

[0030] S110: Obtain the report to be verified contained in the report set.

[0031] In this embodiment, a report set can be understood as a collection of multiple reports. These can be reports sent by multiple source objects, or multiple reports sent by a single source object, such as a collection of reports sent by multiple subordinate units in a multi-level organization, or a collection of multiple reports sent by a single subordinate unit. A report can be understood as a table containing multiple statistical data, such as a power consumption statistics report or a power cost statistics report. Unverified reports can be understood as reports in a report set that have not been verified.

[0032] Specifically, obtain the reports to be verified contained in the report set.

[0033] For example, in a multi-level organization, multiple subordinate units can upload their respective reports to a superior unit's system or platform for storage through the Internet or other means. The execution entity can send an acquisition instruction to the location where the report set is stored to obtain the reports to be verified contained in the report set.

[0034] S120: Perform report quality verification on each report to be verified, and determine the report verification result of the report to be verified.

[0035] In this embodiment, the report quality verification can be understood as verifying the correctness of the content in the report, etc. The report verification result can be understood as representing the situation of the report quality verification.

[0036] Specifically, after the execution entity obtains the report to be verified, it performs report quality verification on each report to be verified. For example, it can recalculate and compare the calculation results in multiple reports, verify logical errors in the reports, or determine whether there are abnormal fluctuations. Various methods can be used to perform report quality verification on the reports and obtain multiple verification results. If the report passes the report quality verification, the report verification result of the report to be verified can be updated to "report normal", and the report is considered a normal report. If the report fails the report quality verification, the report verification result of the report to be verified can be updated to "report abnormal", and the report is considered a problem report.

[0037] S130: If there is a problem report whose report verification result is a report exception, determine the source object of the problem report, and send the generated report exception report to the source object.

[0038] In this embodiment, a problem report can be understood as a report that fails report quality verification, that is, a report that contains data errors, such as logical errors. A source object can be understood as the object to which the report is sent, such as a terminal device of a subordinate unit in a multi-level organization or an individual terminal device.

[0039] In this embodiment, a report exception report can be understood as a report that displays the cause of a report exception and report information. For example, the report exception report may include: report date, report serial number, row and column where the exception occurred, report quality verification rules, exception data, calculated data, etc.

[0040] Specifically, the executing entity obtains the report verification result. If the report verification result is that the report is abnormal, then the report is a problem report. There is abnormal data in this report. The specific location of the abnormal data in this report, the report quality verification rules for determining that the data is abnormal data, and the calculated data obtained according to the report quality verification rules, the upload date and processing date of the report, the serial number used to identify the report, etc. can be obtained and a report abnormality report can be generated for all the information. When the uploaded report is received, the corresponding contact information of the source object that uploaded the report can be automatically generated or obtained. According to the contact information of the source object, the report abnormality report can be sent to the source object through SMS or email.

[0041] For example, a report with serial number 1 for month x, year x includes the following information: electricity sales in location A (row 1, column 2) for 500,000 kilowatts; electricity sales in location B (row 2, column 2) for 400,000 kilowatts; electricity sales in location C (row 3, column 2) for 200,000 kilowatts; and total electricity sales in row 4, column 2 for 1,000,000 kilowatts. Report quality verification indicates that total electricity sales = electricity sales in location A + electricity sales in location B + electricity sales in location C. Therefore, 50 + 40 + 20 = 110, resulting in a calculated result of 1,100,000 kilowatts. However, the total electricity sales in the report are 1,000,000 kilowatts, which differs from the calculated result. Therefore, the abnormal report is a problematic report, and a report abnormality report can be generated. The report's contents may include: report date x, month x, report serial number 1, abnormality in row 4, abnormality in column 2, report quality verification rule: total electricity sales = electricity sales in location A + electricity sales in location B + electricity sales in location C, abnormal data 100, calculated data 110, etc.

[0042] This first embodiment provides a report data quality verification method that verifies the quality of a report to be verified, determines whether the data in the report is correct, generates a detailed report exception report for the problematic report, and sends the report exception report to the source object. The source object can query the report exception report for detailed information such as the location of the abnormal data in the report and the abnormality, thereby providing the source object with a clear problem solution. This achieves automated report verification and improves the accuracy of report verification.

