CN113298354A - Automatic generation method and device of business derivative index and electronic equipment - Google Patents
Automatic generation method and device of business derivative index and electronic equipment Download PDFInfo
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Abstract
The disclosure relates to an automatic generation method and device of a business derived index, electronic equipment and a computer readable medium. The method comprises the following steps: generating a plurality of business process data based on the product interaction page and the business category; establishing entity contact data based on a plurality of data tables in a service database; establishing an incidence relation between the plurality of data tables and the service categories based on the plurality of service process data, wherein the data tables comprise atom indexes; establishing logical relationships between the plurality of data tables based on the entity contact data; and automatically generating a business derivative index according to the business category, the incidence relation and the logic relation, wherein the business derivative index is composed of at least one atomic index. The automatic generation method, the automatic generation device, the electronic equipment and the computer readable medium of the business derived index can improve the efficiency of data output and the efficiency of business analysis decision.
Description
Technical Field
The present disclosure relates to the field of computer information processing, and in particular, to an automatic generation method and apparatus for a service derivative indicator, an electronic device, and a computer-readable medium.
Background
The data analysis index system is that on the basis of recognized and unified data indexes, a group of data indexes related to business problems or decision objectives are constructed around the business problems or the decision objectives, the internal structure and relevance of the group of indexes are analyzed, and the data indexes are directly applied to problem analysis or objective decision through construction of an analysis model.
A large number of data tables related to services are stored in the service database, and the data stored in such tables can be regarded as atomic indexes, and in general, indexes without any modifier in the data tables are atomic indexes, also called metrics, and in general, in the tables, aggregation fields, order quantities, user quantities, pv, uv, and the like. The atomic indexes are relatively single and cannot provide complete business analysis capability, thereby resulting in low efficiency, effectiveness and benefit of business analysis. The atomic indexes are subjected to addition, subtraction, multiplication and division or the limitation of modifiers, and the like, and the derived indexes can reflect more information, so that business analysts often need to generate the derived indexes based on the atomic indexes to construct a data analysis index system. However, currently, the derivative indexes are generated by combining a plurality of atomic indexes basically depending on experience accumulation of analysts, the generation efficiency of the derivative indexes is low, and whether the derivative indexes are the optimal atomic index combination or not is unknown.
Therefore, a new method, an apparatus, an electronic device and a computer-readable medium for automatically generating a new service derived index are needed.
The above information disclosed in this background section is only for enhancement of understanding of the background of the disclosure and therefore it may contain information that does not constitute prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
In view of this, the present disclosure provides an automatic generation method and apparatus for a service derivative index, an electronic device, and a computer readable medium, which can improve the efficiency of data output and the efficiency of business analysis decision, provide necessary monitoring and early warning for key service processes and OKR, and avoid the problems of data cluster resource waste and the like.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to an aspect of the present disclosure, a method for automatically generating a service derivation index is provided, where the method includes: generating a plurality of business process data based on the product interaction page and the business category; establishing entity contact data based on a plurality of data tables in a service database; establishing an incidence relation between the plurality of data tables and the service categories based on the plurality of service process data, wherein the data tables comprise atom indexes; establishing logical relationships between the plurality of data tables based on the entity contact data; and automatically generating a business derivative index according to the business category, the incidence relation and the logic relation, wherein the business derivative index is composed of at least one atomic index.
Optionally, comprising: and generating a business core index based on the corresponding dimension characteristic and time characteristic of the business derivative index and the internal atomic index thereof.
Optionally, generating a service core index based on the service derivative index and the dimensional characteristic and the time characteristic corresponding to the internal atomic index thereof includes: extracting dimensional features of the atomic index based on the plurality of data tables; extracting the time characteristics of the atomic indexes based on the business process data; and generating a business core index based on the corresponding dimension characteristic and time characteristic of the business derivative index and the internal atomic index thereof.
Optionally, the method further comprises: and generating service warning information when the service core index does not accord with a preset strategy.
Optionally, the method further comprises: establishing a monitoring instruction of the business derived index on a business platform to generate the business derived index at regular time; and generating the service core index at regular time according to the service derivative index.
