CN112070364A

CN112070364A - Data analysis early warning method, system, computing device and computer readable storage medium

Info

Publication number: CN112070364A
Application number: CN202010838986.5A
Authority: CN
Inventors: 卢泓伶; 聂亚兰; 刘志青; 黄信宇; 卢永强; 谢荣江; 王俊海
Original assignee: Guangdong Xintong Communication Co ltd
Current assignee: Guangdong Xintong Communication Co ltd
Priority date: 2020-08-19
Filing date: 2020-08-19
Publication date: 2020-12-11

Abstract

The invention discloses a data analysis early warning method, a data analysis early warning system, computing equipment and a computer readable storage medium. The method comprises the following steps: setting a first threshold and a second threshold for a data set and for respective subsets of data belonging to the data set; determining whether the input data corresponding to each data subset exceeds a first threshold of its corresponding data subset, determining whether the sum of the input data exceeds a first threshold of the data set, determining whether an excess magnitude of the input data corresponding to each data subset exceeding the first threshold of its corresponding data subset is greater than a second threshold of its corresponding data subset, and determining whether an excess magnitude of the sum of the input data exceeding the first threshold of the data set is greater than the second threshold of the data set; and outputting early warning information aiming at the input data or the input data sum with the exceeding magnitude value larger than the corresponding second threshold value. The invention can assist the user to quickly find out the problem of data non-compliance and improve the working efficiency.

Description

Data analysis early warning method, system, computing device and computer readable storage medium

Technical Field

The invention relates to the technical field of computers, in particular to a data analysis early warning method, a data analysis early warning system, computing equipment and a computer readable storage medium.

Background

Budgeting is a systematic way for an organization, such as an enterprise, to allocate resources, such as financial, physical, human, etc., reasonably to achieve a given goal. Enterprises can monitor the implementation progress of targets through budgets, help control expenses, and predict cash flow and profits of enterprises.

The comprehensive budget management is a main method for managing and controlling the interior of an enterprise, the enterprise utilizes an informationized comprehensive budget management system to improve the working efficiency, and the comprehensive budget management is realized through key steps of budget planning, budget control, budget analysis and the like.

The traditional budget analysis mode needs to collect a lot of information, then a lot of analysis reports are compiled, and the difference between the actual generation amount and the budget can be obtained through a lot of calculation, so that time and labor are wasted, and the problems existing in the analysis results are difficult to timely and comprehensively find after the difference information is obtained.

Disclosure of Invention

The invention provides a data analysis early warning method, which comprises the following steps: setting a first threshold and a second threshold for a data set and for respective subsets of data belonging to the data set; determining whether the input data corresponding to each data subset exceeds a first threshold of its corresponding data subset, determining whether the sum of the input data exceeds a first threshold of the data set, determining whether an excess magnitude of the input data corresponding to each data subset exceeding the first threshold of its corresponding data subset is greater than a second threshold of its corresponding data subset, and determining whether an excess magnitude of the sum of the input data exceeding the first threshold of the data set is greater than the second threshold of the data set; and outputting early warning information aiming at the input data or the input data sum with the exceeding magnitude value larger than the corresponding second threshold value.

In one embodiment of the present invention, the first threshold is a predetermined value, and the second threshold is a predetermined percentage.

In one embodiment of the invention, the first threshold of the data set is determined by the sum of the first thresholds of the respective data subsets.

In one embodiment of the invention, at least one of the first threshold and the second threshold is resettable.

In an embodiment of the invention, the outputting the warning information includes displaying on a screen of the electronic device in a form of a pop-up box.

In an embodiment of the present invention, the data analysis early warning method includes displaying a data analysis result on a screen of the electronic device in the form of an analysis chart.

In an embodiment of the present invention, the data set is a budget application form, and the data subset is each individual budget application item in the budget application form.

The invention also provides a data analysis early warning system, which comprises: a threshold setting module for setting a first threshold and a second threshold for a data set and for respective subsets of data belonging to the data set; a data analysis module for determining whether the input data corresponding to each data subset exceeds a first threshold of its corresponding data subset, determining whether the sum of the input data exceeds a first threshold of the data set, determining whether an excess magnitude of the input data corresponding to each data subset exceeding the first threshold of its corresponding data subset is greater than a second threshold of its corresponding data subset, and determining whether an excess magnitude of the sum of the input data exceeding the first threshold of the data set is greater than the second threshold of the data set; and the early warning module is used for outputting early warning information aiming at the input data or the sum of the input data with the exceeding magnitude value larger than the corresponding second threshold value.

The invention also provides a computing device which comprises a memory and a processor, wherein the memory stores programs, and the processor realizes the data analysis early warning method when executing the programs.