[0043] As a first optional embodiment of this embodiment, the report data quality verification method further includes:

[0044] a1. Receive permission change requests from the report source object.

[0045] In this embodiment, the permission change application can be understood as an application for changing the editing permission of a report, which may include information about the report whose permission is to be changed and information about the source object.

[0046] Specifically, if the source object wants to modify an uploaded problem report, but the editing permission for the problem report is disabled, the source object can send a permission change request to the terminal that controls table permission changes. For example, if subordinate unit A wants to obtain editing permission for Table 2, the source object sends the permission change request to the terminal. When the permission change request sent by the source object is transmitted to the terminal, the execution entity can receive the permission change request sent by the source object, including the report information with the permission to be changed and the source object information.

[0047] b1. Based on the permission change application, find the report with the permission to be changed.

[0048] Specifically, since each report has an identifier, and each report identifier is different, based on the report information in the permission change application, the executing entity can search for the report identifier in the report library to find the report with the corresponding permission to be changed.

[0049] c1. When the permission change conditions are met, the report editing permission is opened.

[0050] In this embodiment, the permission change condition can be understood as whether it has been reviewed.

[0051] Specifically, the executing entity can display the permission change application in the form of a pop-up window, to-do list, etc. on the corresponding display terminal for reviewers to view and review. When the review is passed, the reviewer can control the report permissions by clicking on the open permission control or button. At this time, the conditions for permission change are met and a permission opening instruction is automatically generated. The executing entity can open the editing permissions of the permission report to be changed according to the permission opening instruction.

[0052] Through the configuration of the first optional embodiment of this embodiment, the auditor can control the permissions of the corresponding report based on the permission change application sent by the report source object, thereby improving the security of the report.

[0053] Example 2

[0054] Figure 2 This is a flowchart of a report data quality verification method provided in Example 2 of the present invention. This embodiment further optimizes the above-mentioned embodiment. By performing data quality verification and data warning judgment on the report to be verified, and determining the report status and report permissions based on the data quality verification and data warning judgment results, automatic report management is achieved.

[0055] like Figure 2 As shown, the method includes:

[0056] S201: Obtain the report to be verified contained in the report set.

[0057] S202: For the report to be verified included in the report set, obtain statistical items included in the report to be verified, and obtain statistical data information corresponding to the statistical items.

[0058] In this embodiment, the statistical items can be understood as statistical items in the report, such as electricity sales, electricity sales amount, etc. The statistical data information can be understood as specific data information, such as electricity sales of 20 kilowatts, electricity sales amount of 20,000 yuan, etc.

[0059] It can be known that the statistical data information of a statistical item in another report may be determined based on the statistical items in multiple reports and their corresponding statistical data information. Therefore, it is necessary to obtain the statistical data information based on the statistical items. The statistical data information in multiple reports can be obtained based on one statistical item.

[0060] Specifically, for the report to be verified included in the report set, all statistical items included in the report to be verified can be obtained, and statistical data information corresponding to each statistical item can be obtained.

[0061] For example, a report might include data showing electricity sales of 100,000 kilowatts and a sales amount of 20,000 yuan in Location A, and electricity sales of 140,000 kilowatts and a sales amount of 30,000 yuan in Location B. The corresponding statistical items are electricity sales and sales amount. The statistical data for electricity sales includes data showing electricity sales of 100,000 kilowatts in Location A and 140,000 kilowatts in Location B; the statistical data for sales amount includes data showing electricity sales of 20,000 yuan in Location A and 30,000 yuan in Location B.

[0062] S203: Perform data quality verification on the statistical data information in each statistical item to obtain a data quality verification result.

[0063] In this embodiment, data quality verification can be understood as verification of the correctness of the data. The data quality verification results may include: normal data quality and abnormal data quality.

[0064] Specifically, the statistical data information in each statistical item is identified according to the attributes of each statistical item, the related statistical data information is identified, and the related statistical data information is verified for data quality through calculation and comparison, and the data quality verification result is obtained according to the comparison situation.

