阅读说明：本技术 基于数据仓库的指标模型管理方法、存储介质和装置 (Index model management method, storage medium and device based on data warehouse ) 是由 宁任声 于 2020-05-29 设计创作，主要内容包括：本申请公开了一种基于数据仓库的指标模型管理方法、装置以及存储介质。其中,该方法包括：接收用于创建指标模型的第一指标模型参数信息,其中指标模型用于对数据仓库中与预定业务相关的数据进行指标分析；根据第一指标模型参数信息,确定用于创建第一指标模型的业务模型单元,并从业务模型单元的字段中确定与第一指标模型相关的度量；根据所确定的度量,创建第一指标模型；以及基于第一物理模型以及第一数据表结构,确定与第一指标模型绑定的物理模型以及数据表结构。(The application discloses an index model management method and device based on a data warehouse and a storage medium. Wherein, the method comprises the following steps: receiving first index model parameter information for creating an index model, wherein the index model is used for performing index analysis on data related to a predetermined service in a data warehouse; determining a business model unit for creating the first index model according to the parameter information of the first index model, and determining the measurement related to the first index model from the field of the business model unit; creating a first metric model from the determined metric; and determining the physical model and the data table structure bound with the first index model based on the first physical model and the first data table structure.)

1. An index model management method based on a data warehouse is characterized by comprising the following steps:

receiving first index model parameter information used for creating an index model, wherein the index model is used for performing index analysis on data related to a preset business in the data warehouse;

determining a business model unit for creating a first index model according to the first index model parameter information, and determining a measure related to the first index model from fields of the business model unit, wherein the business model unit comprises fields related to the preset business, the business model unit is bound with a first physical model, and the first physical model is bound with a first data table structure which is arranged in a physical database and used for constructing the data warehouse;

creating the first metric model according to the determined metric; and

and determining a physical model and a data table structure bound with the first index model based on the first physical model and the first data table structure.

2. The method of claim 1, wherein the act of creating the first metric model from the determined metrics comprises:

determining a first expression and/or a first statistical granularity for defining the first index model according to the parameter information of the first index model; and

creating the first metric model from the metric using the first expression and/or the first statistical granularity.

3. The method of claim 1, wherein determining a business model unit for creating a first metric model and determining metrics related to the first metric model from fields of the business model unit comprises:

determining a dimension model unit or a fact model unit which is associated with the predetermined business and is used as the business model unit according to the first index model parameter information, wherein the dimension model unit comprises a field for describing a dimension for analyzing the predetermined business, and the fact model unit comprises a field for describing a fact associated with the predetermined business; and

determining the metric related to the first metric model from a field of the dimension model unit or the fact model unit.

4. The method of claim 1, further comprising:

receiving second index model parameter information for creating an index model;

determining an index model set used for creating a second index model according to the parameter information of the second index model;

and creating the second index model according to the index models in the index model set.

5. The method of claim 4, wherein the operation of creating the second index model from the index models in the set of index models comprises:

determining a second expression for defining the second index model according to the parameter information of the second index model; and

and creating the second index model according to the index models in the index model set and the second expression.

6. The method of claim 4, further comprising:

constructing a second physical model related to the second index model, and creating a second data table structure corresponding to the second physical model in a physical database; and

and binding the second index model and the second physical model to realize the association between the second index model and the second data table structure.

7. The method of claim 5, wherein the operation of creating the second index model from the index models in the set of index models and the second expression comprises:

determining whether the metric models in the set of metric models are created based on the same fact model unit, wherein the fact model unit comprises a field describing a fact associated with the predetermined service; and

in a case where it is determined that the index models in the index model set are created based on the same fact model unit, the second index model is created from the index models in the index model set and the second expression.

8. The method of claim 7, wherein the operation of creating the second index model from the index models in the set of index models and the second expression comprises, in the event that it is determined that the index models in the set of index models are created based on different fact model units, performing the following operations:

determining whether the different fact model elements are associated with a common dimension; and

in a case where it is determined that the different fact model units are associated with a common dimension, the second index model is created from the index models in the index model set and the second expression.

9. A storage medium comprising a stored program, wherein the method of any one of claims 1 to 8 is performed by a processor when the program is run.

