CN111724063A

CN111724063A - Business data processing method and device, electronic equipment and storage medium

Info

Publication number: CN111724063A
Application number: CN202010567265.5A
Authority: CN
Inventors: 陈玉婷; 徐静娴; 艾春伶; 李咪娜; 冯婷婷
Original assignee: Shanghai Sensetime Intelligent Technology Co Ltd
Current assignee: Shanghai Sensetime Intelligent Technology Co Ltd
Priority date: 2020-06-19
Filing date: 2020-06-19
Publication date: 2020-09-29

Abstract

The present disclosure relates to a method and an apparatus for processing service data, an electronic device and a storage medium, wherein the method comprises: monitoring service data in a project operation system; under the condition that the service data are monitored, determining a label of the service data by executing a dynamic byte code preset with a classification module, wherein the label of the service data is a label corresponding to a classification result obtained by classifying the service data by the classification module; and according to the label of the service data, carrying out operation analysis on the service data to obtain an operation analysis result. The embodiment of the disclosure can improve the timeliness of operation analysis on new projects and avoid analysis on dirty data.

Description

Business data processing method and device, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for processing service data, an electronic device, and a storage medium.

Background

In profitable or non-profitable organizations such as enterprises, public institutions, public welfare organizations and the like, good and effective organization and management and benefit index tracking are important influence factors for organization development. Therefore, analyzing business data of projects operated by the organization to track project operation states can help the organization to optimize project operation in time.

In an organization project operation system, since an organization often operates a plurality of projects and a business direction is continuously adjusted, project data of a new project is generated in the project operation system, and how to analyze the project data of the new project in time is an urgent problem to be solved.

Disclosure of Invention

The present disclosure provides a technical solution for processing service data.

According to an aspect of the present disclosure, a method for processing service data is provided, including:

monitoring service data in a project operation system;

under the condition that the service data are monitored, determining a label of the service data by executing a dynamic byte code preset with a classification module, wherein the label of the service data is a label corresponding to a classification result obtained by classifying the service data by the classification module;

and according to the label of the service data, carrying out operation analysis on the service data to obtain an operation analysis result.

In a possible implementation manner, the tag includes a parameter tag, where the parameter tag is used to indicate that the service data includes a parameter value of a parameter corresponding to the parameter tag, and the parameter includes a parameter for analyzing the operation capability of the project operation system;

the operation analysis of the service data according to the label of the service data to obtain an operation analysis result includes:

acquiring parameter values in the service data according to parameters indicated by the parameter labels of the service data;

and analyzing the operation capacity of the project operation system by using the acquired parameter values to obtain an operation analysis result.

In a possible implementation manner, the tag includes an item tag indicating an item to which the service data belongs, and the performing operation analysis on the service data according to the tag of the service data to obtain an operation analysis result includes:

and analyzing the operation capacity of the project by taking the project as an analysis dimension according to the project indicated by the project label of the service data to obtain an operation analysis result.

In a possible implementation manner, the tag includes an organization tag indicating an organization to which the service data belongs, and the performing operation analysis on the service data according to the tag of the service data to obtain an operation analysis result includes:

and according to the organization indicated by the organization label of the business data, taking the organization as an analysis dimension, and carrying out organization operation capacity analysis on the organization to obtain an operation analysis result.

In a possible implementation manner, the analyzing, by using the obtained parameter value, the operation capability of the project operation system to obtain an operation analysis result includes:

according to the parameter values, determining index values of the financial indexes of the target analysis dimensionality;

and determining the operation capacity of the target analysis dimension according to the index value.

In one possible implementation, the method further includes:

and pushing the operation analysis result to the target equipment.

In a possible implementation manner, performing operation analysis on the service data according to the label of the service data to obtain an operation analysis result includes:

and carrying out operation analysis on the service data according to the label of the service data through a distributed streaming computing framework to obtain an operation analysis result.