[0065] Furthermore, data quality verification is performed on the statistical data information in each statistical item to obtain a data quality verification result. The specific steps may be:

[0066] a2. For the statistical data information in the statistical items, obtain the information of the same period and the corresponding information of the current period in the statistical data information, and determine the attribute dimension to which the statistical item belongs.

[0067] In this embodiment, the information of the same period can be understood as the information of the same month of the previous year corresponding to the current month. For example, the information of the same period of the nth month of the kth year corresponds to the information of the nth month of the k-1th year, which is X. k-1，n The current period information can be understood as the same information as the month of the report itself, such as the current period information of month n in year k-1 is X k-1，n Attribute dimensions can be understood as information about the characteristics of statistical items, such as the time, location, and region corresponding to the statistical items in the report.

[0068] Specifically, for statistical data information in a statistical item, the same period information and the current period information corresponding to the same period information in the statistical data information can be identified based on the time information contained in the statistical item, and the attribute dimension to which the statistical item belongs can be determined based on the attributes of the statistical item.

[0069] b2. Perform a first intermediate check based on the attribute dimensions and statistical data information.

[0070] In this embodiment, the first intermediate verification can be understood as a verification performed according to a set calculation method.

[0071] Specifically, based on the attribute dimensions and the corresponding statistical data, it is possible to determine which statistical data is itemized information and which is the aggregated information obtained by calculating the itemized information according to the corresponding calculation formula. The determined itemized information is then calculated according to the corresponding calculation formula to obtain a calculated value, which is then compared with the aggregated information to determine whether they are identical. If they are identical, the quality verification is normal; if they are different, the quality verification is abnormal.

[0072] For example, report 1 is the electricity consumption value from January to December of year k, report 2 is the electricity consumption value from January to December of year k-1, and report 3 is the total electricity consumption value of years k and k-1. The corresponding attribute dimension is the time dimension, and the corresponding calculation formula is: the total electricity consumption value of years k and k-1 is equal to the sum of the electricity consumption values ​​of each month from January to December of year k plus the sum of the electricity consumption values ​​of each month from January to December of year k-1, to obtain the calculated value, and compare the calculated value with the total electricity consumption value of years k and k-1 in report 3 to determine whether they are the same. That is, it can be expressed by a logical expression as follows: for report statistical item x, for report statistical item x, the granularity g of dimension d (such as the dimension can be a time of one year) can be subdivided into granularities g1, g2..., g n (If there are 12 months in a year, there are 12 granularities in total), the statistical data information corresponding to granularity g is xg, the statistical data information corresponding to granularity g1 is xg1, the statistical data information corresponding to granularity g2 is xg2, and the statistical data information corresponding to granularity g n The corresponding statistical data information is xg n , then the first intermediate check rule can be:

[0073] c2. Perform a second intermediate check based on the information from the same period and the corresponding information from the current period.

[0074] In this embodiment, the second intermediate verification can be understood as a verification of selecting identical information according to the report.

[0075] Specifically, compare the information of the same period and the corresponding information of this period. The two should be consistent. Determine whether they are the same. If they are the same, the quality verification is normal. If they are different, the quality verification is abnormal.

[0076] For example, Report 4 is the electricity consumption in the kth year, which includes the current information X1 of the nth month of the kth year, and the information of the same period (i.e., the electricity consumption of the nth month of the k-1th year) is X2; Report 5 is the information of the k-1th year, which includes the current information X3 of the nth month of the k-1th year, and the information of the same period (i.e., the electricity consumption of the nth month of the k-2th year) X4. X2 is compared with X3 to determine whether the two are the same.

[0077] d2. If both the first intermediate check and the second intermediate check are normal in quality check, the normal data quality is used as the data quality check result of the statistical item.

[0078] Specifically, if the statistical data information corresponding to each statistical item in the report has passed the first intermediate verification and the second intermediate verification, and there is no statistical numerical information mismatch or calculation error, that is, the quality verification is normal, then the normal data quality will be used as the data quality verification result of the statistical item.

[0079] e2. Otherwise, the data quality anomaly is used as the data quality verification result of the statistical item.

