Cross-system reconciliation result analysis method and device

Abstract

According to the cross-system reconciliation result analysis method and device provided by the invention, a cross-system reconciliation table of a target service is acquired, and each field in the cross-system reconciliation table is determined; configuring a target report format for the cross-system reconciliation table according to each pre-acquired general report format and each field in the cross-system reconciliation table; according to a preset target data statistical mode, extracting target statistical data from the cross-system reconciliation table with the configured target report format, and carrying out statistics on the target statistical data according to the target data statistical mode to obtain a target statistical result; and determining a target alarm rule corresponding to the target data statistical mode, and when the target statistical result meets an alarm condition of the target alarm rule, triggering an alarm. Therefore, the problems of insufficient data display, incomplete monitoring and alarm functions and the like in the cross-system account checking process of the existing big data platform can be effectively solved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method and device for analyzing cross-system reconciliation results. Background Art

[0002] In modern enterprise operations, cross-system reconciliation, a crucial step in ensuring data consistency and accuracy, has become an integral component of various business systems. With the advancement of informatization, enterprises' data sources are becoming increasingly diverse, and data interaction and synchronization between different systems are becoming increasingly complex. To address this complexity, enterprises often rely on big data platforms for data processing, reconciliation, and verification. However, while existing big data platforms have demonstrated capabilities in processing massive amounts of data and performing cross-system reconciliation, they still face significant limitations in practical applications.

[0003] Currently, big data platforms can aggregate data from various systems and perform basic verification, but flaws remain in the complete closed-loop process of cross-system reconciliation. Specifically, data display methods are limited, making it difficult to intuitively present key information, hindering analysis and decision-making efficiency. Monitoring and alerting capabilities are also incomplete, and alerts are insufficiently effective and timely, leading to delays in identifying and addressing issues. Summary of the Invention

[0004] The purpose of this application is to solve at least one of the above-mentioned technical deficiencies, especially the technical deficiencies in the prior art in data analysis and alarms for cross-system reconciliation.

[0005] In a first aspect, the present application provides a method for analyzing cross-system reconciliation results, the method comprising:

[0006] Obtain the cross-system reconciliation table for the target business and identify the fields in the cross-system reconciliation table;

[0007] Configure the target report format for the cross-system reconciliation table based on the pre-obtained general report formats and the fields in the cross-system reconciliation table;

[0008] According to the pre-set target data statistical method, the target statistical data is extracted from the cross-system reconciliation table with the configured target report format, and the target statistical data is counted according to the target data statistical method to obtain the target statistical results;

[0009] Determine the target alarm rule corresponding to the target data statistical method, and trigger an alarm when the target statistical result meets the alarm condition of the target alarm rule.

[0010] In one embodiment, the step of configuring a target report format for the cross-system reconciliation table based on pre-acquired general report formats and fields in the cross-system reconciliation table includes:

[0011] For each field in the cross-system reconciliation table, determine the general table format corresponding to the field, and set the display format of the field according to the corresponding general table format to obtain the target report format of the cross-system reconciliation table.

[0012] In one embodiment, the step of extracting target statistical data from a cross-system reconciliation table configured with a target report format according to a preset target data statistical method includes:

[0013] Determine the data items required for the data statistics method, and extract the target statistical data from the cross-system reconciliation table in the configured target report format according to each data item.

[0014] In one embodiment, after the step of performing statistics on target statistical data according to the target data statistics method to obtain target statistical results, the step further includes:

[0015] Select a target chart type that matches the target statistical results, and visualize the target statistical results using the target chart type.

[0016] In one embodiment, when the target statistical result meets the alarm condition of the target alarm rule, after the step of triggering the alarm, the following steps are included:

[0017] When the target statistical results meet the alarm conditions of the target alarm rules, an alarm message is generated;

[0018] The alarm information is sent to the users corresponding to the notification channel through the predetermined notification channel.