According to an aspect of the present disclosure, there is provided a service data processing apparatus, including:

the monitoring module is used for monitoring the service data in the project operation system;

the determining module is used for determining a label of the service data by executing a dynamic byte code preset with a classifying module under the condition that the service data is monitored, wherein the label of the service data is a label corresponding to a classifying result obtained by classifying the service data by the classifying module;

and the analysis module is used for carrying out operation analysis on the service data according to the label of the service data to obtain an operation analysis result.

the analysis module is used for acquiring parameter values in the service data according to the parameters indicated by the parameter labels of the service data; and analyzing the operation capacity of the project operation system by using the acquired parameter values to obtain an operation analysis result.

In a possible implementation manner, the tag includes an item tag indicating an item to which the service data belongs, and the analysis module is configured to analyze the operation capability of the item by using the item as an analysis dimension according to the item indicated by the item tag of the service data, so as to obtain an operation analysis result.

In a possible implementation manner, the tag includes an organization tag indicating an organization to which the business data belongs, and the analysis module is configured to perform, according to the organization indicated by the organization tag of the business data, an analysis on an organization operation capability of the organization with the organization as an analysis dimension, to obtain an operation analysis result.

In a possible implementation manner, the analysis module is configured to determine an index value of the financial index of the target analysis dimension according to the parameter value; and determining the operation capacity of the target analysis dimension according to the index value.

In one possible implementation, the apparatus further includes: and the pushing module is used for pushing the operation analysis result to the target equipment.

In a possible implementation manner, the analysis module is configured to perform operation analysis on the service data according to the label of the service data through a distributed streaming computation framework, so as to obtain an operation analysis result.

According to an aspect of the present disclosure, there is provided an electronic device including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.

According to an aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the above-described method.

In the embodiment of the disclosure, by monitoring the service data in the project operation system, the service data can be processed in time when the service data is generated, in the process of processing the service data, the preset classification module can be updated in time and flexibly according to the service data of a new project when the new project is generated through the dynamic bytecode, the label of the service data is determined by executing the dynamic bytecode preset with the classification module, the service data is given with the label, the service data can be operated and analyzed in a classified manner, even if the service data generated by the new project is analyzed in time according to the label of the service data, and the timeliness of operating and analyzing the new project is improved.

In addition, the service data is analyzed according to the label of the service data, so that the dirty data can be prevented from being analyzed, and the operation and analysis efficiency is improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure.

Fig. 1 shows a flow chart of a business data processing method according to an embodiment of the present disclosure;

FIG. 2 is a system architecture diagram illustrating a business data processing method according to an embodiment of the present disclosure;

FIG. 3 shows a block diagram of a business data processing apparatus according to an embodiment of the present disclosure;

FIG. 4 shows a block diagram of an electronic device in accordance with an embodiment of the disclosure;

fig. 5 shows a block diagram of an electronic device in accordance with an embodiment of the disclosure.

Detailed Description

Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.

Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.

Fig. 1 is a flowchart illustrating a service data processing method according to an embodiment of the present disclosure, and as shown in fig. 1, the service data processing method includes:

and step S11, monitoring the service data in the project operation system.

The project operation system may be any system for operating a project of an organization, for example, a profit structure such as an enterprise, or a non-profit organization such as a public institution or a public welfare organization, and may be, for example, a sales system, a game operation system, or the like, or may include a financial system, a personnel system, or the like inside the organization. In the present disclosure, a specific project system is not limited, and in practical applications, a project operation system may be determined according to a project to be subjected to operation analysis.

The business data may be any data generated in the project operation system, such as order data, staff labor hour data, and the like;

in the process of monitoring the project operation system, if the project operation system is an aspect Programming (AOP) oriented system, the aspect logic for monitoring may be added to the service modules to be monitored, so as to monitor the service data of the service modules.

Step S12, determining the label of the service data by executing the dynamic bytecode preset with the classification module when the service data is monitored.

The label of the service data is a label corresponding to a classification result obtained by classifying the service data by the classification module. The classification result and the label have a corresponding relationship, which may be preset, or the label corresponding to the classification result may be the classification result itself, that is, the classification result may be directly used as the label of the service data.