The invention also provides a computer readable storage medium, on which a program is stored, which when executed by a processor implements the above data analysis early warning method.

The invention can assist the user to quickly find out the problem of data non-compliance and improve the working efficiency.

Drawings

Fig. 1 is a flowchart of a data analysis early warning method according to an embodiment of the present invention.

Fig. 2 is a structural diagram of a data analysis early warning system according to an embodiment of the present invention.

Fig. 3 is an internal structural diagram of a computing device of an embodiment of the present invention.

Detailed Description

In the budget management system, budget analysis is a key, the function mainly analyzes and processes data according to a service application scene, and simultaneously, excess early warning is carried out on a budget application form by combining with a set budget analysis rule. The embodiment of the invention provides a data analysis early warning method, which can provide budget analysis and early warning functions based on a budget management system when being applied to budget management.

Referring to fig. 1, a data analysis early warning method according to an embodiment of the present invention includes: 1) setting a first threshold and a second threshold for a data set and for respective subsets of data belonging to the data set; 2) determining whether the input data corresponding to each data subset exceeds a first threshold of its corresponding data subset, determining whether the sum of the input data exceeds a first threshold of the data set, determining whether an excess magnitude of the input data corresponding to each data subset exceeding the first threshold of its corresponding data subset is greater than a second threshold of its corresponding data subset, and determining whether an excess magnitude of the sum of the input data exceeding the first threshold of the data set is greater than the second threshold of the data set; and 3) outputting early warning information aiming at the input data or the input data sum with the exceeding magnitude larger than the corresponding second threshold value.

In one embodiment of the present invention, the first threshold may be a predetermined value, such as a natural number. The second threshold may be a predetermined percentage. In one embodiment of the invention, the first threshold of the data set may be determined by a sum of the first thresholds of the respective data subsets. That is, the first threshold of each data subset may be directly set, and the first threshold of the data set may be obtained by summing the first thresholds of each data subset without being directly set.

In one embodiment of the invention, at least one of the first threshold and the second threshold is resettable. According to actual needs, the first threshold and the second threshold may be one of them, or both of them may be reset, so as to ensure continuous updating to cope with actual needs.

When the data analysis early warning method and the data analysis early warning system are applied to budget management, budget analysis can be rapidly carried out on the budget application form, accuracy of an analysis result is guaranteed, the budget analysis rule is automatically established, the system analyzes the budget application form submitted by a user according to the established rule, the analysis result is displayed in a chart form, meanwhile, early warning is carried out on the analysis result which does not conform to the standard, and detailed early warning information is displayed, so that the method and the system can assist an audit user in rapidly finding and positioning problems. When the data analysis early warning method and the data analysis early warning system are applied to budget management, the method specifically comprises the following steps:

establishing a budget analysis rule;

budget analysis;

and (5) carrying out excess early warning.

In the step 1 of establishing the budget analysis rule, the system can support manual setting of the budget analysis rule, and a user can set the budget analysis rule according to needs. For example, the following may be set: for the submitted budget application form, the application amount of the single budget application item is required to be not more than 20% of the set item amount in the system, the total budget amount of the budget application form is required to be not more than 15% of the total budget amount calculated by the system, wherein 20% and 15% are changeable values. The budget application form is a data set, each individual budget application item is a data subset, the amount of the project set in the system is a first threshold value of each data subset, the total budget amount calculated by the system is a first threshold value of the data set, the application amount of the individual budget application item does not exceed the percentage (20%) of the amount of the project set in the system, namely a second threshold value of each data subset, and the total budget amount of the budget application form does not exceed the percentage (15%) of the total budget amount calculated by the system, namely a second threshold value of the data set.

In the budget analysis of step 2, the system may analyze the submitted budget application form according to the budget rules set in step 1, and generate a corresponding chart for displaying the analysis result.

In the above steps, when analyzing the budget application form, the system first analyzes the individual budget application items, and then analyzes the budget total of the budget application form. For example, the existing budget application form 1 includes budget application items a, B, and C, where the number of applications is 1, the application amount is 150,100,235, and the total application amount is 485. These data are the input data for each subset of data, and the sum of the input data.

According to the budget amount of the project set in the system described in step 1, the budget amounts of the individual items of the application items a, B, and C are 146,112,190, i.e. the first threshold values of the preset data subsets a, B, and C are 146,112,190.