[0019] In one embodiment, the method further comprises:

[0020] Determine a secondary data statistical method for the target statistical result, and perform secondary statistics on the target statistical result according to the secondary data statistical method to obtain a secondary statistical result;

[0021] Determine the secondary alarm rule corresponding to the secondary data statistics method, and trigger an alarm when the secondary statistical result meets the alarm condition of the secondary alarm rule.

[0022] In a second aspect, the present application provides a result analysis device based on cross-system reconciliation, the device comprising:

[0023] The cross-system reconciliation table acquisition module is used to obtain the cross-system reconciliation table of the target business and determine the various fields in the cross-system reconciliation table;

[0024] The target report format configuration module is used to configure the target report format for the cross-system reconciliation table based on the pre-acquired general report formats and the fields in the cross-system reconciliation table;

[0025] The target statistical result determination module is used to extract target statistical data from the cross-system reconciliation table with the configured target report format according to the pre-set target data statistical method, and to perform statistics on the target statistical data according to the target data statistical method to obtain the target statistical result;

[0026] The alarm trigger module is used to determine the target alarm rule corresponding to the target data statistical method, and trigger the alarm when the target statistical result meets the alarm condition of the target alarm rule.

[0027] In one embodiment, the target report format configuration module includes:

[0028] The target report format configuration unit is used to determine the general table format corresponding to each field in the cross-system reconciliation table, and set the display format of the field according to the corresponding general table format to obtain the target report format of the cross-system reconciliation table.

[0029] In a third aspect, the present application provides a storage medium: the storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the cross-system reconciliation result analysis method as described in any one of the above embodiments.

[0030] In a fourth aspect, the present application provides a computer device, comprising: one or more processors, and a memory;

[0031] Computer-readable instructions are stored in the memory. When the computer-readable instructions are executed by one or more processors, the steps of the cross-system reconciliation result analysis method in any of the above embodiments are performed.

[0032] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0033] The cross-system reconciliation results analysis method and device provided in this application can effectively solve the problems of insufficient data display, incomplete monitoring and alarm functions, etc. in the cross-system reconciliation process of existing big data platforms. Through this method, first of all, it is possible to configure a suitable target report format for the cross-system reconciliation form, so as to clearly and intuitively present key information and improve data analysis and decision-making efficiency; secondly, with the help of a preset target data statistical method, the target data is extracted and counted from the cross-system reconciliation form, which can achieve in-depth analysis of the reconciliation data. In addition, the target alarm rules set in the method automatically trigger an alarm when the statistical results meet specific conditions, ensuring that problems can be discovered and handled in a timely manner. This cross-system reconciliation result analysis method helps to improve the integrity and real-time performance of cross-system data reconciliation, thereby improving the accuracy and reliability of data processing, and optimizing cross-system data interaction and synchronization processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0035] Figure 1 A flowchart of a method for analyzing cross-system reconciliation results provided in an embodiment of the present application;

[0036] Figure 2 A schematic diagram of the structure of an analysis device for cross-system reconciliation results provided in an embodiment of the present application;

[0037] Figure 3 A schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0039] This application provides a method for analyzing cross-system reconciliation results. The following embodiments are described using the method applied to a computer device as an example. It is understood that the computer device can be any device with data processing capabilities, including but not limited to a single server, a server cluster, a personal laptop, a desktop computer, etc. Figure 1 As shown, the method may include the following steps:

[0040] S101: Obtain a cross-system reconciliation table for a target business, and determine each field in the cross-system reconciliation table.

[0041] The target business refers to a specific business process or module that requires reconciliation in daily operations. A cross-system reconciliation table summarizes reconciliation data between different systems and contains relevant data items from different information systems. For example, if business A involves systems b and c, and business B involves systems a and c, then the cross-system reconciliation table for business A would be a summary of the reconciliation data from systems b and c. A field refers to a single data item in the cross-system reconciliation table, representing a specific information category, such as order number, amount, or time.