The dynamic bytecode is a dynamically generated bytecode, the Java code can be executed in a Java virtual machine after being compiled into the bytecode, and the bytecode may specifically exist in the form of a binary file and may be generated by a Java compiler. The modification of the dynamic byte codes can be realized by dynamically modifying the classes and methods in the dynamic byte codes.

In the disclosure, a classification module is preset in the dynamic bytecode, and the classification module can classify the service data to determine the label of the service data.

The category specifically classified by the classification module may be determined according to an analysis dimension of the data in the operation analysis process, where the analysis dimension may be an object or an angle targeted by the analysis, and the dimension may be, for example, a dimension of an item (i.e., an item is used as an object for analysis), a dimension of an organization architecture (e.g., a department in an organization structure is used as an object for analysis), and then the label may be "a item", "B item", "X department", or the like.

In addition, the dimension may also be a dimension of a parameter used in a specific operation analysis process, for example, in a process of calculating a profit situation, parameters such as cost, revenue, and the like are used, and the dimension of the analysis may be cost (i.e., analysis is performed with cost as an object) or revenue (i.e., analysis is performed with revenue as an object), and then the label may be a "cost" label or a "revenue" label. The service data processing method of the present disclosure will be discussed in detail later with reference to different classification dimensions, and will not be described herein.

The classification module may classify the service data according to a set category, and the classification module may be a classification network obtained through machine learning training, or may be a classification expression with a built-in regular expression (also referred to as a regular expression). The present disclosure is not limited to a specific implementation of the classification module.

And step S13, performing operation analysis on the service data according to the label of the service data to obtain an operation analysis result.

After the label of the service data is obtained, the service data can be operated and analyzed in different categories according to the label of the service data. The operation analysis process will be described in detail later in conjunction with possible implementations of the present disclosure.

According to the embodiment of the disclosure, by monitoring the service data in the project operation system, the service data can be processed in time when the generation of the service data is monitored, in the process of processing the service data, the preset classification module can be updated in time and flexibly according to the service data of a new project when the new project exists through the dynamic byte codes, the label of the service data is determined by executing the dynamic byte codes preset with the classification module, the service data is endowed with the label, the service data can be operated and analyzed in different categories, even if the service data generated by the new project is analyzed in time according to the label of the service data, and the timeliness of the operation and analysis of the new project is improved.

In addition, the dynamic byte codes preset with the classification modules are executed to determine the labels of the service data, so that the dirty data which is not in a given range, has no meaning to operation analysis or has illegal format is screened and eliminated, the service data is analyzed according to the labels of the service data, the dirty data can be prevented from being analyzed, and the efficiency of operation analysis is improved.

In addition, the business data processing method does not need to make requirements on the format of the business data in the project operation system, when a new project is generated, the operation analysis of the new project can be realized by updating the classification module in the dynamic byte code, the project operation system can be analyzed without customizing the data format of the business data by the project operation system, and the applicability is strong.

The implementation manner of the service data processing method provided by the present disclosure may be various, and in one possible implementation manner, the classification module may be a classification expression, and the determining the label of the service data includes: matching data in the service data through rules in the classification expressions; and determining the label of the service data according to the rule met by the matched data. For example, the classification expression may have a regular expression built therein, and the data may be matched by the preset regular expression, and the label of the data may be determined according to the matching result.

Because the classification expression is preset in the dynamic byte code which can be dynamically updated, the rules in the classification expression can be dynamically updated according to the change condition of the items in the item operation system, and when the items in the item operation system are updated, the rules for classifying the service data of the new items can be dynamically written into the dynamic byte code. Under the condition that a new project exists in the project operation system, the classification expression can be flexibly and dynamically updated, and the timely analysis of the new project service data is realized.

In a possible implementation manner, the tag includes a parameter tag, where the parameter tag is used to indicate that the service data includes a parameter value of a parameter corresponding to the parameter tag, and the parameter includes a parameter for analyzing the operation capability of the project operation system; the operation analysis of the service data according to the label of the service data to obtain an operation analysis result includes: acquiring parameter values in the service data according to the parameters indicated by the parameter labels of the service data; and analyzing the operation capacity of the project operation system by using the acquired parameter values to obtain an operation analysis result.