Optionally, generating a plurality of business process data based on the product interaction page and the business category includes: acquiring bottom program data of a product interaction page; extracting a business interaction process between the product interaction pages based on the bottom program data; and generating the business process data based on the business interaction process.
Optionally, the establishing entity contact data based on a plurality of data tables in the service database includes: extracting entity types, attributes and incidence relations in the data tables; and establishing entity contact data based on the entity type, the attribute and the incidence relation.
Optionally, establishing an association relationship between the plurality of data tables and the service categories based on the plurality of service process data includes: extracting the extraction relation between each business process data in the plurality of business process data and the data table based on the bottom layer program data; and establishing an association relation among the plurality of data tables based on the plurality of business process data and the extraction relation.
Optionally, automatically generating a service derivation index according to the service category, the association relationship, and the logical relationship includes: automatically generating a plurality of initial business derivation indexes according to the business category, the incidence relation and the logic relation; and examining the plurality of initial business derivative indexes through historical business data to generate the business derivative indexes.
Optionally, automatically generating a plurality of initial service derivation indicators according to the service category, the association relationship, and the logical relationship, includes: determining a target atomic index related to the business category; extracting other atom indexes related to the target atom index based on the incidence relation and the logic relation; generating the initial business derivative metrics based on the target atomic metrics and the other atomic metrics.
According to an aspect of the present disclosure, an apparatus for automatically generating a service derived index is provided, the apparatus including: the flow module is used for generating a plurality of business flow data based on the product interaction page and the business category; the entity module is used for establishing entity contact data based on a plurality of data tables in the service database; the association module is used for establishing association relations among the plurality of data tables and the service categories based on the plurality of service process data, wherein the data tables comprise atom indexes; a logic module for establishing a logical relationship between the plurality of data tables based on the entity contact data; and the derivation module is used for automatically generating a business derivation index according to the business category, the incidence relation and the logic relation, wherein the business derivation index is composed of at least one atom index.
Optionally, comprising: and the core module is used for generating a service core index based on the service derivative index and the corresponding dimension characteristic and time characteristic of the internal atomic index.
Optionally, the core module includes: a dimension unit for extracting dimension features of the atomic index based on the plurality of data tables; the time unit is used for extracting the time characteristics of the atomic indexes based on the business process data; and the core unit is used for generating a service core index based on the service derivative index and the corresponding dimension characteristic and time characteristic of the internal atomic index.
Optionally, the method further comprises: and the warning module is used for generating service warning information when the service core index does not accord with a preset strategy.
Optionally, the method further comprises: the monitoring module is used for establishing a monitoring instruction of the business derived index on a business platform so as to generate the business derived index at regular time; and generating the service core index at regular time according to the service derivative index.
Optionally, the flow module includes: the program unit is used for acquiring bottom program data of the product interaction page; the extraction unit is used for extracting the business interaction flow among the product interaction pages based on the underlying program data; and the flow unit is used for generating the business flow data based on the business interaction flow.
Optionally, the entity module is further configured to extract entity types, attributes, and association relationships in the plurality of data tables; and establishing entity contact data based on the entity type, the attribute and the incidence relation.
Optionally, the associating module includes: the relation unit is used for extracting the extraction relation between each business process data in the plurality of business process data and the data table based on the bottom program data; and the establishing unit is used for establishing the association relation among the plurality of data tables based on the plurality of business process data and the extraction relation.
Optionally, the derivation module is further configured to use an initial unit, configured to automatically generate a plurality of initial business derivation indicators according to the business category, the association relationship, and the logical relationship; and the derivation unit is used for examining the plurality of initial business derivation indexes through historical business data so as to generate the business derivation indexes.
Optionally, the initial unit is further configured to determine a target atomic index related to a service class; extracting other atom indexes related to the target atom index based on the incidence relation and the logic relation; generating the initial business derivative metrics based on the target atomic metrics and the other atomic metrics.
According to an aspect of the present disclosure, an electronic device is provided, the electronic device including: one or more processors; storage means for storing one or more programs; when executed by one or more processors, cause the one or more processors to implement a method as above.
According to an aspect of the disclosure, a computer-readable medium is proposed, on which a computer program is stored, which program, when being executed by a processor, carries out the method as above.
