CN113298354B - Automatic generation method and device of service derivative index and electronic equipment - Google Patents
Automatic generation method and device of service derivative index and electronic equipment Download PDFInfo
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- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
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Abstract
The disclosure relates to an automatic generation method, an automatic generation device, an electronic device and a computer readable medium of a service derivative index. 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 association relationship between the plurality of data tables and service categories based on the plurality of service flow data, wherein the data tables contain atomic indexes; establishing a logical relationship between the plurality of data tables based on the entity contact data; and automatically generating a service derivative index according to the service category, the association relation and the logic relation, wherein the service derivative index consists of at least one atomic index. The method, the device, the electronic equipment and the computer readable medium for automatically generating the service derivative index can improve the efficiency of data output and improve the operation analysis decision-making efficiency.
Description
Technical Field
The present disclosure relates to the field of computer information processing, and in particular, to a method, an apparatus, an electronic device, and a computer readable medium for automatically generating a service derivative indicator.
Background
The data analysis index system is used for constructing a group of data indexes related to the business problems or decision targets around the business problems or decision targets on the basis of the recognized unified data indexes, analyzing the inherent structure and relevance of the group of indexes, and applying the data analysis index system to problem analysis or target decision directly or by constructing an analysis model.
A large number of business-related data tables are stored in a business 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, aggregation fields, order quantity, user quantity, pv, uv and the like in the tables. The atomic index is relatively single and cannot provide complete business analysis capability, which results in low efficiency, effectiveness and benefit of business analysis. The limitation of adding, subtracting, multiplying and dividing or modifying words on the atomic index can be called as a derivative index, and the derivative index can reflect more information, so that service analysts often need to generate the derivative index based on the atomic index to construct a data analysis index system. However, the derivative indexes are basically generated by combining a plurality of atomic indexes according to the experience accumulation of an analyst, the generation efficiency of the derivative indexes is low, and whether the derivative indexes are optimal atomic index combinations is unknown.
Therefore, there is a need for a new method, apparatus, electronic device, and computer-readable medium for automatically generating a service derivative indicator.
The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the 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 a method, an apparatus, an electronic device, and a computer readable medium for automatically generating a service derived index, which can improve the efficiency of data output, improve the efficiency of operation analysis decision, provide necessary monitoring and early warning for key service flows and OKR, and avoid the problems of wasting data cluster resources, etc.
Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.
According to an aspect of the present disclosure, an automatic generation method of a service derivative indicator is provided, 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 association relationship between the plurality of data tables and service categories based on the plurality of service flow data, wherein the data tables contain atomic indexes; establishing a logical relationship between the plurality of data tables based on the entity contact data; and automatically generating a service derivative index according to the service category, the association relation and the logic relation, wherein the service derivative index consists of at least one atomic index.
Optionally, the method comprises: and generating a service core index based on the dimension characteristics and the time characteristics corresponding to the service derivative index and the internal atomic index.
Optionally, generating a service core index based on the dimension feature and the time feature corresponding to the service derivative index and the internal atomic index thereof includes: extracting dimension characteristics of the atomic indexes based on the plurality of data tables; extracting the time characteristics of the atomic indexes based on the business process data; and generating a service core index based on the dimension characteristics and the time characteristics corresponding to the service derivative index and the internal atomic index.
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 service derivative index on a service platform to generate the service derivative index at fixed 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 business interaction flows between the product interaction pages based on the bottom program data; and generating the business process data based on the business interaction process.
Optionally, establishing entity contact data based on a plurality of data tables in the service database includes: extracting entity types, attributes and association relations in the plurality of data tables; and establishing entity contact data based on the entity type, the attribute and the association relation.
Optionally, establishing an association relationship between the plurality of data tables and the service class based on the plurality of service flow data includes: extracting an extraction relation of each business process data neutralization data table in the plurality of business process data based on the bottom program data; and establishing an association relationship between the plurality of data tables based on the plurality of business process data and the extraction relationship.