[0080] Specifically, if the calculated statistical data in a report differs from the statistical data in the report, the report has failed the first intermediate verification, but the current period's information is the same as the same period's information, indicating that the report has passed the second intermediate verification. If the calculated statistical data in a report is the same as the statistical data in the report, the report has passed the first intermediate verification, but the current period's information is different from the same period's information, indicating that the report has failed the second intermediate verification. If the calculated statistical data in a report differs from the statistical data in the report, the report has failed the first intermediate verification, but the current period's information is also different from the same period's information, indicating that the report has also failed the second intermediate verification. All three of these situations correspond to data quality verification results that include data quality anomalies as statistical items.

[0081] S204: Perform data early warning judgment on the statistical data information in each statistical item to obtain an early warning judgment result.

[0082] In this embodiment, the data early warning judgment can be understood as judging whether the data exceeds a preset range. The early warning judgment result can include: whether a data early warning is needed or not.

[0083] Specifically, the attributes of the statistical items are compared with the pre-set attributes that require early warning judgments, and the statistical data information that requires data early warning judgments is identified. The year-on-year growth rate and the month-on-month growth rate of these statistical data information are calculated, and data early warning judgments are made on the year-on-year growth rate and the month-on-month growth rate to obtain early warning judgment results.

[0084] Furthermore, a data early warning judgment is performed on the statistical data information in each statistical item to obtain an early warning judgment result. The specific steps may be:

[0085] a3. Based on the statistical data information in the statistical items, determine the year-on-year growth rate and month-on-month growth rate of the statistical items.

[0086] Specifically, according to the calculation method of the year-on-year growth rate and the month-on-month growth rate, find the corresponding statistical data information and calculate the year-on-year growth rate and the month-on-month growth rate.

[0087] For example, report 7 is the electricity consumption in the kth year, which includes the current information X for the nth month of the kth year. k,n , the electricity consumption X in month n-1 of year k k,n-1 , the electricity consumption in month n of year k-1 is X k-1,n The year-on-year growth rate is (X k,n -X k-1,n ) / X k-1,n ; The month-on-month growth rate is (X k,n -X k,n-1 ) / X k,n-1 .

[0088] b3. Determine whether the year-on-year growth rate and the month-on-month growth rate fall within the corresponding threshold ranges.

[0089] In this embodiment, the threshold intervals can be understood as different threshold intervals set according to the year-on-year growth rate and month-on-month growth rate of different statistical items, including year-on-year growth rate threshold intervals and month-on-month growth rate threshold intervals. For example, the year-on-year growth rate threshold interval for residential electricity consumption is [e,f], and the month-on-month growth rate threshold interval is [g,h]; the year-on-year growth rate threshold interval for large industrial electricity consumption is [u,i], and the month-on-month growth rate threshold interval is [t,y], etc.

[0090] Specifically, the year-on-year growth rate threshold interval and the quarter-on-quarter growth rate threshold interval corresponding to each statistical item are pre-set, and the calculated year-on-year growth rate and quarter-on-quarter growth rate are compared with the corresponding threshold intervals to determine whether the year-on-year growth rate and quarter-on-quarter growth rate belong to the corresponding threshold intervals.

[0091] For example, the normal fluctuation range of the year-on-year growth rate is set to [c, d], and the normal fluctuation range of the month-on-month growth rate is set to [a, b]. k,n -X k-1,n ) / X k-1,n ; and the month-on-month growth rate (X k,n -X k,n-1 ) / X k,n-1 , judge whether the calculated year-on-year growth rate is within the range of [c, d], and judge whether the calculated month-on-month growth rate is within the range of [a, b]. The data warning judgment rule can be: a≤(X k,n -X k,n-1 ) / X k,n-1 ≤b,c≤(X k,n -X k-1,n ) / X k-1,n ≤d, where X k,n is the statistical data of month n in year k, X k,n-1 is the statistical data of month n-1 in year k, X k-1,n is the statistical data information of the nth month in the k-1th year, [a,b] is the normal fluctuation range of the month-on-month growth rate, and [c,d] is the normal fluctuation range of the year-on-year growth rate.

