CN113837593B

CN113837593B - Virtual data distribution method, device, equipment and storage medium

Info

Publication number: CN113837593B
Application number: CN202111101771.6A
Authority: CN
Inventors: 屈静
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2021-09-18
Filing date: 2021-09-18
Publication date: 2023-08-15
Anticipated expiration: 2041-09-18
Also published as: CN113837593A

Abstract

The disclosure provides a virtual data distribution method, device, equipment and storage medium, relates to the technical field of computers, and particularly relates to the fields of Internet application, data structures and the like. The specific implementation scheme is as follows: obtaining a virtual data distribution application, wherein the virtual data distribution application comprises organization members applying for virtual data; determining a class corresponding to the organization member based on a pre-constructed class hierarchy; determining a target data volume corresponding to the category based on a pre-constructed data volume model; virtual data is allocated based on the target data amount. The virtual data service efficiency is improved.

Description

Virtual data distribution method, device, equipment and storage medium

Technical Field

The disclosure relates to the technical field of computers, in particular to the fields of internet application, data structures and the like, and specifically relates to a virtual data distribution method, device, equipment and storage medium.

Background

With the development of multimedia technology and the like, the application of virtual data is becoming wider and wider, and becomes an important means in the processes of operation, sales and the like. Virtual data, such as virtual currency, is beneficial to stimulating user consumption, increasing flow, improving platform user viscosity, etc., and there are many scenarios where virtual data distribution is actually needed, such as promotion of new products, internal personnel testing, reimbursement, compensation, various marketing campaigns, etc.

Disclosure of Invention

The disclosure provides a virtual data distribution method, device, equipment and storage medium.

According to a first aspect of the present disclosure, there is provided a virtual data allocation method, including:

obtaining a virtual data distribution application, wherein the virtual data distribution application comprises organization members applying for virtual data;

determining a category corresponding to the organization member based on a pre-constructed category hierarchy;

determining a target data volume corresponding to the category based on a pre-constructed data volume model, wherein the target data volume is used for representing the data volume to be distributed of virtual data distribution;

virtual data is allocated based on the data volume.

According to a second aspect of the present disclosure, there is provided a virtual data distribution apparatus comprising:

the virtual data distribution system comprises an acquisition module, a data distribution module and a data distribution module, wherein the acquisition module is used for acquiring a virtual data distribution application, and the virtual data distribution application comprises organization members for applying for virtual data;

the determining module is used for determining the category corresponding to the organization member based on a pre-constructed category hierarchy; determining a target data volume corresponding to the category based on a pre-constructed data volume model, wherein the target data volume is used for representing the data volume to be distributed of virtual data distribution;

And the allocation module is used for allocating virtual data based on the target data volume.

According to a third aspect of the present disclosure, there is provided an electronic device comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect.

According to a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method according to the first aspect.

According to a fifth aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method according to the first aspect.

The virtual data distribution method and the virtual data distribution device based on the data volume model can reasonably distribute virtual data by utilizing the data volume.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.

Drawings

The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a flow chart of a virtual data allocation method provided by an embodiment of the present disclosure;

FIG. 2 is a flow chart of determining a target data amount based on a data amount model in an embodiment of the present disclosure;

FIG. 3 is a flow diagram of virtual data allocation in an embodiment of the present disclosure;

FIG. 4 is a schematic flow chart of establishing a data volume model in an embodiment of the present disclosure;

FIG. 5 is a schematic diagram of structural information in an embodiment of the present disclosure;

FIG. 6 is a schematic diagram of a class hierarchy in an embodiment of the present disclosure;

FIG. 7 is a schematic diagram of a storage structure storing node information in a class hierarchy in an embodiment of the present disclosure;

FIG. 8 is a schematic diagram of a storage structure storing organization member information in an embodiment of the present disclosure;

FIG. 9 is a schematic diagram of a data volume model in an embodiment of the present disclosure;

FIG. 10 is an example diagram of a category hierarchy architecture in an embodiment of the present disclosure;

FIG. 11 is an exemplary diagram of a data volume model built based on the category hierarchy shown in FIG. 10;

FIG. 12 is a schematic diagram of a storage structure storing attribute information in an embodiment of the present disclosure;

FIG. 13 is a schematic diagram of querying available data amounts based on a pre-created data amount model in an embodiment of the present disclosure;

FIG. 14 is a flow chart of virtual data allocation based on a data volume model in an embodiment of the present disclosure;

FIG. 15 is another flow chart of virtual data allocation based on a data volume model in an embodiment of the present disclosure;

FIG. 16 is a schematic diagram of a state transition in an embodiment of the present disclosure;

FIG. 17 is another schematic diagram of a state transition in an embodiment of the present disclosure;

FIG. 18 is a schematic diagram of a configuration of a virtual data distribution apparatus according to an embodiment of the present disclosure;

FIG. 19 is a schematic diagram of another configuration of a virtual data distribution apparatus according to an embodiment of the present disclosure;

FIG. 20 is a schematic diagram of a virtual data distribution apparatus according to an embodiment of the present disclosure;

FIG. 21 is a schematic diagram of a virtual data distribution apparatus according to an embodiment of the present disclosure;

fig. 22 is a block diagram of an electronic device used to implement the virtual data allocation method of an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

The virtual data distribution system can provide important functions such as virtual data distribution, user activation binding, reserved product consumption, product deduction according to needs, transaction details and the like, is beneficial to stimulating user consumption, increasing flow, improving platform user viscosity, and is an important preferential means in the processes of sales, operation and the like.