Optionally, automatically generating a service derivative indicator according to the service category, the association relation and the logic relation, including: automatically generating a plurality of initial service derivative indexes according to the service category, the association relation and the logic relation; and checking the plurality of initial service derivative indexes through historical service data to generate the service derivative indexes.
Optionally, automatically generating a plurality of initial service derivative indexes according to the service category, the association relation and the logic relation, including: determining target atomic indexes related to service types; extracting other atomic indexes related to the target atomic indexes based on the association relation and the logic relation; generating the initial traffic derived index based on the target atomic index and the other atomic index.
According to an aspect of the present disclosure, an apparatus for automatically generating a service derivative indicator 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 between the plurality of data tables and the business categories based on the plurality of business process data, wherein the data tables contain atomic indexes; the logic module is used for establishing a logic relation among the plurality of data tables based on the entity contact data; and the deriving module is used for automatically generating a service deriving index according to the service category, the association relation and the logic relation, wherein the service deriving index consists of at least one atomic index.
Optionally, the method comprises: and the core module is used for generating a service core index based on the dimension characteristics and the time characteristics corresponding to the service derivative index and the internal atomic index.
Optionally, the core module includes: a dimension unit, configured to extract dimension features of the atomic indicators 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 dimension characteristics and the time characteristics corresponding to the service derivative index and 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 service derivative index on the service platform so as to generate the service derivative index at fixed 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 the bottom program data of the product interaction page; the extraction unit is used for extracting business interaction flows between the product interaction pages based on the bottom 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 multiple data tables; and establishing entity contact data based on the entity type, the attribute and the association relation.
Optionally, the association module includes: a relationship unit, configured to extract an extraction relationship of the neutralization data table in each business process data in the plurality of business process data based on the underlying 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 deriving module is further configured to automatically generate a plurality of initial service derivative indexes according to the service class, the association relationship and the logical relationship; and the deriving unit is used for checking the plurality of initial service deriving indexes through historical service data to generate the service deriving indexes.
Optionally, the initial unit is further configured to determine a target atomic indicator related to the service class; extracting other atomic indexes related to the target atomic indexes based on the association relation and the logic relation; generating the initial traffic derived index based on the target atomic index and the other atomic index.
According to an aspect of the present disclosure, there is provided an electronic device including: one or more processors; a storage means for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the methods as described above.
According to an aspect of the present disclosure, a computer-readable medium is presented, on which a computer program is stored, which program, when being executed by a processor, implements a method as described above.
According to the automatic generation method, the device, the electronic equipment and the computer readable medium of the service derivative index, a plurality of service flow data are generated based on the product interaction page and the service category; establishing entity contact data based on a plurality of data tables in a service database; establishing an association relationship between the plurality of data tables and service categories based on the plurality of service flow data, wherein the data tables contain atomic indexes; establishing a logical relationship between the plurality of data tables based on the entity contact data; according to the business category, the association relation and the logic relation, business derivative indexes are automatically generated, and the business derivative indexes are formed by at least one atomic index, so that the data output efficiency can be improved, the business analysis decision-making efficiency can be improved, necessary monitoring and early warning can be provided for key business processes and OKR, and the problems of waste of data cluster resources and the like are 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 examples of the present disclosure and other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
Fig. 1 is a system block diagram illustrating a method and apparatus for automatically generating a traffic derived index according to an exemplary embodiment.
Fig. 2 is a flow chart illustrating a method of automatically generating traffic derived metrics according to an exemplary embodiment.
Fig. 3 is a flow chart illustrating a method of automatically generating traffic derived metrics according to another exemplary embodiment.
Fig. 4 is a flow chart illustrating a method of automatically generating traffic derived metrics according to another exemplary embodiment.
Fig. 5 is a block diagram illustrating an apparatus for automatically generating traffic derived metrics according to an exemplary embodiment.
Fig. 6 is a block diagram illustrating an apparatus for automatically generating traffic derived metrics according to another exemplary embodiment.
Fig. 7 is a block diagram of an electronic device, according to an example embodiment.
Fig. 8 is a block diagram of a computer-readable medium shown according to an example embodiment.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many 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 the example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, 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 disclosed aspects may be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they 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 order of actual execution may be changed according to actual situations.
