CN112860629B - Method and system for attributing performance, computer equipment and readable storage medium thereof - Google Patents
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Abstract
The invention relates to a performance attribution method and system, a computer device and a readable storage medium thereof. The performance attribution method comprises the following steps: establishing a performance attribution rule; loading the performance attribution rule into a rule engine, and creating a rule engine instance; carrying out standard preprocessing on the transaction source data, and outputting the transaction source data in a standard format; inputting the transaction source data in the standard format into a rule engine, and making a performance attribution decision by the rule engine according to a performance attribution rule of a rule engine instance; and obtaining and storing a performance attribution decision result from the rule engine. The performance attribution method and the system preprocess the discrete data into the flattened standard format data, reduce the data processing complexity during performance attribution, reduce the error rate and improve the performance attribution processing efficiency. By using the performance attribution method and the system, the performance attribution of each time does not need manual intervention, and the human resource investment can be reduced.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a performance attribution method and system, a computer device, and a readable storage medium thereof.
Background
The traditional performance attribution method is to use Excel table or Database (DB) storage process to count the business data according to the appointed performance attribution logic, and finally obtain the performance attribution result. According to the performance attribution scheme based on the Excel form, business data are required to be imported into the Excel form, and manual processing is carried out according to the appointed performance attribution logic. In the scheme, manual operation is needed for each performance attribution, time is long, and errors are prone to occurring. And setting execution time based on the performance attribution scheme in the database storage process, and automatically triggering and completing the performance attribution by the system. Due to the implementation of the database-based storage process, the performance attribution rules are not easy to maintain.
Disclosure of Invention
In view of the foregoing, there is a need for a performance attribution method and system, a computer device, and a readable storage medium thereof that can efficiently distribute credit orders.
An embodiment of the present invention provides a performance attribution method, which includes the following steps:
s1: establishing a performance attribution rule;
s2: loading the performance attribution rule into a rule engine, and creating a rule engine instance;
s3: carrying out standard preprocessing on the transaction source data, and outputting the transaction source data in a standard format;
s4: inputting the transaction source data in the standard format into a rule engine, and making a performance attribution decision by the rule engine according to a performance attribution rule of a rule engine instance;
s5: and obtaining and storing a performance attribution decision result from the rule engine.
As a further improvement of the above embodiment, in step S1, the performance attribution rules of the visualization are created in the visualization interface, and the performance attribution rules of the visualization are saved in the database.
As a further modification of the above embodiment, the step S2 further includes the steps of:
s21: compiling a performance attribution rule template according to business requirements, and storing the performance attribution rule template into a template file;
s22: loading the performance attribution rule, and generating a complete performance attribution rule text by using a template engine and combining the performance attribution rule template;
s23: loading the complete performance attribution rule text into the rules engine, creating the rules engine instance.
As a further modification of the above embodiment, the step S3 further includes the steps of:
s31: creating a data standardization preprocessing task;
s32: flattening preprocessing is carried out on the scattered transaction source data to obtain transaction source data in a standard format;
s33: and saving the standard format transaction source data into a database.
Another aspect of an embodiment of the present invention further provides a performance attribution system, which includes:
the rule creating module is used for creating a performance attribution rule;
the data standardization module is used for carrying out standardization preprocessing on the transaction source data and outputting the transaction source data in a standard format;
the rule engine module is used for making performance attribution decisions according to the performance attribution rules and the standard format transaction source data;
and the storage module is used for acquiring and storing the performance attribution decision result from the rule engine and storing the performance attribution rule.
As a further improvement of the above embodiment, the rule creating module has a visualization interface, and creates a visualization performance attribution rule in the rule creating module, and saves the visualization performance attribution rule in the storage module.
As a further refinement of the above embodiment, the performance attribution system further comprises:
the achievement attribution rule template module is used for compiling an achievement attribution rule template according to business requirements and storing the achievement attribution rule template into a template file;
the template engine module is used for generating a complete achievement attribution rule text according to the achievement attribution rule and the achievement attribution rule template;
the rules engine creates the rules engine instance from the complete performance attribution rules text.
As a further improvement of the above embodiment, the data standardization module creates a data standardization preprocessing task and performs flattening preprocessing on the scattered transaction source data to obtain standard format transaction source data, and stores the standard format transaction source data in the storage module.
Embodiments of the present invention further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements the steps of the performance attribution method according to any one of the above embodiments.
Embodiments of the present invention further provide a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the processor implements the steps of the performance attribution method according to any one of the above embodiments.
The performance attribution method and the system preprocess the discrete data into the flattened standard format data, reduce the data processing complexity during performance attribution, reduce the error rate and improve the performance attribution processing efficiency. By using the performance attribution method and the system, the performance attribution of each time does not need manual intervention, and the human resource investment can be reduced.
Drawings
The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular description of preferred embodiments of the invention, as illustrated in the accompanying drawings. Like reference numerals refer to like parts throughout the drawings, and the drawings are not intended to be drawn to scale in actual dimensions, emphasis instead being placed upon illustrating the principles of the invention.
