Data management system and data management method based on data driving

Abstract

The invention provides a data management system and a data management method based on data driving. The data management system based on data driving comprises a storage device and a processor. The storage device is used for storing a plurality of process models. The processor is coupled to the storage device and is used for receiving the setting data set. The processor performs a second compilation on the plurality of component data sets to combine the plurality of component data sets into the plurality of process data sets. According to the data management system and the data management method based on data driving, secondary compiling can be automatically carried out on the set data set according to the multiple process models, and then the component data corresponding to the set data set is combined into the multiple process data sets.

Description

Technical Field

[0001] The present invention relates to a packaging data processing technology, in particular to a data management system and a data management method based on data drive. Background Art

[0002] In traditional task processes, people make judgments on tasks at each stage and perform corresponding operations and adjustments based on personal experience. In this way, each execution step requires people to perform data management and task process management based on past experience. Therefore, traditional task processes and data processing are highly dependent on human experience and require people to make judgments item by item, which leads to the problem of not achieving a good experience reuse effect. Summary of the invention

[0003] The present invention is directed to a data management system and a data management method based on data drive, which can automatically generate corresponding component data groups according to set data groups, and then combine the component data groups into multiple process data groups.

[0004] According to an embodiment of the present invention, the data management system based on data drive of the present invention includes a storage device and a processor. The storage device is used to store a process model. The processor is coupled to the storage device and is used to receive a set data group. The processor performs a first compilation on the set data group to generate a plurality of component data groups. The processor performs a second compilation on the plurality of component data groups to combine the plurality of component data groups into a plurality of process data groups.

[0005] According to an embodiment of the present invention, the data management method of the present invention includes the following steps: receiving a setting data group through a processor; performing a first compilation on the setting data group through the processor to generate multiple component data groups; and performing a second compilation on the multiple component data groups through the processor to combine the multiple component data groups into multiple process data groups.

[0006] Based on the above, the data management system and data management method based on data drive of the present invention can automatically generate component data sets related to the task process according to the setting data sets input by the user, and can match them to the corresponding process data sets.

[0007] In order to make the above features and advantages of the present invention more clearly understood, embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a circuit diagram of a data management system based on data drive according to an embodiment of the present invention;

[0009] Figure 2 is a flow chart of a data management method according to an embodiment of the present invention;

[0010] Figure 3 is a schematic diagram of a data management system according to an embodiment of the present invention;

[0011] Figure 4 is a schematic diagram of a first compilation and a second compilation of an embodiment of the present invention;

[0012] Figure 5 is a schematic diagram of a data management system according to an exemplary embodiment of the present invention.

[0013] Description of Reference Numerals

[0014] 100: Data management system;

[0015] 101: Set data group;

[0016] 102: process data group;

[0017] 110: processor;

[0018] 120: storage device;

[0019] 301: data;

[0020] 302: process model;

[0021] 303: component data group;

[0022] 304: process data;

[0023] 310: Control model;

[0024] 311: timing parameters;

[0025] 312: Standard setting parameters;

[0026] 313: measure parameters;

[0027] 320: Restriction Model;

[0028] 321: target parameters;

[0029] 322: conditional parameters;

[0030] 323: behavioral parameters;

[0031] 330: Assignment model;

[0032] 331: working parameters;

[0033] 332: rule parameters;

[0034] 340: driver model;

[0035] 341: Timing parameters;

[0036] 342: Working parameters;

[0037] 350: Decision model;

[0038] 351: timing parameters;

[0039] 352: According to parameters;

[0040] 360: target component;

[0041] 361: Mission components;

[0042] 362: Project components;

[0043] 363: API components;

[0044] 370: Active component;

[0045] 371: Activity data component;

[0046] 372: ESP components;

[0047] 373: Task data component;

[0048] 374: Filter component;

[0049] 375: computing components;

[0050] 376: operator component;

[0051] 380: Verification component;

[0052] 381: expression component;