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 element. Accordingly, a first component discussed below could be termed a second component without departing from the teachings of the concepts of the present disclosure. As used herein, the term "and/or" includes any one of the associated listed items and all combinations of one or more.
Those skilled in the art will appreciate that the drawings are schematic representations of example embodiments and that the modules or flows in the drawings are not necessarily required to practice the present disclosure, and therefore, should not be taken to limit the scope of the present disclosure.
Fig. 1 is a system block diagram illustrating a method and apparatus for automatically generating a traffic derived index according to an exemplary embodiment.
As shown in fig. 1, the system architecture 10 may include traffic databases 101, 102, 103, a network 104, and a server 105. The network 104 is the medium used to provide the communication links between the traffic databases 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The service related data may be stored by the overuse service databases 101, 102, 103, more specifically, different service databases may store data of different service categories. The business databases 101, 102, 103 may be a variety of electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server providing data analysis of data in the business databases 101, 102, 103. The background management server can analyze the business data and the like, and extract the business derivative index to feed back to an administrator of the financial service website.
Server 105 may 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; server 105 may, for example, establish an association between the plurality of data tables and the business category based on the plurality of business process data, wherein the data tables include an atomic indicator; server 105 may establish a logical relationship between the plurality of data tables, for example, based on the entity contact data; the server 105 may automatically generate a service derivative indicator, e.g. from the service class and the association, the logical relationship, the service derivative indicator being composed of at least one atomic indicator.
The server 105 may also generate a service core index based on, for example, the dimension characteristics, time characteristics corresponding to the service derivative index and its internal atomic index.
The server 105 may also generate service alert information, for example, when the service core indicator does not meet a preset policy.
The server 105 may be an entity server, or may be a plurality of servers, for example, it should be noted that the method for automatically generating the service derivative indicator provided in the embodiment of the present disclosure may be executed by the server 105, and accordingly, the device for automatically generating the service derivative indicator may be set in the server 105.
Fig. 2 is a flow chart illustrating a method of automatically generating traffic derived metrics according to an exemplary embodiment. The method 20 for automatically generating the service derivative indicator at least includes steps S202 to S210.
As shown in fig. 2, in S202, a plurality of business process data is generated based on a product interaction page and a business category. The underlying program data of the product interaction page may be obtained, for example; extracting business interaction flows between the product interaction pages based on the bottom program data; and generating the business process data based on the business interaction process.
In this disclosure, a specific technical description may be given for a platform that provides a financial network service as an example, and it can be known that the method in this disclosure may also be applied to network platforms in other fields.
In a financial network service platform, the product may be a resource-like product, and in this disclosure, a resource refers to any substance, information, time that may be utilized, and information resources include computing resources and various types of data resources. The data resources include various dedicated data in various fields. However, for convenience, the present invention is described with respect to financial data resources, but those skilled in the art will appreciate that the present invention may be used for allocation of other resources.
The user can register, trust and log in on the product interaction page, and the operations of risk assessment, third party risk assessment, resource allocation, resource return and the like are performed. The interactive page can also comprise a promotion display page, a third party transaction page, an administrator operation page and the like. The product interaction page can be divided into a user class interaction page, a transaction class interaction page, a log class interaction page, a marketing class interaction page and the like according to business categories.
Extracting bottom program data according to the categories of different product interaction pages, analyzing the bottom program data to extract business logic among the product interaction pages, and further generating business flow data.
In S204, entity contact data is established based on a plurality of data tables in the business database. Entity types, attributes and associations in the plurality of data tables may be extracted, for example; and establishing entity contact data based on the entity type, the attribute and the association relation.
The entity type in the data table can be used as the identification of the atomic index, and specifically can be user identification, order category, order quantity, user quantity, pv, uv and the like. The attribute may be a data attribute of the atomic indicator, and the association relationship may be an association relationship between a plurality of data tables based on the identification of the atomic indicator. If the user identification exists among the plurality of data tables, the plurality of data tables containing the user identification may be considered to be associated.