According to the automatic generation method and device of the business derivative index, the electronic equipment and the computer readable medium, a plurality of business process data are generated based on the product interaction page and the business category; establishing entity contact data based on a plurality of data tables in a service database; establishing an incidence relation between the plurality of data tables and the service categories based on the plurality of service process data, wherein the data tables comprise atom indexes; establishing logical relationships between the plurality of data tables based on the entity contact data; and automatically generating service derived indexes according to the service category, the incidence relation and the logic relation, wherein the service derived indexes are composed of at least one atomic index, so that the data output efficiency can be improved, the operation analysis decision efficiency can be improved, necessary monitoring and early warning can be provided for key service processes and OKR, and the problems of data cluster resource waste and the like can be avoided.
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.
Drawings
The above and other objects, features and advantages of the present disclosure will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings. The drawings described below are merely some embodiments of the present disclosure, and other drawings may be derived from those drawings by those of ordinary skill in the art without inventive effort.
Fig. 1 is a system block diagram illustrating a method and an apparatus for automatically generating a service derivation index according to an exemplary embodiment.
FIG. 2 is a flow diagram illustrating a method for automatic generation of business derivative metrics in accordance with an exemplary embodiment.
FIG. 3 is a flow chart illustrating a method for automatic generation of business derivative metrics in accordance with another exemplary embodiment.
FIG. 4 is a flow chart illustrating a method for automatic generation of business derivative metrics in accordance with another exemplary embodiment.
Fig. 5 is a block diagram illustrating an apparatus for automatically generating business derived metrics in accordance with an exemplary embodiment.
Fig. 6 is a block diagram illustrating an apparatus for automatically generating business derived metrics in accordance with another exemplary embodiment.
FIG. 7 is a block diagram illustrating an electronic device in accordance with an example embodiment.
FIG. 8 is a block diagram illustrating a computer-readable medium in accordance with an example embodiment.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals denote the same or similar parts in the drawings, and thus, a repetitive description thereof will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
It will be understood that, although the terms first, second, third, etc. may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one element from another. Thus, a first component discussed below may be termed a second component without departing from the teachings of the disclosed concept. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
It is to be understood by those skilled in the art that the drawings are merely schematic representations of exemplary embodiments, and that the blocks or processes shown in the drawings are not necessarily required to practice the present disclosure and are, therefore, not intended to limit the scope of the present disclosure.
Fig. 1 is a system block diagram illustrating a method and an apparatus for automatically generating a service derivation index according to an exemplary embodiment.
As shown in fig. 1, system architecture 10 may include business databases 101, 102, 103, network 104, and server 105. Network 104 serves as a medium for providing communication links between service databases 101, 102, 103 and server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The service related data may be stored by using the service databases 101, 102, 103, more specifically, different service databases may store data of different service classes. The business databases 101, 102, 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server that provides various services, such as a back-office management server that provides data analysis for data in the business databases 101, 102, 103. The background management server can analyze and process the business data and feed back the extracted business derived indexes to the administrator of the financial service website.
The server 105 can generate a plurality of business process data, for example, based on the product interaction page and the business category; the server 105 may establish entity contact data, for example, based on a plurality of data tables in a business database; the server 105 may establish an association relationship between the plurality of data tables and the service categories, for example, based on the plurality of service process data, where the data tables include an atomic index; server 105 may establish logical relationships between the plurality of data tables, for example, based on the entity contact data; the server 105 may automatically generate a business derivative index, for example, according to the business category and the association relationship, the logical relationship, the business derivative index being composed of at least one atomic index.
The server 105 may also generate a business core index based on the corresponding dimensional features and time features of the business derivative index and its internal atomic index, for example.
The server 105 may also generate the service alert information, for example, when the service core indicator does not meet a preset policy.
The server 105 may be a single entity server, or may be composed of a plurality of servers, for example, it should be noted that the method for automatically generating the business derivation index provided by the embodiment of the present disclosure may be executed by the server 105, and accordingly, an automatic generating device of the business derivation index may be disposed in the server 105.
FIG. 2 is a flow diagram illustrating a method for automatic generation of business derivative metrics in accordance with an exemplary embodiment. The method 20 for automatically generating a service derived indicator at least comprises steps S202 to S210.