[0042] In this step, the computer first needs to retrieve the cross-system reconciliation tables for the target business from storage or through a network request. This can be done by exporting cleaned table data from the big data platform to a relational database, which ensures data integrity and consistency, and provides complex query support, transaction management, data security, and standardization. Alternatively, the computer can search for the target business's identifier in the cloud storage system and retrieve relevant cross-system reconciliation tables, or obtain data tables provided by external systems through an API. Next, the computer needs to identify the table structure and parse the field names and their data types.

[0043] It's understandable that obtaining the target business's cross-system reconciliation table accurately captures the reconciliation data required for that business. By accurately identifying and parsing each field in the table, we can effectively understand the data structure, ensuring data availability and consistency. This reduces analytical bias caused by misunderstood or missing fields and provides a reliable foundation for further data statistics and alerts. Therefore, obtaining the target business's reconciliation table and clarifying field information can optimize subsequent data processing, improve data consistency and accuracy, thereby increasing reconciliation efficiency and accuracy and reducing the probability of errors.

[0044] S102: Configuring a target report format for the cross-system reconciliation table according to the pre-acquired general report formats and the fields in the cross-system reconciliation table.

[0045] A general report format is a predefined data display template or structure suitable for different scenarios or business operations, including specific fields, data layout rules, and display methods. A target report format is a report structure customized for specific business or analytical needs, which can most effectively display data in cross-system reconciliation tables.

[0046] In this step, the computer device first needs to load various general report formats from the repository or predefined template library according to business needs or specific application scenarios. Among them, the structured report format definition can be obtained by querying the template information in the configuration database or by reading the configuration file. Next, the computer device needs to parse the cross-system reconciliation table and identify the various fields in the table. Among them, the table parsing library can be used to read the file and automatically identify the column name and data type. Afterwards, based on the framework of the general report format, the fields extracted from the reconciliation table are matched with the fields in the target report format. For example, the general report format may have a "date" field, and the target report format may require statistics by "month". According to this requirement, the "date" field is converted to "month", and then the data item is placed in the corresponding position of the target report format.

[0047] It can be understood that by obtaining a common report format, it is possible to select a report structure that meets the requirements from predefined templates, making subsequent format configuration more efficient and consistent. Next, by determining the various fields in the cross-system reconciliation form, it is ensured that the key information in the reconciliation data can be correctly understood and extracted, avoiding field identification errors or omissions. Finally, by configuring the target report format for the cross-system reconciliation form, the reconciliation data can be presented in a format suitable for analysis and display, ensuring the clarity and readability of the report. In this way, the process of configuring the target report format can ensure the accuracy of data display, improve the operability and decision-making efficiency of data analysis, and effectively support subsequent data statistics and alarm work.

[0048] S103: According to a pre-set target data statistical method, target statistical data is extracted from the cross-system reconciliation table in the configured target report format, and the target statistical data is counted according to the target data statistical method to obtain a target statistical result.

[0049] Target data statistical methods refer to pre-defined methods for processing and analyzing data, including summation, counting, averaging, maximum, and minimum values. The goal is to extract useful information from the data and generate aggregated statistics. Target statistical data refers to specific data items that need to be extracted and analyzed within the configured target report format based on the target data statistical method, such as amounts, quantities, and time fields related to reconciliation. Target statistical results refer to the results processed using the target data statistical method.

[0050] In this step, the computer device can first use a table parsing tool to read the data of specified columns, such as the amount column, quantity column, time column, etc., from the configured target report format to identify and extract relevant target statistical data. Afterwards, statistics on the extracted target statistical data usually need to be calculated according to a pre-set statistical method. Among them, the built-in statistical library can be used to process the data. For example, for the amount column, the total amount or average amount can be calculated. For the time column, the number of transactions within the date range may need to be calculated. After the statistical operation, the target statistical results are output, which can be in numerical form or other forms of summary data.