[0053] 382: Js components;

[0054] 383: Circulation components;

[0055] 384: Exclusive components;

[0056] 390: Behavioral components;

[0057] 391:IM components;

[0058] 392: email component;

[0059] 393: Restrict form components;

[0060] 394: data update component;

[0061] 410: Process model;

[0062] 411: Control ability;

[0063] 412: Restricted Capacity;

[0064] 413: Decision-making ability;

[0065] 414: Assignment capability;

[0066] 415: driving ability;

[0067] 420: parameters;

[0068] 421: Timing parameters;

[0069] 422: Task execution;

[0070] 423: timing parameters;

[0071] 424: Standard setting parameters;

[0072] 425: rule parameters;

[0073] 426: Action parameters;

[0074] 431: target component;

[0075] 432: Active component;

[0076] 433: Verification component;

[0077] 434: Behavioral component;

[0078] 440: process path;

[0079] 450: process data group;

[0080] 455: process path;

[0081] 501: client device;

[0082] 502: Server;

[0083] 503: Load balancer;

[0084] 504: Data Management Center;

[0085] 505: Authentication Center;

[0086] 506: application server;

[0087] 507: Registration center;

[0088] 508: Configuration center;

[0089] 509: service tracking;

[0090] 510: Data management system;

[0091] 511: service monitoring;

[0092] 512: cache data storage area;

[0093] 513: persistent data storage area;

[0094] 514: message queue area;

[0095] 515: Knowledge Graph;

[0096] 516: Log storage area;

[0097] S210~S230: steps. DETAILED DESCRIPTION

[0098] Reference will now be made in detail to exemplary embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Whenever possible, the same reference numerals are used in the drawings and the description to refer to the same or like parts.

[0099] First of all, it is explained that the data management system and data management method based on data drive of the present invention can simplify the difficulty and complexity of the design of business processing flow, and improve reusability. The process data group described in each embodiment of the present invention can be, for example, from query instructions to the setting of material information in manufacturing, billing process in finance or leave process, etc. These process settings and processing logics can be abstractly defined as process data groups, and include processing logic, processing data type, data state, characteristics and other contents. In addition, there will be a corresponding series of processing logics for different types of raw data in different states, so the present invention can encapsulate these process data groups into tasks. When encapsulating process data, it is only necessary to select the process type involved (such as driving ability, restriction ability, assignment ability, decision-making ability and control ability) and input basic settings (such as trigger conditions, time parameters, timing settings, corresponding actions, information content, authorized personnel, etc.), and the data management system based on data drive of the present invention can automatically encapsulate it into a suitable processing logic (i.e., task logic) and combine it with the original processing logic (i.e., process data group). In this way, the convenience of encapsulating business processing flow can be greatly simplified and reusability can be improved. In addition, at runtime, appropriate task logic can be dynamically activated according to data changes for processing (ie, data-driven).

[0100] Figure 1 FIG. 1 is a circuit diagram of a data management system based on data drive according to an embodiment of the present invention. Figure 1, the data management system 100 based on data drive includes a processor 110 and a storage device 120. The processor 110 is coupled to the storage device 120. The data management system 100 based on data drive may also include an input device with actual circuit elements, a user interface, a communication interface or a data transmission interface, so that the processor 110 can receive instructions or signals of a process establishment request, a process editing request or a process encapsulation request from a data source or an external device or according to a user operation. In this embodiment, the data management system 100 based on data drive may be, for example, a personal computer, a workstation computer or other electronic device with data computing capabilities. In one embodiment, the data management system 100 based on data drive may also be integrated in a cloud server or a private server within an enterprise. In one embodiment, the data management system 100 based on data drive may be used, for example, to implement an enterprise resource planning (ERP) system, and may execute multiple application programming interfaces (APIs) to call multiple demand data (such as personnel data stored in other servers and material information stored in other servers, etc.). In one embodiment, the process data group 102 refers to a task logic (or program) for executing a specific business function based on business data, such as task logic for executing a purchase order function based on procurement data, or task logic for executing a purchase requisition function based on purchase request data, but the present invention is not limited thereto.