10. An index model management apparatus (1700) based on a data warehouse, comprising:

a first parameter information receiving module (1710) for receiving first index model parameter information for creating an index model for performing index analysis on data related to a predetermined service in the data warehouse;

a business model unit determining module (1720) for determining a business model unit for creating a first index model according to the first index model parameter information, and determining a metric related to the first index model from fields of the business model unit, wherein the business model unit includes fields related to the predetermined business, the business model unit is bound with a first physical model, and the first physical model is bound with a first data table structure which is arranged in a physical database and used for constructing the data warehouse;

a first metric model creation module (1730) for creating the first metric model in accordance with the determined metric; and

a binding object determination module (1740) configured to determine a physical model and a data table structure bound to the first metric model based on the first physical model and the first data table structure.

Technical Field

The present application relates to the field of computer technologies, and in particular, to a data warehouse-based index model management method, storage medium, and apparatus.

Background

With the continuous development of enterprises, as data generated in the business management process has the characteristics of large quantity, high updating frequency, complex analysis and processing and the like, a certain data processing and analyzing tool needs to be used for analyzing and managing mass data so as to meet the requirements of management, wind control, decision making and the like. Therefore, it is necessary to establish an index management tool to manage the construction, modification, tracking, etc. of indexes of the data warehouse.

The existing method for constructing the index needs to solve the table structure and table relationship, and because different table structures and table relationships need to be converted through a plurality of intermediate conversions, the conversion can be completed by professional technicians, and a large amount of personnel cost is consumed. And the mode is limited by a specific data table in the data warehouse, the relation between the model and the actual business cannot be reflected in a business view, and the constructed index cannot be migrated from one data warehouse to other data warehouses.

In order to solve the technical problems that the method for constructing the index model in the prior art needs to solve the table structure and table relationship, needs professional technicians to finish the method, consumes a large amount of personnel cost, is limited by a specific data table in a data warehouse, cannot reflect the relationship between the model and actual business from a business perspective, and cannot migrate the constructed index model from one data warehouse to other data warehouses, an effective solution is not provided at present.

Disclosure of Invention

The embodiment of the disclosure provides an index model management method, medium and device based on a data warehouse management platform, and at least solves the technical problems that in the prior art, a method for constructing an index model needs to solve a table structure and table relationship, can be completed only by professional technicians, consumes a large amount of personnel cost, is limited by a specific data table in a data warehouse, cannot reflect the relationship between a model and actual business from a business view angle, and cannot migrate the constructed index model from one data warehouse to other data warehouses.

According to an aspect of the embodiments of the present disclosure, there is provided a data warehouse-based index model management method, including: receiving first index model parameter information for creating an index model, wherein the index model is used for performing index analysis on data related to a predetermined service in a data warehouse; determining a business model unit for creating a first index model according to the parameter information of the first index model, and determining measurement related to the first index model from fields of the business model unit, wherein the business model unit comprises fields related to a preset business, the business model unit is bound with a first physical model, and the first physical model is bound with a first data table structure which is arranged in a physical database and used for constructing a data warehouse; creating a first metric model from the determined metric; and determining the physical model and the data table structure bound with the first index model based on the first physical model and the first data table structure.

According to another aspect of the embodiments of the present disclosure, there is also provided a storage medium including a stored program, wherein the method of any one of the above is performed by a processor when the program is executed.

According to another aspect of the embodiments of the present disclosure, there is also provided an index model management apparatus based on a data warehouse, including: the system comprises a first parameter information receiving module, a first index model parameter information generating module and a first index information analyzing module, wherein the first parameter information receiving module is used for receiving first index model parameter information used for creating an index model, and the index model is used for performing index analysis on data related to a preset service in a data warehouse; the business model unit determining module is used for determining a business model unit used for creating a first index model according to the parameter information of the first index model, and determining measurement related to the first index model from fields of the business model unit, wherein the business model unit comprises fields related to a preset business, the business model unit is bound with a first physical model, and the first physical model is bound with a first data table structure which is arranged in a physical database and used for constructing a data warehouse; a first index model creation module for creating a first index model based on the determined metric; and the binding object determining module is used for determining the physical model and the data table structure bound with the first index model based on the first physical model and the first data table structure.