However, related cloud virtual data distribution has the conditions of abusing, misuse and resource waste, and the functions and the usage of the current virtual data ports are confusing. The related virtual data distribution has the conditions of abusing, abusing and wasting resources, and has the following points in detail:

virtual data allocation: the organization personnel with allocation rights have a large number, and the problem of irregular allocation and the problem of allocation rights management caused by the variation of the organization personnel exist.

Virtual data usage scenarios: the scenes of virtual data distribution in actual need are numerous, such as popularization of new products, testing of internal personnel, paying, compensation, various marketing activities and the like, and the purposes and channels of virtual data are required to be more refined, so that the requirements of clients on preferential requirements are met, the marketing resources can be accurately mastered, and the abuse problem is avoided.

Virtual data, which is a computational cost, is too generalized to be applied to unrelated scenarios, and thus cannot achieve its original allocation objective, such as a coupon that would otherwise be required to be applied to a 1-core 1G virtual machine service, and is instead applied to a graphics processor (Graphics Processing Unit, GPU) type virtual machine, resulting in cost loss.

The embodiment of the disclosure can realize closed-loop virtual data distribution, intelligently manage investment of virtual data cost, greatly improve virtual data use efficiency, and simultaneously excite the virtual data to stimulate user consumption, increase stream and improve the value of platform user viscosity.

The embodiment of the disclosure further refines the application of the virtual data, sets different data amount for the virtual data of different applications, constructs a data amount model to perform cost allocation management and control of a full-flow closed loop, and supports dynamically adjusting a category architecture tree model; supporting the dynamic adjustment of the data quantity model according to marketing strategies, market demands of products and market data feedback; the investment of the cost of the intelligent management virtual data can be helped, the use efficiency of the virtual data is improved greatly, and the value of the virtual data is stimulated; finally, the management of virtual data loss is realized.

The virtual data allocation method provided by the embodiment of the present disclosure is described in detail below.

The virtual data distribution method provided by the embodiment of the disclosure can be applied to electronic equipment, and in particular, the electronic equipment can comprise a server, a terminal and the like.

The embodiment of the disclosure provides a virtual data distribution method, which can include:

determining a class corresponding to the organization member based on a pre-constructed class hierarchy;

determining a target data volume corresponding to the category based on a pre-constructed data volume model, wherein the target data volume is used for representing the data volume to be distributed for virtual data distribution;

virtual data is allocated based on the target data amount.

In the embodiment of the disclosure, the data quantity is reasonably utilized to distribute the virtual data based on the data quantity model, so that the resource waste is reduced, and the use efficiency of the virtual data is improved.

Fig. 1 is a flowchart of a virtual data allocation method according to an embodiment of the present disclosure. As shown in fig. 1, the virtual data allocation method provided by the embodiment of the present disclosure may include:

s101, obtaining a virtual data distribution application.

The virtual data allocation application includes an organization member applying for virtual data.

The organization members applying for virtual data, i.e. the virtual data applicant, may send the virtual data allocation application in a customer relationship management system (CRM) of the service provider console, so that the electronic device may receive the virtual data allocation application through the CRM system.

The virtual data may include credit values, points, virtual currency such as vouchers, and the like.

S102, determining the class corresponding to the organization member based on a pre-constructed class hierarchy.

The category hierarchy may include a relationship to which a plurality of categories belong.

Categories may be divided by department, project, business, etc.

In one implementation, a class hierarchy may be pre-built, the class hierarchy including a plurality of nodes. One node in the class team hierarchy corresponds to one class, and each node may have attribute information. For example, the attribute information may include organization members included in a category to which the node corresponds. Thus, after obtaining an organization member, the category hierarchy is queried to determine the category corresponding to the organization structure.

S103, determining the target data volume corresponding to the category based on a pre-constructed data volume model.

The target data amount is used to represent the amount of data to be allocated for virtual data allocation.

In one implementation, as shown in fig. 2, S103 may include:

s201, based on the data quantity model, available data quantity corresponding to the category is obtained.

Specifically, searching a data volume model, determining corresponding data volume nodes in a data volume model department, searching parent nodes of the data volume nodes according to the sequence of searching from bottom to top, and the like until a root node of the data volume model is found.

The data volume of all the data volume nodes on the path from the data volume node to the root node can be used as the available data volume corresponding to the department. The data amount of the preset number of data amount nodes on the path may also be selected as the available data amount corresponding to the department, for example, the available data amount corresponding to the preset node where the distance between the data amount nodes is not greater than the preset value, and so on.

S202, selecting a target data volume from available data volumes according to a preconfigured selection rule.

The selection rules may include a sort order, a priority order, and the like.

For example, the plurality of available data amounts may be sorted by attribute information, and then the target data amount may be selected based on the sorting result. For example, the plurality of available data amounts are sorted according to the purpose, application range, validity period, data amount value, and the like, for example, the order with the specific purpose is first, the order with the specific application range is first, the order with the validity period is first, the order with the budget amount is first, and the like, and then one available data amount ordered at the forefront is selected as the target data amount. Simple understanding, i.e., for a particular product coupon budget return, for a particular zone, for an early (fast expiring) expiration date, or for a relatively small data volume value.