[0101] In this embodiment, the processor 110 of the business data processing system 100 may include, for example, a central processing unit (CPU), or other programmable general-purpose or special-purpose microprocessors, digital signal processors (DSP), application specific integrated circuits (ASIC), programmable logic devices (PLD), other similar processing circuits, or a combination of these devices.

[0102] In this embodiment, the storage device 120 may be a remote cloud storage service or a local data storage service. The storage device 120 may include a memory and / or a database, wherein the memory may be, for example, a non-volatile memory (NVM). The storage device 120 may store relevant programs, modules, systems or algorithms for implementing the various embodiments of the present invention, so that the processor 110 can access and execute them to implement the relevant functions and operations described in the various embodiments of the present invention. The storage device 120 may also be used, for example, to cache the structured packaged process data described in the various embodiments of the present invention.

[0103] Figure 2 FIG. 1 is a flow chart of a data management method according to an embodiment of the present invention. Figure 1 as well as Figure 2 , the data management system 100 based on data drive may execute the following steps S210 to S230. In step S210, the processor 110 may receive the setting data set 101. In this embodiment, the processor 110 of the data management system 100 based on data drive may receive the setting data set 101 from a data source. In this regard, the data source may be, for example, data obtained through an application port or process setting data input by a user. Alternatively, the setting values ​​included in the setting data set 101 may be data generated by certain sensors and specific data processing, environmental information, or human settings, etc.

[0104] In step S220, the processor 110 performs a first compilation on the setting data group 101 to generate a plurality of component data groups. In one embodiment, the component data group is a technical component. In this embodiment, the setting data group refers to mapping certain transactions, processes, and processing logics in the real world into the digital domain and encapsulating them into data. In this embodiment, the setting data group may include executing corresponding processes and operations according to data states, executing specific processes (such as dispatching and filling out work orders) at each specific time according to set values, and fields in the original process data (fields refer to descriptions and implementations by the language of the corresponding coding program). The component data group may be data obtained by analyzing and classifying the setting data group.

[0105] For example, the component data group may be a target data flow, a data processing rule, a verification data setting component, or a behavior setting component. More specifically, the component data group may include multiple process components. The process component may be a data update component for updating data or for re-capturing data, a data browsing component for displaying and editing data, or a timed detection component for timed detection of data.

[0106] In step S230, the processor 110 performs a second compilation on the multiple component data groups to combine the multiple component data groups into the multiple process data groups 102. In the present embodiment, the process data group refers to an algorithm or logic that can process the structured and encapsulated data, and the task logic in the process data group can define the data range that it can process. Regarding the second compilation, specifically, the processor 110 combines the component data group with the corresponding process data (which can be a process with the same target data, such as a task process for calculating the total number of employees). In other words, the processor 110 adjusts and updates the original task process (i.e., multiple process data groups) according to the component data group. Specifically, the processor 110 combines the new process data into the original process data group according to the target data and processing logic in the task component, calculation component, and Js component loop component in the setting data group, thereby generating an updated process data group 102.

[0107] Figure 3 FIG. 1 is a schematic diagram of a data management system according to an embodiment of the present invention. Figure 1 as well as Figure 3 , the above step S210 also includes: the processor 110 displays multiple process models 302 on the display, and then receives multiple setting instructions input by the user. The multiple process models 302 include a drive model 340, an assignment model 330, a control model 310, a decision model 350, and a restriction model 320. Each setting instruction is one of a selection instruction, a parameter setting instruction, a script input instruction, and an assignment instruction. Specifically, the data management system 100 guides the user to input process settings and processing logic corresponding to different execution functions based on the multiple pre-set process models 302.