In the above embodiment, the system first analyzes the individual budget application items contained in the budget application form 1, where the application amounts of the items a and C both exceed the budget amount set by the system, the ratio of the exceeded portions is 2.74% and 23.68%, respectively, and the application amount of the item B is lower than the budget amount set by the system. And analyzing the total budget amount of the budget application form, wherein the total budget amount of the budget application form 1 is 146+112+190 to 448, and the total actual application amount of the budget application form is 485 to exceed 8.26% through system calculation. It can be seen that the amount of the application of item C exceeds 23.68% of the budget amount set by the system, which is greater than 20% of the budget amount set in the budget analysis rule in step 1, i.e. the amount of the excess of the data subset C is greater than the corresponding second threshold. The application amount of the item A exceeds the budget amount set by the system by 2.74 percent and is less than 20 percent set in the budget analysis rule in the step 1, namely the exceeding amount of the data subset A is less than the corresponding second threshold value. Data subset B does not exceed its corresponding first threshold, and there is no excess magnitude, so that the step of determining whether the excess magnitude is greater than the second threshold is also not required. The actual budget total of the budget application form exceeds 8.26% of the total calculated by the system and is less than 15% of the budget total, that is, the exceeding amount of the data set is less than the corresponding second threshold.

It should be noted that, when the budget application form is analyzed in the step 2, the method includes, but is not limited to, comparing and analyzing the application quota with the quota set by the system, and may also compare and analyze the budget quota with the historical project budget quota, and generate a quota analysis statistical chart, etc.

In the excess early warning in step 3, after the system analyzes the submitted budget request form in step 2, for the excess budget form, the system can perform excess early warning in a bullet frame mode and list detailed excess information, including: the name of the excess application item, the number of the application items, the application amount, the amount set by the system, the excess percentage and the like. Therefore, when the audit personnel open the budget application form 1 for auditing, the problem of data non-compliance can be quickly found out. Taking the budget application form 1 in step 2 as an example, the application amount of the item C exceeds 23.68% of the budget amount set by the system, and is greater than 20% set in the budget analysis rule in step 1, so that the warning information needs to be output. The application amount of the item B does not exceed the budget amount set by the system. The application amount of the item A exceeds the budget amount set by the system by 2.74 percent and is less than 20 percent of the budget analysis rule set in the step 1. The actual budget total of the budget application form exceeds 8.26% of the total calculated by the system and is less than 15% of the budget total. Therefore, the items B, A and the budget total do not need to output early warning information.

The data analysis early warning method and the data analysis early warning system support the autonomous establishment of the budget analysis rule, have high system application flexibility, and can help a user to quickly perform budget analysis according to the established budget analysis rule, thereby realizing the timeliness of the budget analysis. The method and the system support early warning on analysis results which are not in compliance, can assist auditing users to quickly find problems, and improve working efficiency.

Referring to fig. 2, the data analysis early warning system of the embodiment of the present invention includes: a threshold setting module for setting a first threshold and a second threshold for a data set and for respective subsets of data belonging to the data set; a data analysis module for determining whether the input data corresponding to each data subset exceeds a first threshold of its corresponding data subset, determining whether the sum of the input data exceeds a first threshold of the data set, determining whether an excess magnitude of the input data corresponding to each data subset exceeding the first threshold of its corresponding data subset is greater than a second threshold of its corresponding data subset, and determining whether an excess magnitude of the sum of the input data exceeding the first threshold of the data set is greater than the second threshold of the data set; and the early warning module is used for outputting early warning information aiming at the input data or the sum of the input data with the exceeding magnitude value larger than the corresponding second threshold value.

The data analysis early warning method can be implemented in computing equipment. An exemplary internal block diagram of a computing device may be shown in fig. 3, which may include a processor, memory, an external interface, a display, and an input device connected by a system bus. Wherein the processor is configured to provide computational and control capabilities. The memory includes a nonvolatile storage medium, an internal memory. The nonvolatile storage medium stores an operating system, an application program, a database, and the like. The internal memory provides an environment for the operation of the operating system and programs in the nonvolatile storage medium. The external interface includes, for example, a network interface for communicating with an external terminal through a network connection. The external interface may also include a USB interface, etc. The display of the computing device may be a liquid crystal display or an electronic ink display, and the input device may be a touch layer covered on the display, or may be, for example, a key, a trackball, or a touch pad arranged on a casing of the computing device, or may be an external keyboard, a touch pad, or a mouse.

A program stored in a non-volatile storage medium in a computing device may implement the above-described data analysis early warning method when executed by a processor. In addition, the non-volatile storage medium may also exist in a separate physical form, such as a usb disk, and when the usb disk is connected to a processor, the program stored in the usb disk is executed to implement the data analysis and early warning method. The method of the invention can also be realized as an APP (application program) in apple or android application markets, and the APP is downloaded to respective mobile terminals by users for operation.