As shown in FIG. 2, in S202, a plurality of business process data are generated based on the product interaction page and the business category. The underlying program data of the product interaction page can be obtained, for example; extracting a business interaction process between the product interaction pages based on the bottom program data; and generating the business process data based on the business interaction process.
In the present disclosure, a specific technical description is given for a certain platform providing financial network services as an example, and it is understood that the method in the present disclosure may also be applied to network platforms in other fields.
In a financial network service platform, a product can be a resource product, and in the present disclosure, a resource refers to any substance, information, and time that can be utilized, and an information resource includes a computing resource and various types of data resources. The data resources include various private data in various domains. However, for convenience, the financial data resources are used as an example in the present invention, but those skilled in the art will understand that the present invention can also be used for allocation of other resources.
The user can perform operations of registration, credit granting, login, risk assessment, third party risk assessment, resource allocation, resource return and the like on the product interaction page. The interaction page can also comprise a promotion display page, a third-party transaction page, an administrator operation page and the like. The product interaction pages can be divided into user interaction pages, transaction interaction pages, log interaction pages, marketing interaction pages and the like according to the service categories.
And extracting bottom program data according to the types of different product interaction pages, analyzing the bottom program data to extract service logic between the product interaction pages, and further generating service flow data.
In S204, entity contact data is established based on the plurality of data tables in the business database. The entity types, attributes and incidence relations in the plurality of data tables can be extracted, for example; and establishing entity contact data based on the entity type, the attribute and the incidence relation.
The entity type in the data table may be used as an identifier of an atomic index, and specifically may be a user identifier, an order type, an order quantity, a user quantity, pv, uv, and the like. The attribute may be a data attribute of the atomic index, and the association may be an association between identifiers of the plurality of data tables based on the atomic index. If the user identifier exists in a plurality of data tables, the plurality of data tables containing the user identifier may be considered to be associated.
The objects that can be objectively distinguished from each other are entities, which may be concrete persons and things, or abstract concepts and connections. The key is that one entity can be distinguished from another entity, and entities with the same attributes have the same characteristics and properties. The entity name and its attribute name set are used to abstract and characterize the same kind of entity.
An entity may be characterized by several attributes. Attributes cannot be separated from an entity, and attributes are relative to an entity. The E-R diagram is represented by an ellipse and is connected with a corresponding entity by a non-directional edge; such as the name, school number, gender, of the student are attributes. And if the multi-value attribute exists, sleeving the solid line ellipse outside the ellipse. If it is a derived attribute, it is represented by a dashed ellipse.
Relationships, also known as relationships, reflect associations within or between entities in the information world. An intra-entity association generally refers to an association between the attributes that make up an entity; an association between entities generally refers to an association between different sets of entities.
In S206, an association relationship between the plurality of data tables and the service categories is established based on the plurality of service process data, where the data tables include an atomic index. The method comprises the following steps: extracting the extraction relation between each business process data in the plurality of business process data and the data table based on the bottom layer program data; and establishing an association relation among the plurality of data tables based on the plurality of business process data and the extraction relation.
More specifically, the read or write relationship for each data table in the business process may be extracted based on the underlying program data, the table entry modification relationship for each data table in the business process may also be extracted, and so on.
In S208, logical relationships between the plurality of data tables are established based on the entity contact data. As described above, the associations may be associations between multiple data tables based on the identification of the atomic index. If the user identifier exists in a plurality of data tables, the plurality of data tables containing the user identifier may be considered to be associated. And converting the incidence relation into a logical relation based on the entity contact data.
In S210, a service derivative index is automatically generated according to the service category, the association relationship, and the logical relationship, where the service derivative index is composed of at least one atomic index. The method comprises the following steps: automatically generating a plurality of initial business derivation indexes according to the business category, the incidence relation and the logic relation; and examining the plurality of initial business derivative indexes through historical business data to generate the business derivative indexes.
The detailed contents of "automatically generating the service derivation index according to the service category and the association relationship, the logical relationship" will be described in the embodiment corresponding to fig. 4.