[0108] Specifically, the driving model 340 triggers the processor 110 to perform the corresponding process (such as dispatching work orders, displaying reminder information, and updating data) when the detected data or parameters meet specific conditions (such as specific time or specific data content). The restriction model 320 is to ensure that the business logic execution process must comply with the rules, that is, the rule setting before the process runs. The decision model 350 is a plurality of options in the process logic (i.e., the business processing logic), which allows the processor 110 to select and perform subsequent processing according to the set value after the preset value. For example, the preset value is to perform calculations, and the preset value can also be recommended according to the rules to simplify the user's decision-making process and shorten the decision-making time required by the user. The control model 310 compares the execution result with the set standard value, and then confirms and verifies whether the execution result meets the default value (i.e., the set standard value). In the control model 310, when the execution result does not meet the default value, the process logic is to execute related and corresponding subsequent process processing.

[0109] The assignment model 330 is a setting value for assigning a task to a specific person (eg, a person with more than 3 years of work experience, a person who has handled the same task, or a person at a supervisor level) when there is a clear job or task to be performed.

[0110] More specifically, the driving model 340 includes a timing parameter 341 and a working parameter 342. In one embodiment, the timing parameter 341 is a frequency parameter and a time period. The working parameter 342 is a specific task (e.g., task A) in the task flow. For example, the field resource planning project (i.e., the timing parameter 341) needs to send an updated task card (i.e., the working parameter 342) to the production management every day.

[0111] The assignment model 330 includes a work parameter 331 and a rule parameter 332. In one embodiment, the work parameter 331 is a specific task (e.g., task A) in the task flow. The rule parameter 332 is a specific person or a specific condition. For example, in the approval task (i.e., the work parameter 331), the reimbursement form with an approval amount greater than 10,000 yuan (rule parameter 332) will be automatically assigned to a senior manager for approval, and the reimbursement form with an amount less than 10,000 yuan will be approved by the direct supervisor.

[0112] The control model 310 includes a timing parameter 311, a standard setting parameter 312, and a measure parameter 313. In one embodiment, the timing parameter 311 is a setting parameter after a specific task is completed or a timed inspection parameter. The standard setting parameter 312 is a parameter for completing on time or completing by quantity. The measure parameter 313 is an early warning notification or an abnormality elimination.

[0113] Regarding the control model 310, for example, before the goods or process orders are put online in the workshop (i.e., the timing parameter 311), it is determined whether the key materials of the critical path are fully prepared (complete) (standard setting parameter 312). When the key materials are not complete, an email reminder (i.e., the measure parameter 313) is sent to the relevant staff. In this way, the setting of the control model 310 can automatically check the materials required for each process in advance to avoid the inability to start the manufacturing process due to the discovery of incomplete materials when the manufacturing process starts, thereby improving the automation of the task process.

[0114] The decision model 350 includes a timing parameter 351 and a basis parameter 352. In one embodiment, the timing parameter 351 is when a specific task is initiated, and the basis parameter 352 is evaluated according to an algorithm or an empirical rule. For example, for a material that is often out of stock (i.e., the timing parameter 351), a new supplier is selected. Therefore, based on the parameters such as the time required for delivery, the on-time delivery rate, and the available quantity (i.e., the basis parameter 352), the supplier that best meets the current task (e.g., the available quantity and the available time are both in line with the requirements of the current task) is calculated.

[0115] The restriction model 320 includes a target parameter 321, a condition parameter 322, and a behavior parameter 323. For example, the target parameter 321 is during or before the task is executed, the condition parameter 322 is based on personnel conditions or business rules, and the behavior parameter 323 is to display a prompt page or restrict the execution of a form. When an employee needs to report abnormal working hours (i.e., the target parameter 321), the corresponding reporting time (i.e., the behavior parameter 323) is provided according to the employee's position (i.e., the condition parameter 322). When the employee's position is a general employee, only the working hours content of the current month can be reported (i.e., the behavior parameter 323). When the employee's position is the chief officer level, the working hours content of the previous month and the current month can be reported (i.e., the behavior parameter 323). In this way, the restriction model 320 can achieve task restrictions and arrangements under different conditions to improve the stability and automation of task processes and data management.