[0092] d3. If yes, then there is no need to issue data warning as a warning judgment result.

[0093] Specifically, if the year-on-year growth rate falls within the year-on-year growth rate threshold range and the month-on-month growth rate falls within the month-on-month growth rate threshold range, there is no need to issue a data warning as a warning judgment result of the report.

[0094] e3. If not, a data warning will be required as a warning judgment result.

[0095] Specifically, if the year-on-year growth rate falls within the year-on-year growth rate threshold range, but the quarter-on-quarter growth rate does not; if the year-on-year growth rate does not fall within the year-on-year growth rate threshold range, but the quarter-on-quarter growth rate does; if the year-on-year growth rate does not fall within the year-on-year growth rate threshold range, but the quarter-on-quarter growth rate does not fall within the quarter-on-quarter growth rate threshold range. In all three cases, no data alert is required as a warning judgment result for this report.

[0096] S205. Determine the report verification result of the report to be verified based on the data quality verification result and the early warning judgment result.

[0097] Specifically, obtain the data quality verification results and early warning judgment results of the report to be verified, and determine whether the report to be verified has passed the data quality verification based on the data quality verification results, and determine whether the report to be verified has passed the early warning judgment results based on the early warning judgment results. If both pass, the report is normal. If one item fails or both items fail, the report is abnormal.

[0098] Furthermore, based on the data quality verification results and the early warning judgment results, the report verification results of the report to be verified are determined, including:

[0099] a4. If the data quality verification result shows that the data quality is normal and the warning judgment result shows that no data warning is required, the report will be normal as the report verification result of the report to be verified.

[0100] Specifically, the execution entity searches for the data quality verification results and warning judgment results for the report to be verified. If the data quality verification result indicates that the data quality is normal and the warning judgment result indicates that no data warning is required, it can be assumed that the total value in the statistical data information of the report to be verified corresponds to the statistical data of each sub-item used to calculate the total value, and the statistical data is within the threshold range. The report to be verified is then considered normal, and the normal report is used as the report verification result for the report to be verified.

[0101] b4. Otherwise, the report to be verified is regarded as a problem report, and the report anomaly is regarded as the report verification result of the report to be verified.

[0102] Specifically, the executing entity searches for the data quality verification results and warning judgment results for the report to be verified. If the data quality verification result indicates that the data quality is normal, the warning judgment result indicates that a data warning is required; if the data quality verification result indicates that the data quality is abnormal, the warning judgment result indicates that a data warning is not required; if the data quality verification result indicates that the data quality is abnormal, the warning judgment result indicates that a data warning is required. In all three cases, if the report to be verified has data quality issues and / or statistical data exceeds the threshold range, the report to be verified will be treated as a problem report, and the report abnormality will be treated as the report verification result for the report to be verified.

[0103] S206: For each report to be verified, determine the report status of the report to be verified according to the data quality verification result and the early warning judgment result, and perform report authority management based on the report status.

[0104] In this embodiment, the report status can be understood as a flag used to indicate whether the report is normal, such as report success, report failure, etc.

[0105] Specifically, the executing entity obtains the data quality verification results and early warning judgment short results corresponding to the report to be verified, and uses the abnormal problems corresponding to the results as the report status of the report to be verified, so that the personnel of the terminal performing the verification can know the status of each verified report based on the report status. The executing entity opens or closes the permission of the report based on whether the report status is reported successfully or failed.

[0106] Furthermore, for each report to be verified, the report status of the report to be verified is determined based on the data quality verification results and the early warning judgment results, and report authority management is performed based on the report status, including:

[0107] a5. When the data quality verification result is abnormal data quality and the warning judgment result is that no data warning is required, the report status of the report to be verified is changed to the first status, and the editing permission of the report to be verified is opened.

[0108] In this embodiment, the first state can be understood as a state for indicating that the data quality is abnormal.