Fig. 1 is a flow chart of a performance attribution method according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a performance attribution system according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a performance attribution system according to another embodiment of the present invention.
Fig. 4 is a schematic diagram of the business flow of the performance attribution system according to the embodiment of the present invention.
Fig. 5 is a diagram of a visualization of performance attribution rules.
FIG. 6 is a schematic diagram of transaction source data normalization preprocessing.
Fig. 7 is a diagram of performance attribution rules text.
Detailed Description
The following detailed description of the present invention is provided in connection with the accompanying drawings and specific embodiments for the purpose of better understanding and enabling those skilled in the art to practice the present invention, which are not intended to limit the present invention.
Referring to fig. 1 to 7, an embodiment of the invention provides a performance attribution method, which includes the following steps:
s1: and establishing a performance attribution rule. In particular, referring to fig. 4 and 5, a system administrator may maintain performance attribution rules through the administration platform, the performance attribution rules being maintained in a database. A performance rule maintenance function (page) can be written in a background management system, and addition, modification, deletion and viewing of performance attribution rules are supported.
S2: the performance attribution rules are loaded into the rules engine, creating a rules engine instance. Introducing rules engine dependent dependencies in the program, establishing performance attribution rules also following the rules engine syntax, loading the performance attribution rules stored in the database, and initializing rules engine instances using these rules.
S3: and carrying out standardized preprocessing on the transaction source data and outputting the transaction source data in a standard format. Referring to fig. 6, the distributed source data is subjected to flattening preprocessing, and standard format transaction source data is output.
S4: the standard format transaction source data is input into a rules engine, which makes performance attribution decisions based on performance attribution rules for the rules engine instance. And performance attribution is realized based on the rule engine, the complexity and the coupling degree of the program code are reduced, and the maintenance cost of the program code is reduced.
S5: and obtaining and storing a performance attribution decision result from the rule engine. The performance attribution decision results may be saved to a database.
In a preferred embodiment, in step S1, visualization performance attribution rules are created in the visualization interface and saved to the database. Fig. 5 shows an example of performance attribution rules for visualization. The 'rule field' of the attribution condition is a standard format field after data preprocessing and corresponds to standard format data; "conditional operators" include equal, greater than, less than, not equal to, empty, not empty, etc.; supporting the configuration of multiple conditions and condition blocks. The performance attribution rule is separated from the program code, and the configuration of the performance attribution rule can be quickly and conveniently realized through a visual operation interface. When the performance attribution rule is changed, only the login management platform is required to be modified through the visual interface, and the modified performance attribution rule takes effect immediately.
In a preferred embodiment, step S2 further includes the steps of:
s21: and compiling a performance attribution rule template according to the business requirements, and storing the performance attribution rule template into a template file.
S22: and loading the performance attribution rule, and generating a complete performance attribution rule text by using a template engine and combining the performance attribution rule template. And loading the performance attribution rule from a database, and rendering a complete performance attribution rule text by using a template engine and combining the rule template file in the previous step. Fig. 7 is an illustration of an example of complete performance attribution rule text.
S23: loading the complete performance attribution rule text into the rules engine, creating the rules engine instance.
In a preferred embodiment, step S3 further includes the steps of:
s31: creating a data standardization preprocessing task;
s32: flattening preprocessing is carried out on the scattered transaction source data to obtain transaction source data in a standard format;
s33: and saving the standard format transaction source data into a database.
Referring to fig. 2 to 4, an embodiment of the present invention further provides a performance attribution system, which includes:
a rule creating module 101, configured to create a performance attribution rule;
the data standardization module 102 is used for carrying out standardization preprocessing on the transaction source data and outputting the transaction source data in a standard format;
the rule engine module 103 is used for making performance attribution decisions according to the performance attribution rules and the standard format transaction source data;
and the storage module 104 is used for acquiring and storing the performance attribution decision result from the rule engine 103 and storing the performance attribution rule. The storage module 104 may be a database.
Referring to fig. 5, in a preferred embodiment, the rule creation module 101 has a visualization interface, establishes the visualized performance attribution rules in the rule creation module 101, and saves the visualized performance attribution rules to the storage module 104.
Referring to fig. 3, in a preferred embodiment, the performance attribution system further comprises:
the achievement attribution rule template module 105 is used for compiling an achievement attribution rule template according to business requirements and storing the achievement attribution rule template into a template file;
the template engine module 106 is used for generating a complete achievement attribution rule text according to the achievement attribution rule and the achievement attribution rule template;
the rules engine 103 creates a rules engine instance from the complete performance attribution rules text.
In a preferred embodiment, the data normalization module 102 creates a data normalization preprocessing task and performs flattening preprocessing on the scattered transaction source data to obtain standard format transaction source data, and stores the standard format transaction source data in the storage module 104.