[0051] As you can understand, first, by extracting target statistical data, you can accurately select the data items you need to analyze from the configured target report format, preventing irrelevant data from interfering with the statistical process. Then, you process the data according to the preset statistical method to extract valuable information.

[0052] S104: Determine a target alarm rule corresponding to the target data statistical method, and trigger an alarm when the target statistical result meets the alarm condition of the target alarm rule.

[0053] Targeted alarm rules are thresholds or conditional rules set for specific data statistics, used to determine when an alarm should be triggered. Alarm rules include basic quantity-based rule-based alarms, month-over-month comparison alarms, and custom rule-based alarm configurations. Custom rules can be implemented using SQL scripts. Alarm conditions are the specific conditions that trigger an alarm when the target data statistics meet a specific rule or threshold. For example, if a statistical value exceeds a set upper limit or falls below a set lower limit, an alarm mechanism will be activated.

[0054] In this step, the computer device first associates the set target data collection method with the alarm rules. After completing the target data collection, the statistical results are compared with the preset alarm rules. For example, if the total amount exceeds the set threshold, an alarm will be triggered. At this time, an alarm notification may be sent to the user or administrator via email, SMS, or system pop-up window to indicate the anomaly.

[0055] As you can see, by defining target alert rules corresponding to the target data statistical method, we can ensure that the alert mechanism is aligned with the statistical method used for data analysis. This allows for timely feedback on potential anomalies or issues when specific statistical results occur, ensuring timely and effective monitoring and feedback of key data in reconciliation work. Subsequently, by triggering alerts, we can immediately issue warnings to relevant personnel or systems, enabling issues to be quickly identified and resolved, effectively mitigating potential risks and ensuring data consistency and accuracy. Automated alert triggering enables real-time monitoring of key indicators, improving work efficiency and enhancing the ability to quickly respond to anomalies.

[0056] In the above embodiment, it is possible to effectively solve the problems of insufficient data display, incomplete monitoring and alarm functions, etc. in the cross-system reconciliation process of the existing big data platform. Through this method, firstly, it is possible to configure a suitable target report format for the cross-system reconciliation form, so as to clearly and intuitively present key information and improve data analysis and decision-making efficiency; secondly, with the help of the preset target data statistics method, the target data is extracted and counted from the cross-system reconciliation form, which can achieve in-depth analysis of the reconciliation data. In addition, the target alarm rules set in the method automatically trigger an alarm when the statistical results meet specific conditions, ensuring that problems can be discovered and handled in a timely manner. This cross-system reconciliation result analysis method helps to improve the integrity and real-time performance of cross-system data reconciliation, thereby improving the accuracy and reliability of data processing and optimizing cross-system data interaction and synchronization processes.

[0057] In one embodiment, the step of configuring a target report format for the cross-system reconciliation table based on pre-acquired general report formats and fields in the cross-system reconciliation table includes:

[0058] For each field in the cross-system reconciliation table, determine the general table format corresponding to the field, and set the display format of the field according to the corresponding general table format to obtain the target report format of the cross-system reconciliation table.

[0059] The display format refers to how each field is presented in the report, including its display order, data type format, display accuracy, etc., with the aim of making the data easier to understand and analyze.

[0060] Specifically, the computer must match each field in the cross-system reconciliation table with its corresponding field in the common table format. This matching can be done by field name, data type, or business rules. For example, if a field in the reconciliation table is "Amount," the computer will locate the corresponding "Amount" field in the common table format and determine its location and data type in the standardized table. Once the common table format for the field is determined, the computer configures the appropriate display format for the field, including how it will be displayed in the target report. For example, if the field is a date, the computer will format it as "yyyy-MM-dd"; if the field is an amount, it might format it as currency with two decimal places. This can be automatically configured using a pre-set format template or customized based on user-entered formatting requirements. After all fields are matched and the display format is configured, the target report format is automatically generated, displaying the data in the specified format. Each field is placed in the corresponding location in the target report, and its content is displayed according to the configured display format.