According to the automatic generation method of the business derived index, a plurality of business process data are generated based on the product interaction page and the business category; establishing entity contact data based on a plurality of data tables in a service database; establishing an incidence relation between the plurality of data tables and the service categories based on the plurality of service process data, wherein the data tables comprise atom indexes; establishing logical relationships between the plurality of data tables based on the entity contact data; and automatically generating service derived indexes according to the service category, the incidence relation and the logic relation, wherein the service derived indexes are composed of at least one atomic index, so that the data output efficiency can be improved, the operation analysis decision efficiency can be improved, necessary monitoring and early warning can be provided for key service processes and OKR, and the problems of data cluster resource waste and the like can be avoided.
It should be clearly understood that this disclosure describes how to make and use particular examples, but the principles of this disclosure are not limited to any details of these examples. Rather, these principles can be applied to many other embodiments based on the teachings of the present disclosure.
FIG. 3 is a flow chart illustrating a method for automatic generation of business derivative metrics in accordance with another exemplary embodiment. The process 30 shown in fig. 3 is a supplementary description of the process shown in fig. 2.
As shown in fig. 3, in S302, the dimensional features of the atomic index are extracted based on the plurality of data tables. The atomic index can exist in different data tables, for example, the user identification can exist in user login information, can also exist in a transaction link, a credit granting link and the like, and different links can be used as one dimension of the user identification.
In S304, the time feature of the atomic index is extracted based on the business process data. Continuing with the above example, the time corresponding to each operation in the user identifier may be extracted based on the service flow data.
In S306, a business core index is generated based on the dimensional feature and the time feature corresponding to the business derivative index and the internal atomic index thereof. For example, the core index related to the user identifier may be a core index of user activity, and the core index may be extracted according to the dimension corresponding to the user identifier and the relationship corresponding to different operations in each dimension, so as to generate the core index.
More specifically, the operation and time of the login information link corresponding to the user identifier, the operation and time corresponding to the transaction link, and the operation and time of the credit granting link can be extracted, and the core index can be formed according to the data related to the transaction link and the login link.
In S308, when the service core indicator does not meet a preset policy, service warning information is generated. Establishing a monitoring instruction of the business derived index on a business platform to generate the business derived index at regular time; and generating the service core index at regular time according to the service derivative index.
Continuing with the above example, it may be considered that when a certain user does not perform a transaction operation for a long time and does not log on the platform for a long time, the user is determined to be a sleeping user, and service warning information for the user is generated, so that an administrator performs a user activation measure on the user. Specific user-activated measures may include assigning a coupon to the user, a telephone alert, and the like.
According to the automatic generation method of the business derived index, the single atom index of the existing business framework is utilized, the time and the dimensionality are increased, and an index system construction method of a composite derived index is assisted, so that the development trend of macroscopic overhead business can be clearer, the business core index can be concerned in real time, the data asset value and the data use efficiency are greatly improved, and the business can realize the improvement of the conversion efficiency of the key business process node.
FIG. 4 is a flow chart illustrating a method for automatic generation of business derivative metrics in accordance with another exemplary embodiment. The flow 40 shown in fig. 4 is a detailed description of S210 "generating the business derivation index automatically according to the business category, the association relationship, and the logical relationship" in the flow shown in fig. 2.
As shown in fig. 4, in S402, a target atomic index associated with a business category is determined. May for example be the traffic class a transaction class, the target source sub-indicator may for example be a transaction serial number, a transaction product, a transaction amount, etc.
In S404, other atomic indexes related to the target atomic index are extracted based on the association relationship and the logical relationship. Other atomic indicators related to the transaction serial number, the transaction product, the transaction amount, and the like are extracted according to the various associations arranged above.
In S406, the initial business derivative metrics are generated based on the target atomic metrics and the other atomic metrics. And randomly and crossly combining the transaction serial number, the transaction product, the transaction amount and other related atomic indexes to generate a plurality of initial service derivative indexes.
In S408, the plurality of initial business derivative indicators are qualified by historical business data to generate the business derivative indicators. And calculating the prediction accuracy, stability and consistency of a plurality of initial service derived indexes based on historical service data for evaluation, and selecting a plurality of service derived indexes from high to low according to the evaluation result.