Those skilled in the art will appreciate that the architecture shown in fig. 3 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

As described above, it can be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments can be implemented by the related hardware instructed by the computer program, which can be stored in a non-volatile computer readable storage medium, and when executed, the computer program can include the processes of the above embodiments of the methods. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The computer according to the present invention is a computing device capable of automatically performing numerical calculation and/or information processing according to instructions set or stored in advance, and the hardware thereof may include at least one memory, at least one processor, and at least one communication bus. Wherein the communication bus is used for realizing connection communication among the elements. The processor may include, but is not limited to, a microprocessor. The computer hardware may also include Application Specific Integrated Circuits (ASICs), Programmable Gate arrays (FPGAs), Digital Signal Processors (DSPs), embedded devices, etc. The computer may also include a network device and/or a user device. Wherein the network device includes, but is not limited to, a single network server, a server group consisting of a plurality of network servers, or a Cloud Computing (Cloud Computing) based Cloud consisting of a large number of hosts or network servers, wherein Cloud Computing is one of distributed Computing, a super virtual computer consisting of a collection of loosely coupled computers.

The computing device may be, but is not limited to, any terminal such as a personal computer, a server, etc. capable of human-computer interaction with a user through a keyboard, a touch pad, a voice control device, etc. The computing device herein may also include a mobile terminal, which may be, but is not limited to, any electronic device capable of human-computer interaction with a user through a keyboard, a touch pad, or a voice control device, for example, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), a smart wearable device, and other terminals. The Network in which the computing device is located includes, but is not limited to, the internet, a wide area Network, a metropolitan area Network, a local area Network, a Virtual Private Network (VPN), and the like.

The memory is for storing program code. The Memory may be a circuit without a physical form and having a Memory function In an integrated circuit, such as a RAM (Random-Access Memory), a fifo (First In First out), and the like. Alternatively, the memory may be a memory in a physical form, such as a memory bank, a TF Card (Trans-flash Card), a smart media Card (smart media Card), a secure digital Card (secure digital Card), a flash memory Card (flash Card), and so on.

The processor may include one or more microprocessors, digital processors. The processor may call program code stored in the memory to perform the associated functions. For example, the various modules illustrated in fig. 3 are program code stored in the memory and executed by the processor to implement the above-described methods. The processor is also called a Central Processing Unit (CPU), and may be an ultra-large scale integrated circuit, which is an operation Core (Core) and a Control Core (Control Unit).

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or elements may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the claims. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A data analysis early warning method is characterized by comprising the following steps:

setting a first threshold and a second threshold for a data set and for respective subsets of data belonging to the data set;

determining whether the input data corresponding to each data subset exceeds a first threshold of its corresponding data subset, determining whether the sum of the input data exceeds a first threshold of the data set, determining whether an excess magnitude of the input data corresponding to each data subset exceeding the first threshold of its corresponding data subset is greater than a second threshold of its corresponding data subset, and determining whether an excess magnitude of the sum of the input data exceeding the first threshold of the data set is greater than the second threshold of the data set; and

and outputting early warning information aiming at the input data or the input data sum exceeding the magnitude value larger than the corresponding second threshold value.

2. The data analysis pre-warning method of claim 1, wherein the first threshold is a predetermined value and the second threshold is a predetermined percentage.

3. The data analysis forewarning method of claim 2, wherein the first threshold of the data set is determined by a sum of the first thresholds of the respective data subsets.

4. The data analysis forewarning method of claim 1, wherein at least one of the first threshold and the second threshold is resettable.

5. The data analysis pre-warning method of claim 1, wherein outputting pre-warning information comprises displaying on a screen of an electronic device in a pop-up box.

6. The data analysis pre-warning method as claimed in claim 1, comprising displaying the data analysis results on a screen of the electronic device in the form of an analysis chart.

7. The data analysis and early warning method as claimed in any one of claims 1 to 6, wherein the data set is a budget application form, and the data subset is each individual budget application item in the budget application form.

8. A data analysis early warning system, comprising:

a threshold setting module for setting a first threshold and a second threshold for a data set and for respective subsets of data belonging to the data set;

a data analysis module for determining whether the input data corresponding to each data subset exceeds a first threshold of its corresponding data subset, determining whether the sum of the input data exceeds a first threshold of the data set, determining whether an excess magnitude of the input data corresponding to each data subset exceeding the first threshold of its corresponding data subset is greater than a second threshold of its corresponding data subset, and determining whether an excess magnitude of the sum of the input data exceeding the first threshold of the data set is greater than the second threshold of the data set; and

and the early warning module is used for outputting early warning information aiming at the input data or the sum of the input data with the exceeding magnitude value larger than the corresponding second threshold value.

9. A computing device comprising a memory and a processor, the memory storing a program, wherein the processor implements the method of any of claims 1-7 when executing the program.

10. A computer-readable storage medium, on which a program is stored, which, when being executed by a processor, carries out the method of any one of claims 1 to 7.