[0061] In this embodiment, by determining the universal table format corresponding to the field, it is possible to ensure that each field in the cross-system reconciliation table can correspond to the standard universal format, avoiding confusion and errors caused by different field naming or data formats. This mapping ensures the uniformity and compatibility of cross-system data and ensures smooth subsequent data processing. Then, by setting the display format of the field, the most appropriate display method can be set for each field according to different business needs and user needs, improving the readability and ease of use of the report and avoiding problems such as irregular field display or information loss.

[0062] In one embodiment, the step of extracting target statistical data from a cross-system reconciliation table configured with a target report format according to a preset target data statistical method includes:

[0063] Determine the data items required for the data statistics method, and extract the target statistical data from the cross-system reconciliation table in the configured target report format according to each data item.

[0064] Specifically, based on the preset statistical method, the relevant data items involved are identified from the target report format. For example, if the statistical method is summation, fields related to the amount are selected as data items. If it is counting, fields related to the number of orders or transactions may be selected. Once it is determined which data items need to be used for statistics, the corresponding data information is extracted from the configured target report format. These data items can be extracted from the table through the table parsing library and saved as raw data sets that can be used for statistical calculations. For example, the amount column, quantity column, etc. in the report are read, and then these data items are processed according to the statistical method to perform summation, average calculation, etc.

[0065] In this embodiment, by determining the data items required for the statistical method, it is possible to ensure that only data relevant to the business objectives is extracted during statistics, thus avoiding unnecessary data redundancy and interference from irrelevant data. This greatly improves the efficiency of the statistical process and makes data processing more accurate and rapid. Subsequently, by accurately extracting the required data items in the target report format and performing calculations according to the set statistical method, the statistical and aggregation of reconciliation data can be automated, improving accuracy.

[0066] In one embodiment, after the step of performing statistics on the target statistical data according to the target data statistics method to obtain the target statistical results, the method further includes:

[0067] Select a target chart type that matches the target statistical results, and visualize the target statistical results using the target chart type.

[0068] The target chart type refers to selecting an appropriate chart format to display data based on the nature and objectives of the target statistical results. For example, a bar chart is suitable for comparing quantities across categories, a line chart is suitable for showing trends in time series, and a pie chart is suitable for showing the proportions of components.

[0069] Specifically, first analyze the data type, range, dimension and other information of the statistical results, and automatically select the appropriate chart type. For example, if the statistical result is a time series data, you can choose a line chart to show the trend; if the statistical result is data of different categories, you may choose a bar chart; if the statistical result involves the proportion of components, you may choose a pie chart. Once the appropriate chart type is determined, convert the target statistical result into a corresponding chart according to the requirements of the chart. For example, map each data item to the X-axis and Y-axis of the chart or the block position of the pie chart. For line charts, connect the data points according to the time series; for bar charts, draw columns according to different categories and set the corresponding heights; for pie charts, assign the angle and size of each block according to the proportion of the data.

[0070] In this embodiment, by selecting a target chart type that matches the target statistical results, the statistical results can be displayed in the most appropriate manner, thereby improving the effectiveness and comprehension of data visualization. Visualizing the target statistical results according to the target chart type can transform the data into an intuitive graphical display, making it easier for users to identify trends, patterns, and anomalies in the data.

[0071] In one embodiment, when the target statistical result meets the alarm condition of the target alarm rule, after the step of triggering the alarm, the following steps are included:

[0072] When the target statistical results meet the alarm conditions of the target alarm rules, an alarm message is generated;

[0073] The alarm information is sent to the users corresponding to the notification channel through the predetermined notification channel.

[0074] Alert information refers to the message or notification generated by the system based on the alert rules, which contains detailed information about the exception, such as the exception data, timestamp, severity level, etc. Notification channel refers to the communication method used to send alert information to the target user.