The operation capacity of the project operation system can be determined by calculating an index reflecting the operation capacity, and the index can be calculated by a parameter value in the service data. For example, the operation capacity of the project operation system can be measured by specific financial indexes, which can include profitability index of the project, labor efficiency of workers, and the like, and the financial indexes can be calculated by parameter values of parameters such as cost, income, and the like.

In the operation capability analysis process, there are various parameters used for calculating the index, and in the case of the profitability index, the parameters used include "cost parameters" (such as sales expenditure, production expenditure, etc.) and "income parameters" (such as sales amount, etc.). The parameter tag of the service data can be determined by executing a dynamic bytecode preset with a classification module. The parameter label of the service data indicates that the service data contains the parameter value of the parameter corresponding to the parameter label, so that the parameter value in the service data can be acquired after the parameter label of the service data is determined, and the operation capability of the project operation system is analyzed by using the acquired parameter value.

For example, taking a certain piece of business data as sales order data as an example, after the generation of the piece of business data is monitored, the parameter tag of the piece of data can be determined to be an "income" tag through a preset classification model, the "income" tag indicates that the piece of data contains a parameter value of an "income parameter", then, the sales amount in the piece of business data can be acquired as the parameter value of the "income parameter" to calculate the profitability index, and further, the profitability of the project operation system is analyzed.

According to the embodiment of the disclosure, the parameter tag of the business data can be determined, the parameter value in the business data is obtained according to the parameter tag, the operation capacity of the project operation system is analyzed, the parameter value required by the operation capacity analysis can be rapidly and accurately determined from the business data, and the operation capacity analysis can be timely and effectively realized no matter whether a new project or an old project in the project operation system is used.

In a possible implementation manner, analyzing the operation capability of the project operation system by using the obtained parameter value to obtain an operation analysis result includes: according to the parameter values, determining index values of the financial indexes of the target analysis dimensionality; and determining the operation capacity of the target analysis dimension according to the index value.

The financial index may include an index of the enterprise evaluating the financial status and the operation result, such as a profitability index (including, for example, a basic fund profit margin, a sales profit margin, and the like), a repayment capacity index (including, for example, an asset liability margin, a liquidity ratio, and the like), and the financial index may be calculated by a formula, and a specific parameter value is assigned to the formula, so that the calculation of the financial index may be performed. The specific formula can be determined according to actual conditions in specific implementation, and the disclosure does not limit the specific formula.

After the indicator value is determined, the operation capability may be evaluated based on a comparison of the indicator value and an indicator threshold. For example, for the profitability index, if the calculated index value is less than or equal to 0, the operation analysis result is that the system does not have the profitability; and if the index value is greater than or equal to the expected index threshold value, the operation analysis result indicates that the profitability of the system exceeds or reaches the expected value.

The operational capabilities of the project operations system may be analyzed through a number of dimensions, such as project dimensions, organizational architecture dimensions, and so forth. The target analysis dimension may be one or more of a plurality of dimensions.

In a possible implementation manner, the tag includes an item tag indicating an item to which the service data belongs, and the performing operation analysis on the service data according to the tag of the service data to obtain an operation analysis result includes: and analyzing the operation capacity of the project by taking the project as an analysis dimension according to the project indicated by the project label of the service data to obtain an operation analysis result.

In a possible implementation manner, the tag includes an organization tag indicating an organization to which the service data belongs, and the performing operation analysis on the service data according to the tag of the service data to obtain an operation analysis result includes: and according to the organization indicated by the organization label of the business data, taking the organization as an analysis dimension, and carrying out organization operation capacity analysis on the organization to obtain an operation analysis result.

In performing the operation capability analysis, the operation capability in different time periods, such as the operation capability in the last 1 day and the operation capability in the last 1 month, can be calculated.

According to the embodiment of the disclosure, the index value of the financial index of the target analysis dimension can be determined through the determined parameter value, the operation capacity of the project operation system is analyzed in detail through different dimensions, and the refinement degree of the capacity analysis of the project operation system is improved.

In one possible implementation, the method further includes: and pushing the operation analysis result to the target equipment.