[0116] In this embodiment, the storage device 120 stores the association relationship between multiple process models 302 and multiple component data groups 303. The above step S220 also includes that the processor 110 analyzes the setting data group 101 (i.e., data 301) and multiple process models 302 to obtain the corresponding component data group 303. The component data group 303 includes a target component 360, an activity component 370, a verification component 380, and a behavior component 390. In this way, the processor 110 performs a first compilation according to the corresponding model (i.e., process model 302) and parameter data in the setting data group 101, and then generates a target component 360, an activity component 370, a verification component 380, and a behavior component 390 respectively. Specifically, the target component 360 includes a task component 361, a project component 362, and an API component 363. The activity component 370 includes an activity data component 371, an ESP (Encapsulating Security Payloads) component 372, a task data component 373, a filtering component 374, a calculation component 375, and an operator component 376. The verification component 380 includes an expression component 381, a Js (JavaScript) component 382, ​​a loop component 383, and an exclusive component 384. The behavior component 390 includes an IM (Instant Messaging) component 391, an email component 392, a restriction form component 393, and a data update component 394. The processor 110 analyzes the component category corresponding to each component data group 303 from the setting data group 101 according to the input parameters or setting instructions in the setting data group 101. For example, the processor 110 analyzes the timing parameter 311 from the setting data group 101 and classifies the timing parameter 311 into the task component 361 in the target component 360. The processor 110 analyzes the sending email reminder in the measure parameter 313, and then generates the email component 392 in the behavior component 390 accordingly. In other words, the processor 110 converts the setting data group 101 into the component data group 303 by executing the first compilation, and then generates the process data 304 to be combined.

[0117] Figure 4 It is a schematic diagram of a first compilation and a second compilation according to an embodiment of the present invention. Figure 55 is a schematic diagram of a data management system of an exemplary embodiment of the present invention. The data management system 510 further includes an application program interface. The data management system 510 displays a plurality of process models 410 on a display of a client device 501 through the application program interface. In this embodiment, the application program interface receives a plurality of setting instructions corresponding to a plurality of process models to generate the setting data set 101, and outputs the setting data set to the processor. Specifically, the processor 110 receives the setting data set 101 by selecting one of the control capability 411, the restriction capability (i.e., the restriction model 320) 412, the decision capability (i.e., the decision model 350) 413, the assignment capability (i.e., the assignment model 330) 414, and the driving capability (i.e., the driving model 340) 415 by the user, and inputting various parameters 420 by the user, such as at least one of the timing parameter 421, the task execution 422, the timing parameter 423, the standard setting parameter 424, the rule parameter 425, and the action parameter 426. In other words, the setting data group is input data input by the user, and the setting data group includes the process model 302 type and input parameters.

[0118] In one embodiment, the target component 431 is related to the target instance in the set data group. The activity component 432 is related to the data acquisition path and data processing settings in the set data group. The verification component 433 is related to the standard data and the comparison settings between data. The behavior component 434 is related to the settings of the state and the corresponding processing behavior. In one embodiment, the processor obtains data from one of the storage device and the server according to the activity component 432, and performs data processing on the data, and the data processing logic includes execution logic and calculation model. The processor of the data management system determines the correctness of the data and the calculation result according to the verification component 433. The processor performs corresponding processing actions on the calculation result according to the behavior component 434.

[0119] For example, the target component 431 includes a task target. The active component 432 includes a data source path and data processing logic. The verification component 433 includes verification rules. The behavior component 434 includes task execution settings. It is worth noting that the processor can obtain corresponding process data from multiple process data according to the target component 431, that is, obtain the task (i.e., process data) of the corresponding set data group. In one embodiment, when the processor executes multiple process data, the processor obtains data according to the data source path of the active component 432 of the multiple component data groups, and then performs verification operations and processing on the data. For example, the process data group 450 includes multiple process paths (i.e., process data) 455, and each process data corresponds to a different task stage. For example, calculating data B from data A can be the first task stage, and then calculating data B with data C of other servers to obtain data D can be the second task stage. Therefore, the processor can match the task stage (i.e., process data) that meets the current target component from multiple process data through the target component.