[0075] Specifically, the target statistical results are evaluated to see if they meet the alarm conditions of the target alarm rules. If so, an alarm message is automatically generated. The generated alarm information may include the rules that triggered the alarm, abnormal data, the time when the alarm was triggered, the alarm priority, etc. Once the alarm information is generated, the computer device will transmit the alarm information to the corresponding user according to the preset notification channel. The notification channel information is read from the pre-configured settings, and the alarm information is sent to the designated user in the corresponding manner. For example, if the notification channel is email, the email sending service is used to send the alarm information to the user's mailbox; if it is SMS, the SMS platform interface is called to send the alarm SMS. If the notification channel is a single or multiple message group chat, a robot is called to send the group message.

[0076] In this embodiment, statistical results are automatically used to determine whether anomalies exist and quickly generate alert notifications, improving alert response speed. When the target statistical results meet the alert conditions, the automatically generated alert information provides the necessary basis for subsequent processing, reducing omissions and delays and ensuring timely response to potential issues. Different notification channels ensure that alert information reaches the appropriate users, ensuring the timeliness and accuracy of alerts.

[0077] In one embodiment, the method further comprises:

[0078] Determine a secondary data statistical method for the target statistical result, and perform secondary statistics on the target statistical result according to the secondary data statistical method to obtain a secondary statistical result;

[0079] Determine the secondary alarm rule corresponding to the secondary data statistics method, and trigger an alarm when the secondary statistical result meets the alarm condition of the secondary alarm rule.

[0080] Among them, secondary data statistics are further statistical operations based on the target statistical results. Secondary statistics are typically used to reanalyze the target statistical results, such as calculating the growth rate, fluctuation range, standard deviation, etc. of the target statistical results to uncover more potential information or anomalies. Secondary statistical results are data summaries or analysis results obtained after processing the target statistical results using secondary data statistics, reflecting deeper information or trends in the target statistical results. Secondary alarm rules are specific rules set based on the secondary data statistical results to determine whether the data is abnormal. Secondary alarm rules can include certain thresholds, deviation levels, or data patterns. When these rules are met, an alarm will be triggered.

[0081] Specifically, the computer device first needs to select an appropriate secondary statistical method based on the characteristics of the target statistical results and the analysis requirements. These methods can include, for example, calculating the standard deviation, growth rate, and periodicity of the target statistical results. The appropriate secondary statistical method can be selected by querying a configuration file, a database, or user-entered rules. For example, for sales data, one might choose to calculate the monthly rate of change in sales volume or the standard deviation to understand the volatility of sales data. Once the secondary data statistical method is determined, the computer device applies the selected statistical method to the target statistical results. For example, the standard deviation of the target statistical results might be calculated to assess their volatility, or the growth rate might be calculated to analyze data trends. The data is calculated according to a predefined formula and the secondary statistical results are output. The computer device then defines corresponding alarm rules for the secondary statistical results. These rules are typically based on predetermined thresholds, fluctuation ranges, and so on. For example, if the calculated growth rate exceeds a set threshold or the standard deviation exceeds a certain expected range, the device will define conditions to trigger an alarm. The computer device automatically determines whether the alarm conditions are met by comparing the secondary statistical results with the conditions in the alarm rules. If the conditions are met, the device will trigger an alarm and generate an alarm message, prompting the user to take appropriate measures.

[0082] In this embodiment, by determining a secondary data statistical method for the target statistical results, the computer device can mine more information based on the preliminary statistical results, further improving the accuracy and reliability of the statistical analysis. Performing secondary statistics on the target statistical results according to the secondary data statistical method enables in-depth analysis of the target statistical results, ensuring that important data information is mined from various dimensions. By determining secondary alarm rules corresponding to the secondary data statistical method and triggering alarms, timely alarms can be issued when data reaches abnormal levels, avoiding delays in addressing critical issues.