In one implementation, a plurality of available data amounts may be presented through a list, so that a target data amount may be more intuitively and conveniently selected based on the list.

Meanwhile, the data analysis and statistics conditions of the data quantity can be displayed, and statistics of time granularity, product granularity, department granularity and member granularity are supported. The data quantity can be counted according to the dimensions of time, products, departments, organization members and the like, and the counted data is displayed.

Selecting the target amount of data from the list may include:

after the organization members applying for virtual data distribution click on an available data amount in the list, the electronic equipment can display attribute information corresponding to the available virtual data and a confirmation button, the organization members applying for virtual data distribution select based on the attribute information, and if the organization members applying for virtual data distribution are selected, the confirmation button is clicked; if not, the back button is clicked.

Based on the data quantity model, the data quantity matched with the organization members applying for virtual data distribution can be selected, the data quantity is reasonably utilized, and the cost waste in the virtual data distribution is reduced.

S104, virtual data is distributed based on the target data quantity.

May include:

acquiring attribute information of a target data volume; drawing a data amount from the target data amount based on the attribute information; virtual data is allocated in accordance with the amount of data drawn from the target amount of data.

The attribute information may include, in particular, the type, status, creation time, validation time, expiration time, corresponding traffic, etc. of the target data volume.

For example, the entire target data amount may be divided based on the attribute information, or a part of the data amount distribution virtual data in the target data amount may be divided.

The data volume is reasonably utilized to distribute the virtual data, so that cost allocation management and control in the virtual data distribution process are realized, and cost waste in the virtual data distribution process can be further reduced.

The data volume acts on the virtual data to be allocated, and the virtual data is allocated, that is, the value required by deducting the virtual data from the data volume can be all the values of the data volume or part of the values in the data volume.

In one implementation, as shown in fig. 3, the drawing of the data volume from the target data volume based on the attributes may include:

s301 sets the state of the target data amount to frozen.

Frozen means not responding to other virtual data allocations.

The state of the virtual data may include: unused, frozen, budgeted consumed, approved, failed, used.

S302, generating an operation record.

The operation record is used for recording an operation request for dividing the data volume from the target data volume.

Specifically, the operation record is used to record an operation request for subtracting the value required for the dummy data from the target data amount.

The value required for the dummy data can be understood as a value of the data amount required for the dummy data.

S303, generating a use record corresponding to the target data volume based on the attribute information and the operation record.

The usage record may be sent to an approval manager to cause the approval manager to approve the usage record.

The approval manager may be a pre-set approval person with the highest authority.

An identification, such as a service number, corresponding to the usage record may be generated.

S304, in response to the approval of the use record, updating the state of the target data volume to be used, and drawing the data volume from the target data volume.

In one implementation, an operation request to scratch a target amount of data is denied in response to a usage record passing approval.

In one implementation, an operation request to draw a data volume from the target data volume may be performed first, and after the approval fails, the value subtracted from the target data volume in the operation record may be increased in the deduction value.

The subtraction value is a value obtained by subtracting the required value of the dummy data from the target data amount in the operation record.

After the approval is failed, the value subtracted from the data quantity in the target data quantity is returned, the accuracy of the data quantity value is ensured, misuse and the like of the data quantity in the virtual data process are avoided, the data quantity is reasonably managed, the cost management and control in the virtual data distribution process is realized, and further the cost waste and the like can be reduced.

After the organization member initiates the application, the organization member does not directly enter the virtual data distribution process, firstly, UCAP of the applicant, account Id (user name using virtual data) of the customer, data volume number (data volume application service number, which needs to have uniqueness), data volume use information, numerical value information of the applied data volume and the like are obtained, freezing operation is carried out on the data volume, a unique service id is generated, then an approval result is waited, and the numerical value of the data volume is deducted by the budget freezing operation.

If the budget approval of the applicant fails or the approval is abnormal, thawing the data volume, and returning the value subtracted from the data volume in the target data volume; if the budget approval result of the applicant is approved, a business id (identification) of frozen data volume needs to be transmitted, the frozen data volume is processed and corresponding virtual data is distributed.

The influence of other virtual data distribution applications on the distribution process can be avoided in the process of processing a virtual data distribution application by freezing, and complete management and control can be established by approval.

In the embodiment of the disclosure, virtual data is distributed based on the pre-created data volume model, so that a whole set of full-flow closed-loop management and control can be realized, abusive sending, abusive use, resource waste and the like in the virtual data distribution process are avoided, and the virtual data use efficiency is improved.

In an alternative embodiment, as shown in fig. 4, the modeling of the data volume according to the embodiments of the present disclosure may include:

s401, constructing a category hierarchy based on structural information of a plurality of categories.

The structural information of the plurality of categories may include associations between the categories, and may be used to represent dependencies between the categories in particular, for example, may include dependencies between the plurality of departments.

Different departments will be described as examples of different categories.

A multi-level tree structure may be built up in a multi-dimensional organization management system. The multidimensional organization management system can be understood as that the actual business of enterprises and the like falls to the ground through a business group-business-product mechanism, the related multidimensional organization management system establishes the association of organizations and products on different levels, and talents can be timely, accurately and effectively distributed and input on the business and the products through the multidimensional organization management system, so that the motility of the talents is fully activated.

Based on the association between departments, connection relations between nodes are established to construct a category hierarchy.

Taking three-layer team architecture Level3 as an example, the structure information is shown in fig. 5.