The things which can be objectively distinguished from each other can be considered as entities, and the entities can be specific people and things or abstract concepts and relations. The key is that one entity can be distinguished from another entity, with entities having the same attributes having the same features and properties. Entity names and their collection of attribute names are used to abstract and characterize similar entities.
Attributes, an entity has a certain property, and an entity can be characterized by several attributes. Attributes cannot deviate from an entity, attributes are relative to an entity. Represented by ovals in the E-R diagram and connected to the corresponding entity by undirected edges; such as student name, number, gender, and all attributes. If the multi-value attribute is adopted, a solid ellipse is sleeved outside the ellipse. And if the attribute is derived, the attribute is represented by a dotted oval.
Contacts, also called relationships, reflect associations within or between entities in the information world. Contacts within an entity generally refer to contacts between the various attributes that make up the entity; contacts between entities generally refer to contacts between different sets of entities.
In S206, an association relationship between the plurality of data tables and the business category is established based on the plurality of business process data, where the data tables include an atomic indicator. Comprising the following steps: extracting an extraction relation of each business process data neutralization data table in the plurality of business process data based on the bottom program data; and establishing an association relationship between the plurality of data tables based on the plurality of business process data and the extraction relationship.
More specifically, the read or write relationships for each data table in the business process may be extracted based on the underlying program data, table entry modifications for each data table in the business process may be extracted, and so on.
In S208, a logical relationship between the plurality of data tables is established based on the entity contact data. As described above, the association relationship may be an association relationship between the plurality of data tables based on the identification of the atomic indicator. If the user identification exists among the plurality of data tables, the plurality of data tables containing the user identification may be considered to be associated. And converting the association relation into a logic relation based on the entity contact data.
In S210, a service derivative indicator is automatically generated according to the service category, the association relationship and the logic relationship, where the service derivative indicator is composed of at least one atomic indicator. Comprising the following steps: automatically generating a plurality of initial service derivative indexes according to the service category, the association relation and the logic relation; and checking the plurality of initial service derivative indexes through historical service data to generate the service derivative indexes.
Details of "automatically generating a service derivative indicator according to the service class and the association relationship, and the logical relationship" will be described in the corresponding embodiment of fig. 4.
According to the automatic generation method of the service derivative index, a plurality of service flow data are generated based on the product interaction page and the service class; establishing entity contact data based on a plurality of data tables in a service database; establishing an association relationship between the plurality of data tables and service categories based on the plurality of service flow data, wherein the data tables contain atomic indexes; establishing a logical relationship between the plurality of data tables based on the entity contact data; according to the business category, the association relation and the logic relation, business derivative indexes are automatically generated, and the business derivative indexes are formed by at least one atomic index, so that the data output efficiency can be improved, the business analysis decision-making efficiency can be improved, necessary monitoring and early warning can be provided for key business processes and OKR, and the problems of waste of data cluster resources and the like are 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 of automatically generating traffic derived metrics according to another exemplary embodiment. The flow 30 shown in fig. 3 is a complementary description of the flow shown in fig. 2.
As shown in fig. 3, in S302, dimensional features of the atomic indicators are extracted based on the plurality of data tables. The atomic index may exist in different data tables, for example, the user identifier may exist in the user login information, may also exist in the transaction link, the trust link exists, and the like, and different links may be used as one dimension of the user identifier.
In S304, a temporal feature of the atomic indicator is extracted based on the business process data. Continuing with the above example, a time corresponding to each operation in the user identification may be extracted based on the business process data.
In S306, a service core index is generated based on the dimension feature and the time feature corresponding to the service derivative index and the internal atomic index. For example, the core index related to the user identifier may be a user liveness core index, and the core index may be generated by extracting the dimension corresponding to the user identifier and the corresponding relation of different operations in each dimension.
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, the operation and time of the credit giving link, and the time of the credit giving 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 index does not conform to a preset policy, service warning information is generated. Establishing a monitoring instruction of the service derivative index on a service platform to generate the service derivative index at fixed time; and generating the service core index at regular time according to the service derivative index.