[0109] Specifically, if the data quality verification result indicates a data quality anomaly and the warning judgment indicates that a data warning is not required, the report status of the report to be verified can be changed to "Submission Failed, Data Quality Anomaly." This indicates that the calculation results in the report to be verified do not correspond to the calculated data. The source object that uploaded the report to be verified can recalculate the corresponding anomaly data based on the received report anomaly report, make changes to the report to be verified, and upload it again. This will then grant editing permissions to the report to be verified.

[0110] b5. When the data quality verification result shows that the data quality is normal and the warning judgment result shows that a data warning is required, the report status of the report to be verified is changed to the second status, and the editing permission of the report to be verified is closed.

[0111] In this embodiment, the second state can be understood as a state for indicating that a data warning is required.

[0112] Specifically, if the data quality verification result is normal and the warning judgment result indicates that a data warning is required, the report status of the report to be verified can be changed to "Submitted successfully, data warning required." If the statistical data in the report to be verified exceeds the set threshold, the source object that uploaded the report to be verified will verify the data for the data warning based on the received report exception report, and the editing permission of the report to be verified will be closed.

[0113] c5. When the data quality verification result indicates that the data quality is abnormal and the warning judgment result indicates that a data warning is required, the report status of the report to be verified is changed to the third status, and the editing permission of the report is opened.

[0114] In this embodiment, the second state can be understood as a state for indicating that the data quality is abnormal and a data warning is required.

[0115] Specifically, if the data quality verification result indicates a data quality anomaly and the warning judgment indicates that a data warning is required, the report status of the report to be verified can be changed to "Submitted successfully, data quality anomaly, and data warning required." If the calculation results in the report to be verified do not correspond to the calculated data, the source object that uploaded the report to be verified will recalculate the corresponding anomaly data based on the received report anomaly report, modify the report to be verified, upload it again, and verify the data in the report that exceeds the threshold range. Editing permissions for the report to be verified can then be granted.

[0116] d5. When the data quality verification result shows that the data quality is normal and the warning judgment result shows that no data warning is required, the report status of the report to be verified is changed to the fourth status, and the editing permission of the report is closed.

[0117] In this embodiment, the fourth state can be understood as being used to display that the report has passed the report quality verification.

[0118] Specifically, if the data quality verification result indicates that the data quality is normal and the warning judgment result indicates that a data warning is not required, the report status of the report to be verified can be changed to "Submitted Successfully." The report to be verified has passed the report quality verification, that is, the data quality verification and the warning judgment. At this time, no modifications are required, and the editing permission for the report to be verified can be disabled.

[0119] The second embodiment provides a report data quality verification method that implements data quality verification and data early warning judgment on the report to be verified, thereby achieving diversified verification and making report verification more comprehensive and accurate. The report status and report permissions are managed based on the verification results, making it easier for auditors and source objects to review the report verification status. Report permissions are automatically managed, making reports more secure, achieving automated verification and management of reports, and ensuring more accurate report verification results.

[0120] Example 3

[0121] Figure 3 This is a schematic diagram of the structure of a report data quality check device provided by the third embodiment of the present invention. Figure 3 As shown, the device includes: an acquisition module 31, a determination module 32, and a sending module 33.

[0122] An acquisition module 31 is used to acquire the report to be verified contained in the report set;

[0123] The determination module 32 is used to perform report quality verification on each report to be verified and determine the report verification result of the report to be verified;

[0124] The sending module 33 is configured to determine the source object of the problem report if there is a problem report whose report verification result is a report anomaly, and send the generated report anomaly report to the source object.

[0125] The third embodiment provides a report data quality verification device that verifies the quality of a report to be verified, determines whether the data in the report to be verified is correct, generates a detailed report exception report for the problematic report, and sends the report exception report to the source object. The source object can query the report exception report for detailed information such as the location of the abnormal data in the report and the abnormal situation, thereby providing the source object with a clear problem solution. This achieves automated report verification and improves the accuracy of report verification.

[0126] Furthermore, the determination module 32 includes:

[0127] The acquisition unit is used to acquire the statistical items contained in the report to be verified contained in the report set, and acquire the statistical data information corresponding to the statistical items.

[0128] The first obtaining unit is used to perform data quality verification on the statistical data information in each statistical item to obtain a data quality verification result.