[0083] The following describes the cross-system reconciliation result analysis device provided by the embodiment of the present application. The cross-system reconciliation result analysis device described below and the cross-system reconciliation result analysis method described above can be referenced to each other. Figure 2 As shown, the present application provides a result analysis device based on cross-system reconciliation, the device comprising:

[0084] The cross-system reconciliation table acquisition module 201 is used to obtain the cross-system reconciliation table of the target business and determine each field in the cross-system reconciliation table;

[0085] The target report format configuration module 202 is used to configure the target report format for the cross-system reconciliation table based on the pre-acquired general report formats and the fields in the cross-system reconciliation table;

[0086] The target statistical result determination module 203 is configured to extract target statistical data from the cross-system reconciliation table configured with the target report format according to a preset target data statistical method, and to perform statistics on the target statistical data according to the target data statistical method to obtain the target statistical result;

[0087] The alarm triggering module 204 is used to determine a target alarm rule corresponding to the target data statistical method, and trigger an alarm when the target statistical result meets the alarm condition of the target alarm rule.

[0088] In one embodiment, the target report format configuration module 202 includes:

[0089] The target report format configuration unit is used to determine the general table format corresponding to each field in the cross-system reconciliation table, and set the display format of the field according to the corresponding general table format to obtain the target report format of the cross-system reconciliation table.

[0090] In one embodiment, the target statistical result determination module 203 includes:

[0091] The target statistical data extraction unit is used to determine the various data items required for the data statistics method, and extract the target statistical data from the cross-system reconciliation table of the configured target report format according to the various data items.

[0092] In one embodiment, after the target statistical result determination module 203, the following further comprises:

[0093] The target statistical result display module is used to select a target chart type that matches the target statistical result and visually display the target statistical result according to the target chart type.

[0094] In one embodiment, after the alarm triggering module 204, the following steps are included:

[0095] An alarm information generation module is used to generate alarm information when the target statistical result meets the alarm condition of the target alarm rule;

[0096] The alarm information notification module is used to send the alarm information to the user corresponding to the notification channel through a predetermined notification channel.

[0097] In one embodiment, the apparatus further comprises:

[0098] A secondary statistical result determination module is used to determine a secondary data statistical method for a target statistical result, and perform secondary statistics on the target statistical result according to the secondary data statistical method to obtain a secondary statistical result;

[0099] The secondary alarm rule determination module is used to determine the secondary alarm rule corresponding to the secondary data statistical method, and trigger an alarm when the secondary statistical result meets the alarm condition of the secondary alarm rule.

[0100] In one embodiment, the present application also provides a storage medium storing computer-readable instructions. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the method for analyzing cross-system reconciliation results as described in any of the above embodiments.

[0101] In one embodiment, the present application also provides a computer device having computer-readable instructions stored therein. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the method for analyzing cross-system reconciliation results as described in any of the above embodiments.

[0102] Schematically, as Figure 3 As shown, Figure 3 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. The computer device 300 can be provided as a server. Figure 3 Computer device 300 includes a processing component 302, which further includes one or more processors, and memory resources represented by memory 301 for storing instructions executable by processing component 302, such as applications. The applications stored in memory 301 may include one or more modules, each corresponding to a set of instructions. Furthermore, processing component 302 is configured to execute the instructions to perform the cross-system reconciliation results analysis method of any of the above-described embodiments.

[0103] The computer device 300 may further include a power supply component 303 configured to perform power management of the computer device 300, a wired or wireless network interface 304 configured to connect the computer device 300 to a network, and an input / output (I / O) interface 305. The computer device 300 may operate based on an operating system stored in the memory 301, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or the like.

[0104] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0105] Finally, it should be noted that, in this article, relational terms such as first and second are merely used to distinguish one entity or operation from another, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprise," "include," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. Without further restriction, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element. Herein, "one," "said," "the," and "its" may also include plural forms unless the context clearly indicates otherwise. A plurality refers to at least two, such as 2, 3, 5, or 8. "And / or" includes any and all combinations of the relevant listed items.

[0106] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referenced to each other.