Continuing the above example, it may be considered that when a user does not conduct 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 a manager conducts user activation measures on the user. Specific user activation measures may include assigning coupons, phone reminders, and the like to the user.
According to the automatic generation method of the service derivative index, the single primitive index of the existing service framework is utilized, the time and the dimension are increased, and the index system construction method of the composite derivative index is assisted, so that the macroscopic overlooking service development trend can be more clear, the service core index is focused in real time, the data asset value and the data use efficiency are greatly improved, and the service is further enabled to achieve the improvement of the conversion efficiency of the key service flow node.
Fig. 4 is a flow chart illustrating a method of automatically generating traffic derived metrics according to another exemplary embodiment. The process 40 shown in fig. 4 is a detailed description of "automatically generating a service derivative indicator according to the service class and the association relationship and the logical relationship" in the process S210 shown in fig. 2.
As shown in fig. 4, in S402, a target atomic index related to a traffic class is determined. The business category may be, for example, a transaction category, and the target source sub-index may be, for example, a transaction serial number, a transaction product, a transaction amount, and the like.
In S404, other atomic indicators related to the target atomic indicator are extracted based on the association relationship and the logical relationship. According to the various associations arranged above, other atomic indicators related to transaction serial numbers, transaction products, transaction amounts and the like are extracted.
In S406, the initial traffic derived index is generated based on the target atomic index and the other atomic index. And carrying out random cross combination on 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 traffic derivative indicators are examined by historical traffic data to generate the traffic derivative indicator. And calculating the prediction accuracy, stability and consistency of a plurality of initial service derivative indexes based on the historical service data, evaluating, and selecting a plurality of service derivative 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 described embodiments are implemented as a computer program executed by a CPU. The above-described functions defined by the above-described methods provided by the present disclosure are performed when the computer program is executed by a CPU. The program may be stored in a computer readable storage medium, which may be a read-only memory, a magnetic disk or an optical disk, etc.
Furthermore, it should be noted that the above-described figures are merely illustrative of the processes involved in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.
The following are device embodiments of the present disclosure that may be used to perform method embodiments of the present disclosure. For details not disclosed in the embodiments of the apparatus of the present disclosure, please refer to the embodiments of the method of the present disclosure.
Fig. 5 is a block diagram illustrating an apparatus for automatically generating traffic derived metrics according to an exemplary embodiment. As shown in fig. 5, the automatic generation device 50 of the service derivative index includes: flow module 502, entity module 504, association module 506, logic module 508, derivatization module 510.
The process module 502 is configured to generate a plurality of business process data based on the product interaction page and the business category; the flow module 502 includes: the program unit is used for acquiring the bottom program data of the product interaction page; the extraction unit is used for extracting business interaction flows between the product interaction pages based on the bottom 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 association relationships in the plurality of data tables; and establishing entity contact data based on the entity type, the attribute and the association relation.
The association module 506 is configured to establish an association relationship between the plurality of data tables and the service class based on the plurality of service flow data, where the data tables include an atomic index; the association module 506 includes: a relationship unit, configured to extract an extraction relationship of the neutralization data table in each business process data in the plurality of business process data based on the underlying 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 logic relationship between the plurality of data tables based on the entity contact data;
the deriving module 510 is configured to automatically generate a service derived indicator according to the service category, the association relationship, and the logical relationship, where the service derived indicator is composed of at least one atomic indicator. The deriving module 510 includes: the initial unit is used for automatically generating a plurality of initial service derivative indexes according to the service category, the association relation and the logic relation; the initial unit is further used for determining target atomic indexes related to the business category; extracting other atomic indexes related to the target atomic indexes based on the association relation and the logic relation; generating the initial traffic derived index based on the target atomic index and the other atomic index. And the deriving unit is used for checking the plurality of initial service deriving indexes through historical service data to generate the service deriving indexes.
Fig. 6 is a block diagram illustrating an apparatus for automatically generating traffic derived metrics according to another exemplary embodiment. As shown in fig. 6, the automatic generation device 60 of the service derivative indicator includes: the system comprises a core module 602, a warning module 604 and a monitoring module 606.