[0129] The second obtaining unit is used to perform data early warning judgment on the statistical data information in each statistical item to obtain an early warning judgment result.

[0130] The determination unit is used to determine the report verification result of the report to be verified based on the data quality verification result and the early warning judgment result.

[0131] The first obtaining unit is specifically configured to:

[0132] For the statistical data information in the statistical items, obtain the information of the same period and the corresponding information of the current period in the statistical data information, and determine the attribute dimension to which the statistical items belong;

[0133] Perform the first intermediate check based on the attribute dimensions and statistical data information;

[0134] Perform a second intermediate check based on the information from the same period and the corresponding information from the current period;

[0135] If both the first intermediate check and the second intermediate check are normal, the data quality is normal as the data quality check result of the statistical item; otherwise,

[0136] Data quality anomalies are used as data quality verification results for statistical items.

[0137] The second acquisition unit is specifically configured to:

[0138] For the statistical data information in the statistical items, determine the year-on-year growth rate and month-on-month growth rate of the statistical items;

[0139] Determine whether the year-on-year growth rate and the month-on-month growth rate fall within the corresponding threshold ranges;

[0140] If so, there will be no need for data warning as a warning judgment result;

[0141] If not, a data warning will be required as a warning judgment result.

[0142] The determination unit is specifically used for:

[0143] If the data quality verification result is that the data quality is normal and the warning judgment result is that no data warning is required, the report is normal as the report verification result of the report to be verified; otherwise,

[0144] The report to be verified is regarded as a problem report, and the report exception is regarded as the report verification result of the report to be verified.

[0145] Furthermore, the determination module 32 further includes:

[0146] The management unit is used to determine the report status of each report to be verified based on the data quality verification results and early warning judgment results, and to manage the report permissions based on the report status.

[0147] The management unit is specifically used to:

[0148] When the data quality check result is abnormal and the warning judgment result is that no data warning is required, the report status of the report to be checked is changed to the first status, and the editing permission of the report to be checked is opened;

[0149] When the data quality check result is that the data quality is normal and the warning judgment result is that a data warning is required, the report status of the report to be checked is changed to the second status, and the editing permission of the report to be checked is closed;

[0150] When the data quality check result indicates that the data quality is abnormal and the warning judgment result indicates that a data warning is required, the report status of the report to be checked is changed to the third status, and the editing permission of the report is opened;

[0151] When the data quality verification result shows that the data quality is normal and the warning judgment result shows that no data warning is required, the report status of the report to be verified is changed to the fourth status, and the editing permission of the report is closed.

[0152] Furthermore, the device further includes:

[0153] The receiving module is used to receive permission change requests sent by the report source object;

[0154] The search module is used to find the report with the permission to be changed based on the permission change application;

[0155] The opening module is used to open the editing permissions of the report when the permission change conditions are met.

[0156] The report data quality checking device provided in the embodiment of the present invention can execute the report data quality checking method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0157] Example 3

[0158] Figure 4 A schematic diagram of the structure of a computer device 10 that can be used to implement an embodiment of the present invention is shown. The computer device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The computer device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0159] like Figure 4 As shown, the computer device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 and a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the computer device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0160] Various components in the computer device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the computer device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0161] Processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors that run machine learning model algorithms, a digital signal processor (DSP), and any other suitable processor, controller, microcontroller, etc. Processor 11 executes the various methods and processes described above, such as the report data quality verification method.

[0162] In some embodiments, the report data quality verification method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on computer device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the report data quality verification method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to execute the report data quality verification method in any other appropriate manner (e.g., via firmware).

[0163] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0164] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0165] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0166] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0167] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0168] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0169] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0170] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A report data quality verification method, characterized in that: include: Get the reports to be verified contained in the report set; Performing report quality verification on each report to be verified, and determining the report verification result of the report to be verified; If there is a problem report whose report verification result is a report exception, determining the source object of the problem report and sending the generated report exception report to the source object; The step of performing report quality verification on each report to be verified and determining the report verification result of the report to be verified includes: For the report to be verified included in the report set, obtain the statistical items contained in the report to be verified, and obtain statistical data information corresponding to the statistical items; Performing data quality verification on the statistical data information in each of the statistical items to obtain a data quality verification result; Performing data early warning judgment on the statistical data information in each of the statistical items to obtain early warning judgment results; Determining the report verification result of the report to be verified based on the data quality verification result and the early warning judgment result; Among them, also include: For each report to be verified, the report status of the report to be verified is determined according to the data quality verification result and the early warning judgment result, and report authority management is performed based on the report status.