Those skilled in the art will appreciate that all or part of the steps implementing the above embodiments are implemented as computer programs executed by a CPU. When executed by the CPU, performs the functions defined by the above-described methods provided by the present disclosure. The program may be stored in a computer readable storage medium, which may be a read-only memory, a magnetic or optical disk, or the like.
Furthermore, it should be noted that the above-mentioned figures are only schematic illustrations of the processes involved in the methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods. For details not disclosed in the embodiments of the apparatus of the present disclosure, refer to the embodiments of the method of the present disclosure.
Fig. 5 is a block diagram illustrating an apparatus for automatically generating business derived metrics in accordance with an exemplary embodiment. As shown in fig. 5, the automatic generation apparatus 50 for business derivation index includes: flow module 502, entity module 504, association module 506, logic module 508, and derivation module 510.
The flow module 502 is configured to generate a plurality of business flow data based on the product interaction page and the business category; the flow module 502 includes: the program unit is used for acquiring bottom program data of the product interaction page; the extraction unit is used for extracting the business interaction flow among the product interaction pages based on the underlying program data; and the flow unit is used for generating the business flow data based on the business interaction flow.
The entity module 504 is configured to establish entity contact data based on a plurality of data tables in the service database; the entity module 504 is further configured to extract entity types, attributes, and associations in the plurality of data tables; and establishing entity contact data based on the entity type, the attribute and the incidence relation.
The association module 506 is configured to establish an association relationship between the multiple data tables and the service categories based on the multiple service process data, where the data tables include an atomic index; the association module 506 includes: the relation unit is used for extracting the extraction relation between each business process data in the plurality of business process data and the data table based on the bottom program data; and the establishing unit is used for establishing the association relation among the plurality of data tables based on the plurality of business process data and the extraction relation.
The logic module 508 is configured to establish a logical relationship between the plurality of data tables based on the entity contact data;
the derivation module 510 is configured to automatically generate a business derivation indicator according to the business category, the association relationship, and the logic relationship, where the business derivation indicator is composed of at least one atomic indicator. The derivation module 510 includes: the initial unit is used for automatically generating a plurality of initial business derivative indexes according to the business category, the incidence relation and the logic relation; the initial unit is further used for determining a target atomic index related to the service class; extracting other atom indexes related to the target atom index based on the incidence relation and the logic relation; generating the initial business derivative metrics based on the target atomic metrics and the other atomic metrics. And the derivation unit is used for examining the plurality of initial business derivation indexes through historical business data so as to generate the business derivation indexes.
Fig. 6 is a block diagram illustrating an apparatus for automatically generating business derived metrics in accordance with another exemplary embodiment. As shown in fig. 6, the automatic generation apparatus 60 for business derivation index includes: a core module 602, an alert module 604, and a monitor module 606.
The core module 602 is configured to generate a service core index based on the service derivative index and the dimensional characteristic and the time characteristic corresponding to the internal atomic index thereof. The core module 602 includes: a dimension unit for extracting dimension features of the atomic index based on the plurality of data tables; the time unit is used for extracting the time characteristics of the atomic indexes based on the business process data; and the core unit is used for generating a service core index based on the service derivative index and the corresponding dimension characteristic and time characteristic of the internal atomic index.
The warning module 604 is configured to generate service warning information when the service core indicator does not meet a preset policy.
The monitoring module 606 is configured to establish a monitoring instruction of the service derivative indicator on a service platform to generate the service derivative indicator at regular time; and generating the service core index at regular time according to the service derivative index.
According to the automatic generation device of the business derived index, a plurality of business process data are generated based on the product interaction page and the business category; establishing entity contact data based on a plurality of data tables in a service database; establishing an incidence relation between the plurality of data tables and the service categories based on the plurality of service process data, wherein the data tables comprise atom indexes; establishing logical relationships between the plurality of data tables based on the entity contact data; and automatically generating service derived indexes according to the service category, the incidence relation and the logic relation, wherein the service derived indexes are composed of at least one atomic index, so that the data output efficiency can be improved, the operation analysis decision efficiency can be improved, necessary monitoring and early warning can be provided for key service processes and OKR, and the problems of data cluster resource waste and the like can be avoided.