The core module 602 is configured to generate a service core index based on the service derivative index and the dimension feature and the time feature corresponding to the internal atomic index. The core module 602 includes: a dimension unit, configured to extract dimension features of the atomic indicators 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 dimension characteristics and the time characteristics corresponding to the service derivative index and the internal atomic index.
The warning module 604 is configured to generate service warning information when the service core indicator does not conform to a preset policy.
The monitoring module 606 is configured to establish a monitoring instruction of the service derivative indicator on the service platform to generate the service derivative indicator at a timing; and generating the service core index at regular time according to the service derivative index.
According to the automatic generation device of the service derivative index, a plurality of service flow data are generated based on the product interaction page and the service class; establishing entity contact data based on a plurality of data tables in a service database; establishing an association relationship between the plurality of data tables and service categories based on the plurality of service flow data, wherein the data tables contain atomic indexes; establishing a logical relationship between the plurality of data tables based on the entity contact data; according to the business category, the association relation and the logic relation, business derivative indexes are automatically generated, and the business derivative indexes are formed by at least one atomic index, so that the data output efficiency can be improved, the business analysis decision-making efficiency can be improved, necessary monitoring and early warning can be provided for key business processes and OKR, and the problems of waste of data cluster resources and the like are avoided.
Fig. 7 is a block diagram of an electronic device, according to an example embodiment.
An electronic device 700 according to such an embodiment of the present disclosure is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is merely an example and should not be construed to limit the functionality and scope of use of embodiments of the present disclosure in any way.
As shown in fig. 7, the electronic device 700 is embodied in the form of a general purpose computing device. Components of 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 connecting the different 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 executable by the processing unit 710 such that the processing unit 710 performs steps in the present specification according to various exemplary embodiments of the present disclosure. For example, the processing unit 710 may perform the steps as shown in fig. 2, 3, and 4.
The memory unit 720 may include readable media in the form of volatile memory units, such as Random Access Memory (RAM) 7201 and/or cache memory 7202, and may further include Read Only Memory (ROM) 7203.
The storage 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 or some combination of which may include an implementation of a network environment.
Bus 730 may be a bus representing one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 700 may also communicate with one or more external devices 700' (e.g., keyboard, pointing device, bluetooth device, etc.), devices that enable a user to interact with the electronic device 700, and/or any devices (e.g., routers, modems, etc.) with which the electronic device 700 can communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 750. Also, electronic device 700 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through network adapter 760. Network adapter 760 may communicate with other modules of electronic device 700 via bus 730. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 700, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, as shown in fig. 8, 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 (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, or a network device, etc.) to perform the above-described method according to the embodiments 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. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk 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 data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable storage medium may also be any readable medium 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 of 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, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, 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., connected via the Internet using an Internet service provider).
The computer-readable medium carries one or more programs, which when executed by one of the devices, 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 association relationship between the plurality of data tables and service categories based on the plurality of service flow data, wherein the data tables contain atomic indexes; establishing a logical relationship between the plurality of data tables based on the entity contact data; and automatically generating a service derivative index according to the service category, the association relation and the logic relation, wherein the service derivative index consists of at least one atomic index.
Those skilled in the art will appreciate that the modules may be distributed throughout several devices as described in the embodiments, and that corresponding variations may be implemented in one or more devices that are unique to the embodiments. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or in combination with the necessary hardware. Thus, the technical solutions 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 (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and include several instructions to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform 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 this disclosure is not limited to the particular arrangements, instrumentalities and methods of implementation 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 (14)
1. An automatic generation method of service derivative indexes is characterized by comprising the following steps:
acquiring bottom program data of a product interaction page;
extracting business interaction flows between product interaction pages based on the bottom program data;
generating business process data based on the business interaction process;
establishing entity contact data based on a plurality of data tables in a service database;
extracting an extraction relation between each business process data in the plurality of business process data and the data table based on the bottom program data;
establishing an association relationship among a plurality of data tables based on the plurality of business process data and the extraction relationship, wherein the data tables contain atomic indexes, and the association relationship is the association relationship among the plurality of data tables based on the identification of the atomic indexes;
establishing a logical relationship between the plurality of data tables based on the entity contact data;
Automatically generating a service derivative index according to the service category, the association relation and the logic relation, wherein the service derivative index consists of at least one atomic index;
generating a service core index based on the dimension characteristics and the time characteristics corresponding to the service derivative index and the internal atomic index thereof;
and generating service warning information when the service core index does not accord with a preset strategy.