The multiple departments include a first level team: team 1, the primary team responsible person is uuap_1. The primary team includes a plurality of secondary teams: team 21 (the secondary team responsible for manmade UUAP_21), team 22 (the secondary team responsible for manmade UUAP_22), team 23 (the secondary team responsible for manmade UUAP_23), team 24 (the secondary team responsible for manmade UUAP_24), team 25 (the secondary team responsible for manmade UUAP_25), team 26 (the secondary team responsible for manmade UUAP_26), team 27 (the secondary team responsible for manmade UUAP_27), team 28 (the secondary team responsible for manmade UUAP_28), team 29 (the secondary team responsible for manmade UUAP_29). Team 28 in the secondary team includes a tertiary team: team 31 (the tertiary team responsible person uuap_31), team 32 (the tertiary team responsible person uuap_32); team 29 in the secondary team includes a tertiary team: team 33 (the tertiary team responsible person uuap_33), team 34 (the tertiary team responsible person uuap_34), team 35 (the tertiary team responsible person uuap_35), team 36 (the tertiary team responsible person uuap_36).

A category hierarchy is constructed based on a three-level category structure, such as a hierarchy and a relationship of categories of each level in the three-level team architecture. One layer category such as first order team: team 1, two-level categories such as second level team: team 21, team 22, team 23 … … team 29, three-level categories such as three-level team: team 21, team 32, build a category hierarchy as shown in FIG. 6.

The class hierarchy is a tree structure. Node information for each node in the category hierarchy may be stored in embodiments of the present disclosure. Specifically, the core field of the node information includes: the current tree node number (OrgId), the parent node id (paramentorgid, i.e., the node of the upper layer closest to the current node), the current tree node organization architecture Name (Name), the full path (OrgPath) from the top parent node to the current node, the business unit (business unit), the organization Attribute (Attribute), the organization architecture state of the current tree node (OrgStatus, i.e., whether the node has been deleted). The node information in the team hierarchy may be stored in the storage structure shown in fig. 7.

Taking different departments as different categories as an example, the category hierarchy includes organization members of each department, namely responsible persons of the departments. The embodiment of the disclosure can store the organization member information of the organization members of various departments. And constructing organization member information corresponding to each node in the multi-level tree structure according to UCAP identities (unique enterprise authentication identities, such as unique enterprise mailbox prefixes and other unique identifiers) of the organization members. The core fields of the organization member information include: organization membership unique identification (UUAP), organization member name (employee name), current tree node number (OrgId, team architecture and organization members are associated according to this field), current member corresponding Level1 team information (OrgPath Level1, primary team), current member corresponding Level2 team information (OrgPath Level2, secondary team), current member corresponding Level3 team information (OrgPath Level3, tertiary team). The organization member information may be stored in a storage structure as shown in fig. 8. The storage structure level of the storage structure is determined according to actual requirements.

In an actual application scenario, there is a possibility that a new department or a deleted department, i.e. structural information of the department changes, so that in order to enable the category hierarchy to accurately reflect the relationship between categories, in an alternative embodiment, the category hierarchy may be updated by adjusting nodes in the tree structure according to the change of the structural information.

Taking different departments as examples, different operations are performed according to different changing requirements of the team, and the team can be understood as the department.

Newly added team: and constructing a new tree structure according to the original department organization structure information table, namely the structure information.

Deletion team: the organization members of the team are deleted first, and then the designated team is deleted.

Newly added subordinate team: selecting a father node team to add nodes newly.

Moving team: the team node to be moved and the target parent node team node are selected, a move operation is performed, and OrgPath, businessUnit involved in the move process is recursively updated from the parent node.

According to different changing requirements of organization members, different operations are performed:

newly added members: and selecting a class hierarchy and nodes of departments to which the organization members belong, and adding UCAP (unmanned Unit Access Point) of the organization members.

Deleting the member: and selecting the organization member information, executing the deleting operation, and simultaneously updating the organization member information in the storage structure.

Configuring member rights: the member authority comprises a first team responsible person and a second team responsible person, wherein the first team responsible person has only one authority, and the second team responsible person can have a plurality of authorities.

Replacement (mobile) team: selecting organization member information, selecting a replaced team in the category hierarchy, clicking and moving to the team button, and simultaneously updating the organization member information in the storage structure.

S402, establishing a data volume model based on the category hierarchy architecture.

The data volume model comprises available data volumes respectively corresponding to all categories in the category hierarchy.

A corresponding amount of available data may be created based on each node in the category hierarchy, with corresponding creation of the respective categories of the corresponding amount of available data based on the hierarchical relationship of each node in the category hierarchy. For example, a corresponding data volume node may be established based on each node in the class hierarchy, i.e., a data volume node corresponding to each class may be established based on the hierarchical relationship of each node in the class hierarchy.

An edit button may be configured for each data volume node in the data volume model, attribute information may be configured, for example, a numerical value of an initial data volume may be set by clicking the edit button, and other attribute information than the numerical value may be set. I.e. after clicking the edit button, the electronic device may provide an edit interface in which attribute information may be entered.

In the embodiment of the disclosure, the category and the data volume can be modeled according to the actual application demand scene, namely, a team hierarchy architecture and a data volume model are constructed, if modeling is carried out by adopting a tree structure, the data volume can be configured for the category-based hierarchy structure, the data volume can be reasonably utilized for distributing virtual data based on the data volume model, the cost management and control of virtual data distribution are realized, and the resource waste is reduced.