FIG. 7 is a block diagram illustrating an electronic device in accordance with an example embodiment.
An electronic device 700 according to this embodiment of the disclosure is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 7, electronic device 700 is embodied in the form of a general purpose computing device. The components of the electronic device 700 may include, but are not limited to: at least one processing unit 710, at least one memory unit 720, a bus 730 that connects the various system components (including the memory unit 720 and the processing unit 710), a display unit 740, and the like.
Wherein the storage unit stores program code that can be executed by the processing unit 710 to cause the processing unit 710 to perform the steps according to various exemplary embodiments of the present disclosure in the present specification. For example, the processing unit 710 may perform the steps as shown in fig. 2, 3, 4.
The memory unit 720 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)7201 and/or a cache memory unit 7202, and may further include a read only memory unit (ROM) 7203.
The memory unit 720 may also include a program/utility 7204 having a set (at least one) of program modules 7205, such program modules 7205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 700 may also communicate with one or more external devices 700' (e.g., keyboard, pointing device, bluetooth device, etc.), such that a user can communicate with devices with which the electronic device 700 interacts, and/or any devices (e.g., router, modem, etc.) with which the electronic device 700 can communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 750. Also, the electronic device 700 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the internet) via the network adapter 760. The network adapter 760 may communicate with other modules of the electronic device 700 via the bus 730. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, as shown in fig. 8, the technical solution according to the embodiment of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, or a network device, etc.) to execute the above method according to the embodiment of the present disclosure.
The software product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The computer readable medium carries one or more programs which, when executed by a device, cause the computer readable medium to perform the functions of: generating a plurality of business process data based on the product interaction page and the business category; establishing entity contact data based on a plurality of data tables in a service database; establishing an incidence relation between the plurality of data tables and the service categories based on the plurality of service process data, wherein the data tables comprise atom indexes; establishing logical relationships between the plurality of data tables based on the entity contact data; and automatically generating a business derivative index according to the business category, the incidence relation and the logic relation, wherein the business derivative index is composed of at least one atomic index.
Those skilled in the art will appreciate that the modules described above may be distributed in the apparatus according to the description of the embodiments, or may be modified accordingly in one or more apparatuses unique from the embodiments. The modules of the above embodiments may be combined into one module, or further split into multiple sub-modules.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Exemplary embodiments of the present disclosure are specifically illustrated and described above. It is to be understood that the present disclosure is not limited to the precise arrangements, instrumentalities, or instrumentalities described herein; on the contrary, the disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (22)
1. A method for automatically generating a service derived index is characterized by comprising the following steps:
generating a plurality of business process data based on the product interaction page and the business category;
establishing entity contact data based on a plurality of data tables in a service database;
establishing an incidence relation between the plurality of data tables and the service categories based on the plurality of service process data, wherein the data tables comprise atom indexes;
establishing logical relationships between the plurality of data tables based on the entity contact data;
and automatically generating a business derivative index according to the business category, the incidence relation and the logic relation, wherein the business derivative index is composed of at least one atomic index.
2. The method of claim 1, comprising:
and generating a business core index based on the corresponding dimension characteristic and time characteristic of the business derivative index and the internal atomic index thereof.
3. The method of claim 2, wherein generating a business core index based on the dimensional features and the time features corresponding to the business derivative index and the internal atomic index thereof comprises:
extracting dimensional features of the atomic index based on the plurality of data tables;
extracting the time characteristics of the atomic indexes based on the business process data;
and generating a business core index based on the corresponding dimension characteristic and time characteristic of the business derivative index and the internal atomic index thereof.
4. The method of claim 2, further comprising:
and generating service warning information when the service core index does not accord with a preset strategy.
5. The method of claim 4, further comprising:
establishing a monitoring instruction of the business derived index on a business platform to generate the business derived index at regular time;
and generating the service core index at regular time according to the service derivative index.
6. The method of claim 1, wherein generating a plurality of business process data based on the product interaction page and the business category comprises:
acquiring bottom program data of a product interaction page;
extracting a business interaction process between the product interaction pages based on the bottom program data;
and generating the business process data based on the business interaction process.