According to another aspect of the embodiments of the present disclosure, there is also provided an index model management apparatus based on a data warehouse, including: a processor; and a memory coupled to the processor for providing instructions to the processor for processing the following processing steps: receiving first index model parameter information for creating an index model, wherein the index model is used for performing index analysis on data related to a predetermined service in a data warehouse; determining a business model unit for creating a first index model according to the parameter information of the first index model, and determining measurement related to the first index model from fields of the business model unit, wherein the business model unit comprises fields related to a preset business, the business model unit is bound with a first physical model, and the first physical model is bound with a first data table structure which is arranged in a physical database and used for constructing a data warehouse; creating a first metric model from the determined metric; and determining the physical model and the data table structure bound with the first index model based on the first physical model and the first data table structure.

In the embodiment of the present disclosure, the business model unit is established independently of the data warehouse, so that the index model in the embodiment is also established independently of the data warehouse. By constructing the index model in this embodiment, a general service person can complete the process without knowing the relationship between the table structure and the table structure or knowing the underlying technology, thereby saving the labor cost. Moreover, because the index model constructed according to the method is not limited by a specific data table in the data warehouse, the relationship between the index model and the actual business can be reflected in a business view, and the constructed index model can be migrated from one data warehouse to other data warehouses.

Furthermore, the method solves the technical problems that the method for constructing the index model in the prior art needs to solve the table structure and table relationship, can be completed by professional technicians and consumes a large amount of personnel cost, and the method is limited by the specific data tables in the data warehouse, cannot reflect the relationship between the model and the actual business from a business view and cannot transfer the constructed index model from one data warehouse to other data warehouses.

Drawings

The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the disclosure and together with the description serve to explain the disclosure and not to limit the disclosure. In the drawings:

fig. 1 is a block diagram of a hardware structure of a computer terminal for implementing the method according to embodiment 1 of the present disclosure;

fig. 2 is a schematic view of a scenario of a data warehouse-based index model management system according to embodiment 1 of the present disclosure;

fig. 3 is a schematic diagram of an operational principle architecture of a system of an index model management method based on a data warehouse according to embodiment 1 of the present disclosure;

fig. 4 is a schematic flow chart of a data warehouse-based index model management method according to a first aspect of embodiment 1 of the present disclosure;

fig. 5 is a schematic diagram of an interface for inputting metric model parameter information according to the first aspect of embodiment 1 of the present disclosure;

fig. 6 is a schematic diagram of first metric model parameter information according to the first aspect of embodiment 1 of the present disclosure;

FIG. 7 is a schematic diagram of an interface for inputting parameter information of a business model unit associated with a metric model according to a first aspect of embodiment 1 of the present disclosure;

fig. 8A and 8B are schematic diagrams of a physical model of a deterministic index model and a physical database data table structure according to a first aspect of embodiment 1 of the present disclosure;

fig. 9A to 9D are schematic diagrams of relevant descriptions of business model elements according to the first aspect of embodiment 1 of the present disclosure;

fig. 10 is a schematic diagram for explaining the metrics and the statistical granularity of the index model according to the first aspect of embodiment 1 of the present disclosure;

fig. 11 is a schematic diagram of second index model parameter information according to the first aspect of embodiment 1 of the present disclosure;

fig. 12 is a schematic interface diagram for inputting information required for building a second calibration model according to the first aspect of embodiment 1 of the present disclosure;

FIG. 13 is a diagram of a structure for building a second physical model and a second data table according to the first aspect of embodiment 1 of the present disclosure;

fig. 14 is a schematic diagram of version information of a first index model according to the first aspect of embodiment 1 of the present disclosure;

fig. 15 is a schematic diagram of version information of a second indexing model according to the first aspect of embodiment 1 of the present disclosure;

fig. 16 is a schematic diagram of a data warehouse-based metric model according to a first aspect of embodiment 1 of the present disclosure;

fig. 17 is a schematic diagram of an index model management apparatus based on a data warehouse according to embodiment 2 of the present disclosure; and

fig. 18 is a schematic diagram of an index model management apparatus based on a data warehouse according to embodiment 3 of the present disclosure.