[0107] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for analyzing cross-system reconciliation results, characterized in that: The method comprises: Obtaining a cross-system reconciliation table for the target business and determining each field in the cross-system reconciliation table; Configuring a target report format for the cross-system reconciliation form according to the pre-acquired general report formats and the fields in the cross-system reconciliation form; According to a pre-set target data statistical method, target statistical data is extracted from the cross-system reconciliation table of the configured target report format, and the target statistical data is counted according to the target data statistical method to obtain a target statistical result; A target alarm rule corresponding to the target data statistical method is determined, and an alarm is triggered when the target statistical result meets the alarm condition of the target alarm rule.

2. The method for analyzing cross-system reconciliation results according to claim 1, characterized in that: The step of configuring a target report format for the cross-system reconciliation table according to the pre-acquired general report formats and the fields in the cross-system reconciliation table includes: For each field in the cross-system reconciliation table, the general table format corresponding to the field is determined, and the display format of the field is set according to the corresponding general table format to obtain the target report format of the cross-system reconciliation table.

3. The method for analyzing cross-system reconciliation results according to claim 1, characterized in that: The step of extracting target statistical data from a cross-system reconciliation table configured with a target report format according to a preset target data statistical method includes: Determine each data item required for the data statistics method, and extract the target statistical data from the cross-system reconciliation table in the configured target report format according to each data item.

4. The method for analyzing cross-system reconciliation results according to claim 1, characterized in that: After the step of collecting the target statistical data according to the data statistics method to obtain the target statistical results, the method further includes: A target chart type that matches the target statistical result is selected, and the target statistical result is visually displayed according to the target chart type.

5. The method for analyzing cross-system reconciliation results according to claim 1, characterized in that: After the step of triggering an alarm when the target statistical result meets the alarm condition of the target alarm rule, the method includes: When the target statistical result meets the alarm condition of the target alarm rule, generating alarm information; The alarm information is sent to the user corresponding to the notification channel through a predetermined notification channel.

6. The method for analyzing cross-system reconciliation results according to any one of claims 1 to 5, characterized in that: The method further comprises: Determining a secondary data statistical method for the target statistical result, and performing secondary statistics on the target statistical result according to the secondary data statistical method to obtain a secondary statistical result; A secondary alarm rule corresponding to the secondary data statistical method is determined, and an alarm is triggered when the secondary statistical result meets the alarm condition of the secondary alarm rule.

7. A result analysis device based on cross-system reconciliation, characterized in that: The device comprises: A cross-system reconciliation table acquisition module is used to obtain the cross-system reconciliation table of the target business and determine each field in the cross-system reconciliation table; A target report format configuration module, configured to configure a target report format for the cross-system reconciliation table based on the pre-acquired general report formats and the fields in the cross-system reconciliation table; A target statistical result determination module is used to extract target statistical data from a cross-system reconciliation table configured with a target report format according to a pre-set target data statistical method, and to perform statistics on the target statistical data according to the target data statistical method to obtain a target statistical result; The alarm triggering module is used to determine the target alarm rule corresponding to the target data statistical method, and trigger an alarm when the target statistical result meets the alarm condition of the target alarm rule.

8. The cross-system reconciliation result analysis device according to claim 7, characterized in that: The target report format configuration module includes: The target report format configuration unit is used to determine the general table format corresponding to each field in the cross-system reconciliation table, and set the display format of the field according to the corresponding general table format to obtain the target report format of the cross-system reconciliation table.

9. A storage medium, characterized in that: The storage medium stores computer-readable instructions, which, when executed by one or more processors, enable the one or more processors to perform the steps of the method for analyzing cross-system reconciliation results as described in any one of claims 1 to 6.

10. A computer device, characterized in that: include: one or more processors, and memory; The memory stores computer-readable instructions, which, when executed by the one or more processors, execute the steps of the method for analyzing cross-system reconciliation results as described in any one of claims 1 to 6.

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