7. The method of claim 1, wherein establishing entity contact data based on a plurality of data tables in a business database comprises:
extracting entity types, attributes and incidence relations in the data tables;
and establishing entity contact data based on the entity type, the attribute and the incidence relation.
8. The method of claim 1, wherein establishing associations between the plurality of data tables and business categories based on the plurality of business process data comprises:
extracting the extraction relation between each business process data in the plurality of business process data and the data table based on the bottom layer program data;
and establishing an association relation among the plurality of data tables based on the plurality of business process data and the extraction relation.
9. The method of claim 1, wherein automatically generating business derivative metrics based on business categories and the associative relationships and the logical relationships comprises:
automatically generating a plurality of initial business derivation indexes according to the business category, the incidence relation and the logic relation;
and examining the plurality of initial business derivative indexes through historical business data to generate the business derivative indexes.
10. The method of claim 9, wherein automatically generating a plurality of initial business derivative metrics based on business category and the associative relationship, the logical relationship comprises:
determining a target atomic index related to the business category;
extracting other atom indexes related to the target atom index based on the incidence relation and the logic relation;
generating the initial business derivative metrics based on the target atomic metrics and the other atomic metrics.
11. An apparatus for automatically generating a business derived index, comprising:
the flow module is used for generating a plurality of business flow data based on the product interaction page and the business category;
the entity module is used for establishing entity contact data based on a plurality of data tables in the service database;
the association module is used for establishing association relations among the plurality of data tables and the service categories based on the plurality of service process data, wherein the data tables comprise atom indexes;
a logic module for establishing a logical relationship between the plurality of data tables based on the entity contact data;
and the derivation module is used for automatically generating a business derivation index according to the business category, the incidence relation and the logic relation, wherein the business derivation index is composed of at least one atom index.
12. The automatic generation apparatus of claim 11, comprising:
and the core module is used for generating a service core index based on the service derivative index and the corresponding dimension characteristic and time characteristic of the internal atomic index.
13. The automatic generation apparatus of claim 12, the core module comprising:
a dimension unit for extracting dimension features of the atomic index based on the plurality of data tables;
the time unit is used for extracting the time characteristics of the atomic indexes based on the business process data;
and the core unit is used for generating a service core index based on the service derivative index and the corresponding dimension characteristic and time characteristic of the internal atomic index.
14. The automatic generation apparatus of claim 12, further comprising:
and the warning module is used for generating service warning information when the service core index does not accord with a preset strategy.
15. The automatic generation apparatus of claim 14, further comprising:
the monitoring module is used for establishing a monitoring instruction of the business derived index on a business platform so as to generate the business derived index at regular time; and generating the service core index at regular time according to the service derivative index.
16. The automatic generation apparatus of claim 11, wherein the flow module comprises:
the program unit is used for acquiring bottom program data of the product interaction page;
the extraction unit is used for extracting the business interaction flow among the product interaction pages based on the underlying program data;
and the flow unit is used for generating the business flow data based on the business interaction flow.
17. The automatic generation apparatus of claim 11, wherein the entity module is further configured to generate the entity data based on the entity data
Extracting entity types, attributes and incidence relations in the data tables; and establishing entity contact data based on the entity type, the attribute and the incidence relation.
18. The automatic generation apparatus of claim 11, wherein the association module comprises:
the relation unit is used for extracting the extraction relation between each business process data in the plurality of business process data and the data table based on the bottom program data;
and the establishing unit is used for establishing the association relation among the plurality of data tables based on the plurality of business process data and the extraction relation.
19. The automatic generation apparatus of claim 11, wherein the derivation module comprises:
the initial unit is used for automatically generating a plurality of initial business derivative indexes according to the business category, the incidence relation and the logic relation;
and the derivation unit is used for examining the plurality of initial business derivation indexes through historical business data so as to generate the business derivation indexes.
20. The automatic generation apparatus of claim 19, wherein the initialization unit is further configured to
Determining a target atomic index related to the business category; extracting other atom indexes related to the target atom index based on the incidence relation and the logic relation; generating the initial business derivative metrics based on the target atomic metrics and the other atomic metrics.
21. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-10.
22. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-10.
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