In an alternative embodiment, data analysis results may be obtained; based on the data analysis results, the data volume model is adjusted.

The data analysis results include the use of virtual data.

For example, the virtual data may be virtual currency such as a voucher, and the use of the virtual data may include information about the use of the voucher by the user, such as the number of vouchers that have not been used due to the voucher, used different amounts, and so forth.

Specifically, with respect to the nodes corresponding to the data amount in the data amount model, based on the data analysis result, the relationship between the nodes and/or the node information of the nodes themselves, that is, the attribute information of the data amount, may be adjusted.

The use condition of the virtual data can be fed back to the data volume model, so that the data volume model can more accurately reflect the actual environment of virtual data application, and further, the adjusted data volume model can be used for distributing the virtual data by reasonably utilizing the data volume, management and control of the virtual data distribution cost are realized, resource waste is reduced, and the like.

The data amount can be divided into two types, a detachable data amount and an non-detachable data amount.

Detachable data amount: a representation that is available to divide the amount of sub-data; non-detachable data amount: the representation is only available for consumer applications.

Taking the data volume as a budget for illustration, the data volume model comprises a first-level number, such as a first-level budget 1, wherein the first-level data volume comprises a plurality of second-level data volumes, such as the first-level budget 1 comprises a second-level budget 1, a second-level budget 2 and a second-level budget 3; the secondary data volume includes a tertiary data volume, e.g., secondary budget 2 includes tertiary budget 1 and tertiary budget 2.

The detachable data volume is shown as non-leaf nodes in the data volume model shown in fig. 9, such as a primary budget 1 and a secondary budget 2; the non-splittable data volume is shown as leaf nodes in the data volume model shown in fig. 9, such as secondary budget 1, secondary budget 3, tertiary budget 1 and tertiary budget 2.

With respect to FIG. 9, the split budget may be divided, any budget added, rolled out, rolled in, used, refunded, etc. While the budget has a validity period, divided by year by default. Acquiring the budget may only acquire the amount of the budget node closest to the current organization member, e.g., the budget node closest to the current organization member may include: parent nodes of the budget nodes corresponding to the current organization members, and so on.

The data volume model may also be a tree structure corresponding to the class architecture model. However, the hierarchy of the data volume model may or may not be consistent with the hierarchy of the class hierarchy.

One category may correspond to a plurality of data amounts, and the hierarchy of data amounts may also be larger than the hierarchy of categories. For example, a division may correspond to multiple budgets, and the level of the budgets may be larger than the level of the division, as shown in FIG. 11, which is a data volume model built based on the category hierarchy as shown in FIG. 10.

Taking the data volume as the budget as an example, each budget corresponds to a budget number, and when using the budget, all available budgets can be queried according to the departments where the current organization members are and the parent department ids of the departments.

The budget information may include: budget unique identification (budgetuid, voucher needs to deduct money from which budget), budget application service number (ApplyBizID, needs to have uniqueness), parent budget number (partntid), budget node type (nodypype, e.g. 0: partitionable node, 1: consumable node), budget name (BudgetName), budget creation time (CreateTime), budget expiration time (EndTime), budget effective time (begin time), budget update time (UpdateTime), budget Status (Status, e.g. 0: normal, 1: locked, 2: obsolete), budget funds Balance (Balance), budget funds total (totalaunt), budget corresponding departments id (DepartmentId), description information of budget, etc. The budget information may be stored in a memory structure as shown in fig. 12.

Multiple departments may also be understood as budget teams, referring to objects that need to be managed by a budget. One budget team may have multiple budget numbers. A budget number is bound with a unique budget amount, and operations such as deduction, freezing and the like of the budget can be performed.

In the embodiment of the disclosure, a group class hierarchy is established according to different classes of architecture information, a data volume model is established, virtual data is distributed based on the class hierarchy and the data volume model, cost management and control of virtual data distribution are achieved, and the use efficiency of virtual data is improved.

The embodiment of the disclosure establishes a category hierarchy architecture and a data volume model, and a category representation department is taken as an example for illustration by taking the data volume as a budget.

The cost allocation management and control of the virtual data distribution of the whole flow closed loop is realized through data volume setting, data volume application, data volume adjustment, data volume freezing and thawing use. Meanwhile, the virtual data application can be refined, and different values can be set for the virtual data of different applications.

Data volume setting: namely, the data volume model is constructed in the above embodiment, and the data volume model comprises the setting of the numerical value of the data volume and the setting of the data volume type architecture.

An edit button may be configured for each data volume node in the data volume model, and attribute information may be configured, for example, a value of an initial data volume may be set by clicking the edit button, and other attribute information than the value of the data volume may be set. I.e. after clicking the edit button, the electronic device may provide an edit interface in which attribute information may be entered.

In addition, the data volume node and attribute information, such as adding, deleting or moving the data volume node, modifying the initial attribute information, etc., may also be adjusted by the edit button.

Data volume usage: when the data volume is used, all available data volumes are inquired according to the category of the current organization member and the parent department id of the current organization member. The data volume is divided into two types, a splittable data volume and a non-splittable data volume, and the data volume can be divided into multiple levels, allowing dividing operations to be performed on the splittable data volume, and new adding, rolling out, rolling in, using, and rolling back operations to be performed on any data volume. The data volume is acquired, and only the data volume of the data volume node closest to the current data volume node is acquired. The data volume use comprises operations such as freezing of the data volume of the initiated application of the core, thawing of the data volume of approval failure, approval success and the like.