The operational analysis results may include at least one of: loss, profit, loss (or profit) above or below expectations, loss (or profit) trends, invested costs above or below planned invested costs, and the like.

The target device can be a personal computer, a handheld terminal and the like of an enterprise, and the target device can display the operation analysis result through a display screen.

In the pushing process, the dynamic display can be pushed to the front end of the website through the websocket communication protocol for dynamic display.

In one possible implementation, the method further includes: and pushing project operation suggestions to the user according to the operation analysis result.

For example, the project invested cost can be calculated and compared with the project plan invested cost to alert the user to control the project cost when the invested cost exceeds the project plan invested cost.

In a possible implementation manner, performing operation analysis on the service data according to the label of the service data includes: and carrying out operation analysis on the service data according to the label of the service data through a distributed streaming computing framework to obtain an operation analysis result.

The distributed streaming computing framework can perform streaming computing and analysis, and the streaming computing is computed and analyzed in real time according to the monitored business data. The distributed streaming computing framework can be a Strom framework, for example, business data can be submitted to the topology of Strom after being labeled, and the business data is subjected to operation analysis by Storm.

According to the embodiment of the disclosure, based on real-time calculation and analysis of big data, the operation capacity of the project operation system can be reflected in real time, the loss or profit trend of the project operation system is reflected, the operation condition of the system is clearly displayed, and an analyst can conveniently and timely position business problems.

Referring to fig. 2, a system architecture diagram of a possible implementation manner provided by the present disclosure is shown, fig. 2 mainly illustrates a system architecture diagram of a business data processing method provided by the present disclosure, and for parts not clarified in fig. 2, refer to the related description above.

In this implementation, the project operation system 201 generates business data, and some of the generated business data may include data used in the operation analysis process, such as data of project income, personnel investment, and the like. Therefore, the classification module 202 is used for labeling the business data generated by the project operation system, so that the classification and the filtration of the business data can be realized.

The tagged data is transmitted to the Storm real-time computing system 204 in real time through the Kafka distributed message system 203, and the Storm real-time computing system 204 calculates indexes reflecting the system operation capacity from multiple dimensions by using the tagged data, so as to analyze the operation capacity of the project operation system 201.

The analysis result may be transmitted to the display terminal 205 in real time, and the display terminal 205 may display the analysis result in real time. In addition, the Storm real-time computing system 204 can store the computed results and related data used by the computing process in the memory 206, and the memory 206 can be, for example, a Redis database.

In a possible implementation manner, the service data processing method may be executed by an electronic device such as a terminal device or a server, where the terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, an in-vehicle device, a wearable device, or the like, and the method may be implemented by a processor calling a computer readable instruction stored in a memory. Alternatively, the method may be performed by a server.

It is understood that the above-mentioned method embodiments of the present disclosure can be combined with each other to form a combined embodiment without departing from the logic of the principle, which is limited by the space, and the detailed description of the present disclosure is omitted. Those skilled in the art will appreciate that in the above methods of the specific embodiments, the specific order of execution of the steps should be determined by their function and possibly their inherent logic.

In addition, the present disclosure also provides a service data processing apparatus, an electronic device, a computer-readable storage medium, and a program, which can be used to implement any service data processing method provided by the present disclosure, and the corresponding technical solutions and descriptions and corresponding descriptions in the methods section are not repeated.

Fig. 3 shows a block diagram of a service data processing apparatus according to an embodiment of the present disclosure, and as shown in fig. 3, the service data processing apparatus 30 includes:

a monitoring module 301, configured to monitor service data in a project operation system;

a determining module 302, configured to determine, by executing a dynamic bytecode preset with a classification module, a tag of the service data when the service data is monitored, where the tag of the service data is a tag corresponding to a classification result obtained by classifying the service data by the classification module;

and the analysis module 303 is configured to perform operation analysis on the service data according to the label of the service data to obtain an operation analysis result.

the analysis module 303 is configured to obtain a parameter value in the service data according to a parameter indicated by a parameter tag of the service data; and analyzing the operation capacity of the project operation system by using the acquired parameter values to obtain an operation analysis result.