[0120] In one embodiment, multiple process data sets form a data map or a process map. The above step S230 includes the processor 110 searching the data map according to the target (i.e., target component 431) in the multiple component data sets to obtain the corresponding process path (i.e., process path 440). In this way, the processor 110 combines the multiple component data sets into the process path 440 to update / establish multiple process data sets 450.

[0121] In one embodiment, the data management system 510 also includes a service monitoring 511, a server 502, a data management center 504, an authentication center 505, an application server 506, a registration center 507, a configuration center 508, and a service tracking 509, but the present case should not be limited to this. The storage device may include a cache data storage area 512, a persistent data storage area 513, a message queue area 514, a knowledge graph 515, and a log storage area 516. The server 502 may be nginx TMServer, server 502 is used to receive the setting data group from the terminal device (i.e., client device 501) through the application program interface, and input the setting data group to the load balancer 503 (Server Load Balancer, SLB). The load balancer 503 inputs the setting data group to multiple application servers 506 according to the current traffic. The registration center 507 is used to store the address of the external server. The configuration center 508 is used to store the database and the address of the application server 506. The service tracking 509 is used to record the call and link of the server 502. In addition, the registration center 507, the configuration center 508, and the service tracking 509 are used to provide the interaction function between the data management system 510 and the external server (for example, obtaining the current user's position from the member management server), and the log after the interaction will be stored in the log storage area 516. The authentication center 505 is used to obtain the current user's position and authority based on the user's login information.

[0122] Therefore, the data management system and data management method based on data drive of the present invention can convert the setting data group into a component data group through the first compilation, and then combine the component data group into multiple process paths according to the second compilation to obtain updated process data. In this way, the data management system can be used for data management and data process encapsulation, thereby realizing the reuse of experience knowledge, encapsulation of processing logic and automatic data processing.

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data management system based on data drive, characterized in that: include: A storage device for storing a plurality of process models; as well as a processor, coupled to the storage device, wherein the processor receives a setting data set, wherein the processor first compiles the setting data set to generate a plurality of component data sets, The processor performs a second compilation on the plurality of component data sets to combine the plurality of component data sets into a plurality of process data sets.

2. The data management system based on data drive according to claim 1, characterized in that: It also includes an application programming interface, wherein the application program interface displays the plurality of process models on a display, The application program interface receives a plurality of setting instructions corresponding to the plurality of process models to generate the setting data set, and outputs the setting data set to the processor.

3. The data management system based on data drive according to claim 1, characterized in that: The multiple process data groups constitute a data map, wherein the processor searches the data map according to the target in the plurality of component data sets to obtain a process path, The processor combines the plurality of component data sets into the process path to update the plurality of process data sets.

4. The data management system based on data drive according to claim 2, characterized in that: The plurality of process models include a driving model, an assignment model, a control model, a decision model, and a restriction model, wherein each of the plurality of setting instructions is one of a selection instruction, a parameter setting instruction, a script input instruction, and an assignment instruction.

5. The data management system based on data drive according to claim 4, characterized in that: Also included is a server, wherein the server receives the setting data set from the terminal device through an application program interface and inputs the setting data set to the load balancer, The load balancer outputs the set data group to multiple application servers according to the current traffic.

6. The data management system based on data drive according to claim 4, characterized in that: The driving model includes timing parameters and working parameters, the assignment model includes working parameters and rule parameters, the control model includes timing parameters, standard setting parameters and measure parameters, the decision model includes timing parameters and basis parameters, and the restriction model includes target parameters, condition parameters and behavior parameters. The processor performs the first compilation according to the corresponding model and parameter data in the setting data group, thereby generating a target component, an activity component, a verification component and a behavior component respectively.