Data volume adjustment: and editing the current data volume calculation after clicking, and adjusting the data volume model according to the company strategy and market feedback data (data analysis result).

Data volume storage: the addition and subtraction record of the current data volume, namely the application and consumption condition of the data volume, needs to be saved.

And the data volume control point is used for controlling the data volume when the virtual data of the server system is distributed.

Virtual data amount calculation logic: the amount of data acts on the virtual data to be allocated.

Referring to fig. 13, a process of querying the available data amount based on a pre-created data amount model is illustrated.

And sending a virtual data distribution application by the organization member applying for virtual data distribution, wherein the organization member applying for virtual data distribution has identification information uuap.

The electronic equipment receives the virtual data allocation application, firstly queries the class hierarchy, and determines the class corresponding to the organization member, for example, determines the department actually operated by the organization member. Then, the data volume model is searched, the corresponding data volume node in the category in the data volume model is determined, and the father node of the data volume node is searched according to the searching sequence from bottom to top, and the father node … … of the father node is searched until the root node of the data volume model is searched. The data volume corresponding to the root node can be used as the available data volume, and the data volume corresponding to the root node comprises the data volume of the root node and the data volume of the child nodes of the root node. The available data volume may be presented in a list form, i.e., the data volume query results are presented.

The organization member uuap interface provides the function of querying the category to which it belongs, and according to the category, can query out all available data amounts available for the category, and then return the list. The organization member selects a corresponding data amount to allocate virtual data when issuing the coupon, for example, the organization member uuap may correspond to the budget number.

The embodiment of the disclosure can apply for the allocation of the data volume and the virtual data through the CRM (customer relationship management system) of the service provider console, and display the use condition of the maintenance data volume through the OSP (operation service system) of the service provider console.

The process of using the data amount according to the embodiment of the present disclosure will be described with reference to fig. 14, and the process of using the data amount may also be understood as a process of performing virtual data allocation based on the data amount.

The setting of the data volume, e.g. the setting of a budget, i.e. the pre-building of a data volume model, the specific building process has been described in detail in the above embodiments.

The AM (applicant) proposes a virtual data distribution application, such as a voucher issuing application, in the CRM system, obtains a list of data amounts based on the data amount model, and selects an available data amount, i.e. obtains an available data amount, such as an available budget, from which a target data amount is selected. AM is an organization member within an organization architecture and may also be understood as the applicant of virtual data distribution.

CRM confirms, freezes the data quantity and returns a frozen business number, then enters an approval program, namely Work flow approval, approval failure or approval abnormality, and unfreezes the data quantity; if the approval passes, the virtual data is allocated with the data amount, and in particular, the CRM allocates the virtual data based on the data amount. In virtual data distribution, the CRM delivers a frozen service number to a system, such as a Coupon system Coupon. In addition, the system performs data analysis, and specifically, may collect data analysis results; based on the data analysis results, the data volume model is adjusted.

Based on the control flow shown in fig. 14, the virtual data allocation according to the embodiment of the present disclosure will be described in detail with reference to fig. 15.

Step 1, applying for virtual data distribution, such as voucher distribution, in the CRM.

And 2, inquiring a data volume list, such as a budget list, according to the uuap.

And 3, inquiring department id by the system coupler according to the uuap.

And step 4, inquiring the GTM department id.

The OSP system of the service provider console provides a data volume display function and can display the data volume which is in effective period, of a specified type and still takes effect without being invalidated; and analyzing and counting the data quantity data, and supporting statistics of time granularity, product granularity, department granularity and member granularity.

Step 5, the coupler returns the data volume list to the CRM.

When the CRM system of the service provider console applies for virtual data distribution, organization members (namely the applicant AM) fill in the purpose and type of the virtual data first, then acquire the current category according to the uuap of the applicant and the virtual data information, such as a data volume list available to the current department, acquire department id information corresponding to the data volume, and the applicant selects and initiates the application of virtual data distribution.

And 6, selecting a target data volume based on applicant uuap, client account id, data volume number, purpose information, application amount information and the like.

Applicant selects a corresponding data amount from the returned data amount list in the CRM system.

And 7, storing the freezing request.

And 8, using the data volume.

And 9, acquiring the numerical value of the data quantity.

And 10, writing the numerical value of the data quantity into a consumption record, and generating a budget application consumption record.

Data amount status: unused; the request for changing the data volume is: has been frozen.

And sending the budget application consumption record to an approver for approval. The approval passes to step 15, and the approval fails or the approval is abnormal, and step 11 is performed.

The steps 7 to 10 can implement data volume freezing logic, taking data volume as budget as an example, after an organization member (i.e. AM) initiates an application, it will not directly enter an allocation link, but will first acquire information such as the applicant UUAP of the budget, the client AccountId (user name), the budget number (the service number of the budget application, the required uniqueness), the information of the budget usage, the information of the applied budget amount, etc., execute a freezing operation on the budget, generate a unique service id, and then wait for an approval result, and the budget freezing operation deducts the balance of the budget.

Step 11, if the budget approval of the applicant is not passed or the approval is abnormal, the budget will be thawed and the balance of the budget will be increased.