In a possible implementation manner, the tags include item tags indicating items to which the service data belong, and the analysis module 303 is configured to analyze the operation capability of the item by using the item as an analysis dimension according to the item indicated by the item tags of the service data, so as to obtain an operation analysis result.

In a possible implementation manner, the tag includes an organization tag indicating an organization to which the business data belongs, and the analysis module 303 is configured to perform, according to the organization indicated by the organization tag of the business data, an analysis on an organization operation capability of the organization with the organization as an analysis dimension, to obtain an operation analysis result.

In a possible implementation manner, the analysis module 303 is configured to determine an index value of the financial index of the target analysis dimension according to the parameter value; and determining the operation capacity of the target analysis dimension according to the index value.

In a possible implementation manner, the analysis module 303 is configured to perform operation analysis on the service data according to the label of the service data through a distributed streaming computation framework, so as to obtain an operation analysis result.

In some embodiments, functions of or modules included in the apparatus provided in the embodiments of the present disclosure may be used to execute the method described in the above method embodiments, and specific implementation thereof may refer to the description of the above method embodiments, and for brevity, will not be described again here.

Embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the above-mentioned method. The computer readable storage medium may be a non-volatile computer readable storage medium.

An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.

The embodiment of the present disclosure further provides a computer program product, which includes a computer readable code, and when the computer readable code runs on a device, a processor in the device executes instructions for implementing the service data processing method provided in any of the above embodiments.

The embodiments of the present disclosure also provide another computer program product for storing computer readable instructions, which when executed cause a computer to perform the operations of the service data processing method provided in any of the above embodiments.

The electronic device may be provided as a terminal, server, or other form of device.

Fig. 4 illustrates a block diagram of an electronic device 800 in accordance with an embodiment of the disclosure. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like terminal.

Referring to fig. 4, electronic device 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.

The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 800 is in an operation mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 may detect an open/closed state of the electronic device 800, the relative positioning of components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.

In an exemplary embodiment, a non-transitory computer-readable storage medium, such as the memory 804, is also provided that includes computer program instructions executable by the processor 820 of the electronic device 800 to perform the above-described methods.

Fig. 5 illustrates a block diagram of an electronic device 1900 in accordance with an embodiment of the disclosure. For example, the electronic device 1900 may be provided as a server. Referring to fig. 5, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.

The electronic device 1900 may also include a power component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output (I/O) interface 1958. The electronic device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, or the like.

In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions executable by the processing component 1922 of the electronic device 1900 to perform the above-described methods.

The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.

The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.

The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.

The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).

Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The computer program product may be embodied in hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied in a computer storage medium, and in another alternative embodiment, the computer program product is embodied in a Software product, such as a Software Development Kit (SDK), or the like.

Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for processing service data is characterized by comprising the following steps:

monitoring service data in a project operation system;

2. The method of claim 1, wherein the tag comprises a parameter tag, the parameter tag is used to indicate a parameter value of the service data that includes a parameter corresponding to the parameter tag, and the parameter comprises a parameter for analyzing an operation capability of the project operation system;

3. The method of claim 1, wherein the tag includes an item tag indicating an item to which the service data belongs, and performing operation analysis on the service data according to the tag of the service data to obtain an operation analysis result includes:

4. The method of claim 1, wherein the tag includes an organization tag indicating an organization to which the service data belongs, and wherein performing the operation analysis on the service data according to the tag of the service data to obtain an operation analysis result includes:

5. The method of claim 2, wherein the analyzing the operation capability of the project operation system by using the obtained parameter value to obtain an operation analysis result comprises:

6. The method according to any one of claims 1-5, further comprising:

and pushing the operation analysis result to the target equipment.

7. The method according to any one of claims 1 to 6, wherein performing operation analysis on the service data according to the label of the service data to obtain an operation analysis result comprises:

8. A service data processing apparatus, comprising:

9. An electronic device, comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to invoke the memory-stored instructions to perform the method of any of claims 1 to 7.

10. A computer readable storage medium having computer program instructions stored thereon, which when executed by a processor implement the method of any one of claims 1 to 7.