The present invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the performance attribution method of any of the above embodiments. The computer-readable storage medium includes, but is not limited to, any type of disk including floppy disks, hard disks, optical disks, CD-ROMs, and magneto-optical disks, ROMs (Read-Only memories), RAMs (Random access memories), EPROMs (EraSable Programmable Read-Only memories), EEPROMs (Electrically EraSable Programmable Read-Only memories), flash memories, magnetic cards, or optical cards. That is, a storage device includes any medium that stores or transmits information in a form readable by a device (e.g., a computer, a cellular phone), and may be a read-only memory, a magnetic or optical disk, or the like.
Embodiments of the present invention further provide a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the performance attribution method according to any one of the above embodiments are implemented. The computer device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server or a cabinet server (including an independent server or a server cluster composed of a plurality of servers) capable of executing programs, and the like. The computer device of the embodiment at least includes but is not limited to: a memory, a processor communicatively coupled to each other via a system bus.
The processor may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor is typically used to control the overall operation of the computer device. In this embodiment, the processor is configured to run program codes stored in the memory or process data to implement the performance attribution method of the above-described embodiments.
The performance attribution method and the system preprocess the discrete data into the flattened standard format data, reduce the data processing complexity during performance attribution, reduce the error rate and improve the performance attribution processing efficiency. By using the performance attribution method and the system, the performance attribution of each time does not need manual intervention, and the human resource investment can be reduced.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (6)
1. A method of performance attribution, comprising the steps of:
s1: establishing a performance attribution rule;
s2: loading the performance attribution rule into a rule engine, and creating a rule engine instance;
s3: carrying out standard preprocessing on transaction source data and outputting a source data file with a standard format;
s4: inputting the transaction source data in the standard format into a rule engine, and making a performance attribution decision by the rule engine according to a performance attribution rule of a rule engine instance;
s5: acquiring and storing a performance attribution decision result from the rule engine;
step S2 further includes the steps of:
s21: compiling a performance attribution rule template according to business requirements, and storing the performance attribution rule template into a template file;
s22: loading the performance attribution rule, and generating a complete performance attribution rule text by using a template engine and combining the performance attribution rule template;
s23: loading the complete performance attribution rule text into the rule engine, creating the rule engine instance;
step S3 further includes the steps of:
s31: creating a data standardization preprocessing task;
s32: flattening preprocessing is carried out on the scattered transaction source data to obtain transaction source data in a standard format;
s33: and saving the standard format transaction source data into a database.
2. The performance attribution method of claim 1, wherein in step S1, visualized performance attribution rules are created in a visualization interface and saved in a database.
3. A performance attribution system, comprising:
the rule creating module is used for creating a performance attribution rule;
the data standardization module is used for carrying out standardization preprocessing on the transaction source data and outputting the transaction source data in a standard format;
the rule engine module is used for making performance attribution decisions according to the performance attribution rules and the standard format transaction source data;
the storage module is used for acquiring and storing a performance attribution decision result from the rule engine and storing the performance attribution decision result and the performance attribution rule;
the achievement attribution rule template module is used for compiling an achievement attribution rule template according to business requirements and storing the achievement attribution rule template into a template file;
the template engine module is used for generating a complete achievement attribution rule text according to the achievement attribution rule and the achievement attribution rule template;
the rule engine creates the rule engine instance according to the complete performance attribution rule text;
the data standardization module creates a data standardization preprocessing task and carries out flattening preprocessing on scattered transaction source data to obtain standard format transaction source data, and the standard format transaction source data are stored in the storage module.
4. The performance attribution system of claim 3, wherein the rule creation module has a visualization interface, wherein visualized performance attribution rules are established in the rule creation module, and wherein the visualized performance attribution rules are saved to the storage module.
5. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the performance attribution method of any one of claims 1-2.
6. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the steps of the performance attribution method of any one of claims 1 to 2 are implemented by the processor when executing the computer program.
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| US5010478A (en) * | 1986-04-11 | 1991-04-23 | Deran Roger L | Entity-attribute value database system with inverse attribute for selectively relating two different entities |
| US7809632B2 (en) * | 2006-04-12 | 2010-10-05 | Uat, Inc. | System and method for assigning responsibility for trade order execution |
| US8965827B2 (en) * | 2011-03-30 | 2015-02-24 | Computer Sciences Corporation | Rules execution platform system and method |
| CN109284106A (en) * | 2018-07-18 | 2019-01-29 | 平安科技（深圳）有限公司 | Method for release management, electronic device and the readable storage medium storing program for executing of business rule |
| CN110109922B (en) * | 2019-04-04 | 2024-05-24 | 广州易策医管科技有限公司 | Performance data acquisition method, device, computer equipment and storage medium |
| CN110647546A (en) * | 2019-09-18 | 2020-01-03 | 北京明略软件系统有限公司 | Third-party rule engine generation method and device |
| CN111951010A (en) * | 2020-07-26 | 2020-11-17 | 中国建设银行股份有限公司 | Business decision method and device based on rule engine, electronic equipment and readable storage medium |
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