2. The method according to claim 1, characterized in that The performing of data quality verification on the statistical data information in each of the statistical items to obtain a data quality verification result includes: For the statistical data information in the statistical item, obtain the information of the same period and the corresponding information of the current period in the statistical data information, and determine the attribute dimension to which the statistical item belongs; Performing a first intermediate check based on the attribute dimension and the statistical data information; Performing a second intermediate check based on the information of the same period and the corresponding information of the current period; If both the first intermediate check and the second intermediate check are normal in quality check, the normal data quality is taken as the data quality check result of the statistical item; otherwise, The data quality abnormality is used as the data quality verification result of the statistical item.

3. The method according to claim 1, characterized in that The performing of data early warning judgment on the statistical data information in each of the statistical items to obtain an early warning judgment result includes: Determine the year-on-year growth rate and month-on-month growth rate of the statistical item based on the statistical data information in the statistical item; Determining whether the year-on-year growth rate and the month-on-month growth rate fall within corresponding threshold ranges; If so, there will be no need for data warning as a warning judgment result; If not, a data warning will be required as a warning judgment result.

4. The method according to claim 2 or 3, characterized in that Determining the report verification result of the report to be verified based on the data quality verification result and the early warning judgment result includes: If the data quality verification result is that the data quality is normal and the warning judgment result is that no data warning is required, the report is normal as the report verification result of the report to be verified; otherwise, The report to be verified is regarded as a problem report, and the report anomaly is regarded as a report verification result of the report to be verified.

5. The method according to claim 1, wherein Determining the report status of the report to be verified according to the data quality verification result and the early warning judgment result, and performing report authority management based on the report status, includes: When the data quality check result is that the data quality is abnormal and the warning judgment result is that no data warning is required, the report status of the report to be checked is changed to the first status, and the editing permission of the report to be checked is opened; When the data quality check result is that the data quality is normal and the warning judgment result is that a data warning is required, the report status of the report to be checked is changed to the second status, and the editing permission of the report to be checked is closed; When the data quality check result is that the data quality is abnormal and the warning judgment result is that a data warning is required, the report status of the report to be checked is changed to the third status, and the editing permission of the report is opened; When the data quality verification result is that the data quality is normal and the warning judgment result is that no data warning is required, the report status of the report to be verified is changed to the fourth status, and the editing authority of the report is closed.

6. The method according to claim 1, characterized in that Also includes: Receive permission change requests from report source objects; According to the permission change application, find the report with the permission to be changed; When the permission change conditions are met, the editing permission of the report is released.

7. A report data quality checking device, characterized in that: include: The acquisition module is used to obtain the reports to be verified contained in the report set; A determination module, configured to perform report quality verification on each report to be verified and determine a report verification result of the report to be verified; A sending module, configured to determine the source object of a problem report if a report verification result indicates that the problem report is abnormal, and to send the generated report abnormality report to the source object; Wherein, the determination module includes: an acquiring unit, configured to acquire, for a report to be verified contained in the report set, statistical items contained in the report to be verified, and acquire statistical data information corresponding to the statistical items; A first obtaining unit is configured to perform data quality verification on the statistical data information in each of the statistical items to obtain a data quality verification result; The second obtaining unit is used to perform data early warning judgment on the statistical data information in each statistical item to obtain an early warning judgment result; a determination unit, configured to determine a report verification result of the report to be verified based on the data quality verification result and the early warning judgment result; Wherein, the determining module further includes: The management unit is used to determine the report status of each report to be verified according to the data quality verification result and the early warning judgment result, and perform report authority management based on the report status.

8. A computer device, characterized in that: The computer device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the report data quality checking method according to any one of claims 1 to 6.

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