7. The data management system based on data drive according to claim 1, characterized in that: The processor analyzes the setting data set and the plurality of process models to obtain the plurality of component data sets, wherein the plurality of component data sets include a target component, an activity component, a verification component, and a behavior component.

8. The data management system based on data drive according to claim 7, characterized in that: The target component is related to the target instance in the setting data group, wherein the activity component is related to the data acquisition path and data processing settings in the setting data group, wherein the verification component is related to standard data and comparison settings between data, and wherein the behavior component is related to the status and corresponding processing behavior settings.

9. The data management system based on data drive according to claim 7, characterized in that: The target component includes a task target, wherein the activity component includes a data source path and a data processing logic, wherein the verification component includes a verification rule, and wherein the behavior component includes a task execution setting.

10. The data management system based on data drive according to claim 7, characterized in that: The data processing logic includes execution logic and a calculation model.

11. A data management method, characterized in that: include: receiving, by a processor, a set data set; performing a first compile of the setting data set by the processor to generate a plurality of component data sets; as well as The processor performs a second compilation on the plurality of component data sets to combine the plurality of component data sets into a plurality of process data sets.

12. The data management method according to claim 11, characterized in that: The step of the processor receiving the setting data group comprises: Display multiple process models on the monitor through the application program interface; as well as A plurality of setting instructions corresponding to the plurality of process models are received through the application program interface to generate the setting data set, and the setting data set is output to the processor.

13. The data management method according to claim 11, characterized in that: A plurality of process data groups form a data map, wherein the step of performing a second compilation on the plurality of component data groups by the processor to combine the plurality of component data groups into the plurality of process data includes: Searching the data map according to the targets in the plurality of component data sets by the processor to obtain a process path; and The processor combines the plurality of component data sets into the process path to update the plurality of process data sets.

14. The data management method according to claim 12, characterized in that: The plurality of process models include a driving model, an assignment model, a control model, a decision model, and a restriction model, wherein each of the plurality of setting instructions is one of a selection instruction, a parameter setting instruction, a script input instruction, and an assignment instruction.

15. The data management method according to claim 14, characterized in that: The step of receiving the setting data group by the processor further includes: receiving the configuration data set from the terminal device through an application program interface by the server, and inputting the configuration data set into the load balancer; and The load balancer outputs the set data group to multiple application servers according to current traffic.

16. The data management method according to claim 14, characterized in that: The driving model includes timing parameters and working parameters, the assignment model includes working parameters and rule parameters, the control model includes timing parameters, standard setting parameters and measure parameters, the decision model includes timing parameters and basis parameters, and the restriction model includes target parameters, condition parameters and behavior parameters. The step of first compiling the setting data set by the processor to generate the plurality of component data sets comprises: The processor performs the first compilation according to the corresponding model and parameter data in the setting data group, thereby generating a target component, an activity component, a verification component and a behavior component respectively.

17. The data management method according to claim 11, characterized in that: The step of the processor performing a first compilation on the setting data set to generate a plurality of component data sets comprises: The processor analyzes the setting data set and a plurality of process models to obtain the plurality of component data sets, wherein the plurality of component data sets include a target component, an activity component, a verification component, and a behavior component.

18. The data management method according to claim 17, characterized in that: The target component is related to the target instance in the setting data group, wherein the activity component is related to the data acquisition path and data processing settings in the setting data group, wherein the verification component is related to standard data and comparison settings between data, and wherein the behavior component is related to the status and corresponding processing behavior settings.

19. The data management method according to claim 17, characterized in that: The target component includes a task target, wherein the activity component includes a data source path and a data processing logic, wherein the verification component includes a verification rule, and wherein the behavior component includes a task execution setting.

20. The data management method according to claim 17, characterized in that: The data processing logic includes execution logic and a calculation model.

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