Step 12, recording budget application consumption records.

And 13, generating a refund record.

Step 14, increment balance and modify transfer (transfer) record as rejected.

Steps 11 to 14 may implement budget thawing logic that thaws the budget if the applicant's budget approval fails or the approval is abnormal, increasing the budget balance.

Step 15, modifying the state of the target budget to used.

And step 16, consuming the budget and distributing the virtual data.

Steps 15 to 16 can implement the allocation of virtual data, if the budget approval result of the applicant is approved, and the business id of the frozen budget needs to be transmitted, the frozen budget will be consumed, and the corresponding virtual data is allocated.

In the embodiment of the disclosure, the data volume application and the transfer of the data volume state are involved in the process of using the data volume, and the data volume application record transfer schematic diagram is shown in fig. 16. Applying for distribution of virtual data, such as applying for a voucher, when the application fails, the voucher budgeting the status of the application record is unused (PENDING); when the application is successful, the state of the voucher budget application record is FROZEN (FROZEN), after the voucher application is successful, an approval process is carried out, the approval passes, the voucher budget application record is Consumed (CONSUMDED), the approval fails, and the voucher budget application record is Returned (REFUNDED).

Fig. 17 is a state transition diagram of data volume consumption. Applying for distribution of virtual data, such as applying for a voucher, when the application fails, the state of budget consumption is no record; when the application is successful, the state of budget consumption is UNUSED (UNUSED). After the application succeeds, an approval procedure is performed, the approval fails, the state of budget consumption is returned (returned), the approval passes, and the state of budget consumption is USED (used_up).

Aiming at the problems of abuse, misuse and resource waste existing in virtual data distribution in the related technology, the embodiment of the disclosure provides a virtual data distribution mode based on a data volume model, which generally comprises the following steps: pre-constructing a data volume model and performing virtual data distribution based on the data volume model. Setting different data quantity values for virtual data of different purposes, not only can solve the problem that the virtual data which is too generalized is applied to irrelevant scenes and cannot finish the original issuing targets, prevent enterprise cost loss, but also can exert the effects that the virtual data stimulates user consumption, increases stream and improves the viscosity of platform users to the maximum extent; the category architecture tree model, that is, the category hierarchy architecture, can dynamically support the adjustment of different enterprises to team architectures in different development periods, including: the organization department structure adding and deleting, department attribute editing, cross-team movement adjustment, organization personnel change in the department door and cross-department personnel change have extremely strong flexibility and adaptability. The data volume model can support setting category types, split categories and non-split categories, dividing the split categories, adding, transferring, using, returning and the like of any category type, namely a flexible support company timely adjusts the data volume model according to marketing strategies aiming at different products in different periods and product data analysis results.

The full-flow closed-loop virtual data distribution can help enterprises to intelligently manage the investment of virtual data cost, so that the virtual data use efficiency is improved greatly, and the value of the virtual data is stimulated; the requirements of a company management layer on management, control and analysis of marketing activities and marketing cost are met; the enterprise management level and the operation efficiency are comprehensively improved, and the maximization of the enterprise value is realized. And the demand of refined marketing to the product can be satisfied, the marketing personnel can be helped to accurately marketing the resources allocated in a specified way, the demand of clients on preferential price can be satisfied, the marketing resources can be accurately mastered, and the abused issuing of the voucher is avoided.

The embodiment of the disclosure further provides a virtual data distribution device, as shown in fig. 18, which may include:

an obtaining module 1801, configured to obtain a virtual data allocation application, where the virtual data allocation application includes an organization member applying for virtual data;

a determining module 1802, configured to determine a category corresponding to an organization member based on a category hierarchy constructed in advance; determining a target data volume corresponding to the category based on a pre-constructed data volume model, wherein the target data volume is used for representing the data volume to be distributed of virtual data distribution;

An allocation module 1803, configured to allocate virtual data based on the target data amount.

Optionally, as shown in fig. 19, further includes:

a building module 1901, configured to build a category hierarchy based on structural information of a plurality of categories, where the structural information is used to represent subordinate relations between the plurality of categories;

the establishing module 1902 is configured to establish a data volume model based on the category hierarchy, where the data volume model includes available data volumes corresponding to respective categories in the category hierarchy.

Optionally, the determining module 1802: the method is also used for obtaining available data quantity corresponding to the category based on the data quantity model; a target data volume is selected from the available data volumes according to a pre-configured selection rule.

Optionally, the allocation module 1803: the method is also used for acquiring attribute information of the target data volume; drawing a data amount from the target data amount based on the attribute information; virtual data is allocated in accordance with the amount of data drawn from the target amount of data.

Optionally, the allocation module 1803: and is further configured to set the state of the target data amount to frozen, the frozen representing no response to other virtual data allocations; generating an operation record for recording an operation request for dividing a data volume from a target data volume; generating a usage record corresponding to the target data volume based on the attribute information and the operation record; in response to the usage record approval passing, the status of the target data volume is updated to used and the data volume is scraped from the target data volume.

Optionally, the allocation module 1803: and the operation request for drawing the data volume from the target data volume is refused in response to the passing of the usage record approval.

Optionally, the category hierarchy is a tree structure, and a node in the tree structure corresponds to a category;

as shown in fig. 20, the apparatus further includes:

the first adjustment module 2001 is configured to update the category hierarchy by adjusting nodes in the tree structure according to the change of the structure information.