2. The method of claim 1, wherein generating a business core index based on the dimension features, time features, corresponding to the business derived index and its internal atomic index, comprises:
extracting dimension characteristics of the atomic indexes based on the plurality of data tables;
extracting the time characteristics of the atomic indexes based on the business process data;
and generating a service core index based on the dimension characteristics and the time characteristics corresponding to the service derivative index and the internal atomic index.
3. The method as recited in claim 1, further comprising:
establishing a monitoring instruction of the service derivative index on a service platform to generate the service derivative index at fixed time;
and generating the service core index at regular time according to the service derivative index.
4. 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 association relations in the plurality of data tables;
and establishing entity contact data based on the entity type, the attribute and the association relation.
5. The method of claim 1, wherein automatically generating a traffic derived indicator from a traffic class and the association relationship, the logical relationship, comprises:
automatically generating a plurality of initial service derivative indexes according to the service category, the association relation and the logic relation;
and checking the plurality of initial service derivative indexes through historical service data to generate the service derivative indexes.
6. The method of claim 5, wherein automatically generating a plurality of initial traffic-derived metrics from traffic categories and the association relationships, the logical relationships, comprises:
determining target atomic indexes related to service types;
extracting other atomic indexes related to the target atomic indexes based on the association relation and the logic relation;
generating the initial traffic derived index based on the target atomic index and the other atomic index.
7. An automatic generation device for service derivative indexes, comprising:
the flow module is used for acquiring the bottom program data of the product interaction page; extracting business interaction flows between product interaction pages based on the bottom program data; generating business process data based on the business interaction process;
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 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; establishing an association relationship among a plurality of data tables based on the plurality of business process data and the extraction relationship, wherein the data tables contain atomic indexes, and the association relationship is the association relationship among the plurality of data tables based on the identification of the atomic indexes;
the logic module is used for establishing a logic relation among the plurality of data tables based on the entity contact data;
the deriving module is used for automatically generating a service deriving index according to the service category, the association relation and the logic relation, wherein the service deriving index consists of at least one atomic index;
the core module is used for generating a service core index based on the dimension characteristics and the time characteristics corresponding to the service derivative index and the internal atomic index thereof;
And the warning module is used for generating service warning information when the service core index does not accord with a preset strategy.
8. The automatic generation apparatus of claim 7, wherein the core module comprises:
a dimension unit, configured to extract dimension features of the atomic indicators 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 dimension characteristics and the time characteristics corresponding to the service derivative index and the internal atomic index.
9. The automatic generation apparatus of claim 7, further comprising:
the monitoring module is used for establishing a monitoring instruction of the service derivative index on the service platform so as to generate the service derivative index at fixed time; and generating the service core index at regular time according to the service derivative index.
10. The automated generation apparatus of claim 7, wherein the entity module is further to
Extracting entity types, attributes and association relations in the plurality of data tables; and establishing entity contact data based on the entity type, the attribute and the association relation.
11. The automatic generation apparatus of claim 7, wherein the derivation module comprises:
the initial unit is used for automatically generating a plurality of initial service derivative indexes according to the service category, the association relation and the logic relation;
and the deriving unit is used for checking the plurality of initial service deriving indexes through historical service data to generate the service deriving indexes.
12. The automatic generation apparatus of claim 11, wherein the initialization unit is further configured to
Determining target atomic indexes related to service types; extracting other atomic indexes related to the target atomic indexes based on the association relation and the logic relation; generating the initial traffic derived index based on the target atomic index and the other atomic index.
13. An electronic device, comprising:
one or more processors;
a storage means for storing one or more programs;
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-6.
14. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-6.
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