Optionally, as shown in fig. 21, the apparatus further includes:

the acquisition module 2101 is used for acquiring a data analysis result, wherein the data analysis result comprises the use condition of virtual data;

a second adjustment module 2102, configured to adjust the data volume model based on the data analysis result.

In the technical scheme of the disclosure, the related processes of collecting, storing, using, processing, transmitting, providing, disclosing and the like of the personal information of the user accord with the regulations of related laws and regulations, and the public order colloquial is not violated.

According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

Fig. 22 shows a schematic block diagram of an example electronic device 2200 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 22, the device 2200 includes a computing unit 2201 that can perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM) 2202 or a computer program loaded from a storage unit 2208 into a Random Access Memory (RAM) 2203. In the RAM 2203, various programs and data required for the operation of the device 2200 may also be stored. The computing unit 2201, the ROM 2202, and the RAM 2203 are connected to each other via a bus 2204. An input/output (I/O) interface 2205 is also connected to bus 2204.

Various components in device 2200 are connected to I/O interface 2205, including: an input unit 2206 such as a keyboard, a mouse, or the like; an output unit 2207 such as various types of displays, speakers, and the like; a storage unit 2208 such as a magnetic disk, an optical disk, or the like; and a communication unit 2209 such as a network card, modem, wireless communication transceiver, or the like. The communication unit 2209 allows the device 2200 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks.

The computing unit 2201 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 2201 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 2201 performs the respective methods and processes described above, such as the virtual data allocation method. For example, in some embodiments, the virtual data allocation method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 2208. In some embodiments, some or all of the computer programs may be loaded and/or installed onto device 2200 via ROM 2202 and/or communications unit 2209. When the computer program is loaded into RAM 2203 and executed by computing unit 2201, one or more steps of the virtual data allocation method described above may be performed. Alternatively, in other embodiments, the computing unit 2201 may be configured to perform the virtual data allocation method in any other suitable manner (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), 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.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.

The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims

1. A virtual data allocation method, comprising:

constructing a category hierarchy based on structural information of a plurality of categories, the structural information being used to represent affiliations between the plurality of categories;

based on the category hierarchy, establishing the data volume model, wherein the data volume model comprises available data volumes respectively corresponding to each category in the category hierarchy;

obtaining a virtual data distribution application, wherein the virtual data distribution application comprises organization members applying for virtual data distribution;

distributing virtual data based on the target data volume;

wherein, based on the pre-constructed data volume model, determining the target data volume corresponding to the category includes: based on the data quantity model, obtaining available data quantity corresponding to the category; selecting the target data volume from the available data volumes according to a pre-configured selection rule;

the assigning virtual data based on the target data amount includes: acquiring attribute information of the target data volume; drawing a data amount from the target data amount based on the attribute information; distributing the virtual data according to the data amount drawn from the target data amount;

the drawing the data volume from the target data volume based on the attribute information includes: setting a state of the target data amount to frozen, the frozen representing no response to other virtual data allocations; generating an operation record for recording an operation request to score a data amount from the target data amount; generating a usage record corresponding to the target data volume based on the attribute information and the operation record; updating the state of the target data volume to be used in response to the approval of the use record, and drawing the data volume from the target data volume; rejecting an operation request for drawing the data volume from the target data volume in response to the use record passing approval;

The method further comprises the steps of:

acquiring a data analysis result, wherein the data analysis result comprises the service condition of the virtual data;

and adjusting the data volume model based on the data analysis result.

2. The method of claim 1, the class hierarchy being a tree structure in which one node corresponds to one class;

the method further comprises the steps of:

and updating the category hierarchy by adjusting nodes in the tree structure according to the change of the structure information.

3. A virtual data distribution apparatus comprising:

the building module is used for building a category hierarchy architecture based on structural information of a plurality of categories, wherein the structural information is used for representing subordinate relations among the categories;

the establishing module is used for establishing the data volume model based on the category hierarchy, wherein the data volume model comprises available data volumes respectively corresponding to each category in the category hierarchy;

An allocation module for allocating virtual data based on the target data amount;

wherein, the determination module: the method is particularly used for obtaining available data quantity corresponding to the category based on the data quantity model; selecting the target data volume from the available data volumes according to a pre-configured selection rule;

the distribution module: the method is particularly used for acquiring attribute information of the target data volume; drawing a data amount from the target data amount based on the attribute information; distributing the virtual data according to the data amount drawn from the target data amount;

the distribution module: and further for setting a state of the target data amount to frozen, the frozen representing non-responsive to other virtual data allocations; generating an operation record for recording an operation request to score a data amount from the target data amount; generating a usage record corresponding to the target data volume based on the attribute information and the operation record; updating the state of the target data volume to be used in response to the approval of the use record, and drawing the data volume from the target data volume; rejecting an operation request for drawing the data volume from the target data volume in response to the use record passing approval;

The apparatus further comprises:

the acquisition module is used for acquiring a data analysis result, wherein the data analysis result comprises the use condition of the virtual data;

and the second adjusting module is used for adjusting the data quantity model based on the data analysis result.

4. The apparatus of claim 3, the class hierarchy being a tree structure in which one node corresponds to one class;

the apparatus further comprises:

and the first adjusting module is used for updating the category hierarchy architecture by adjusting the nodes in the tree structure according to the change of the structure information.

5. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-2.

6. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-2.