Detailed Description

In order to make those skilled in the art better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure. It is to be understood that the described embodiments are merely exemplary of some, and not all, of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

According to the present embodiment, there is provided an embodiment of a data warehouse-based index model management method, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer-executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.

The method embodiments provided by the present embodiment may be executed in a server or similar computing device. Fig. 1 illustrates a hardware block diagram of a computing device for implementing a data warehouse-based metric model management method. As shown in fig. 1, the computing device may include one or more processors (which may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory for storing data, and a transmission device for communication functions. Besides, the method can also comprise the following steps: a display, an input/output interface (I/O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of the I/O interface), a network interface, a power source, and/or a camera. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the electronic device. For example, the computing device may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.

It should be noted that the one or more processors and/or other data processing circuitry described above may be referred to generally herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part in software, hardware, firmware, or any combination thereof. Further, the data processing circuitry may be a single, stand-alone processing module, or incorporated in whole or in part into any of the other elements in the computing device. As referred to in the disclosed embodiments, the data processing circuit acts as a processor control (e.g., selection of a variable resistance termination path connected to the interface).

The memory may be configured to store software programs and modules of application software, such as program instructions/data storage devices corresponding to the index model management method based on the data warehouse in the embodiment of the present disclosure, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, implements the index model management method based on the data warehouse of the application software. The memory may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory located remotely from the processor, which may be connected to the computing device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission device is used for receiving or transmitting data via a network. Specific examples of such networks may include wireless networks provided by communication providers of the computing devices. In one example, the transmission device includes a Network adapter (NIC) that can be connected to other Network devices through a base station to communicate with the internet. In one example, the transmission device may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.

The display may be, for example, a touch screen type Liquid Crystal Display (LCD) that may enable a business person to interact with a business person interface of the computing device.

It should be noted here that in some alternative embodiments, the computing device shown in fig. 1 described above may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that FIG. 1 is only one example of a particular specific example and is intended to illustrate the types of components that may be present in a computing device as described above.

Fig. 2 is a schematic view of a scenario of the index model management system based on a data warehouse according to the present embodiment. Referring to fig. 2, the system includes: terminal device 100 and data warehouse management platform 200. The service personnel inputs index model parameter information or an instruction for managing the index model to the terminal device 100, then the terminal device 100 sends the index model parameter information or the instruction to the data warehouse management platform 200, and the terminal device 100 and the data warehouse management platform 200 can interact with each other. It should be noted that the terminal device 100 and the data warehouse management platform 200 in the system may be adapted to the above-described hardware structure.

In addition, fig. 3 also shows an operational principle architecture design diagram of a system for implementing the index model management method based on the data warehouse according to the embodiment. The system operates on the data warehouse management platform 200 shown in fig. 2. Referring to fig. 3, the system is divided into three layers from top to bottom, an access layer, a service layer and a storage layer.

The access layer is the user's portal, which is consistent with the business model, through which the user accesses the system functionality. The package management entry, the Web service and ODBC service module: 1. the management entrance is an operation entrance of a human management model such as an administrator or a modeling engineer; the Web service exposes the model information in a Web way, and metadata and data of the model can be inquired through a Web service interface or interface; and 3, the ODBC service provides query service in a mode of carrying out SQL protocol communication through TCP connection, and a user can be connected with the ODBC service for operation by using ODBC driver or an SQL client supporting ODBC.

The service layer is the realization of system service logic and is responsible for receiving the operation request of the access layer, processing related services according to the request and responding. The data modeling management system is mainly embodied in the layer and mainly comprises five core function models: a model management and execution manager.

Model management is based on adding an index model on the basis of a business model. The business model, the physical model and the index model are metadata for model management, and the functional responsibility of the model is to manage the establishment, maintenance, query, tracking and the like of the model. Different model management is responsible for different responsibilities: the business model is modeled from a business angle and comprises business process management, dimension entity (namely dimension model) management and fact model management; the physical model is modeled from a technical angle and comprises table structure and table relation management, constraint and quality management and mapping relation management; the index model is based on the business model, and establishes indexes for evaluating business conditions from a business perspective, and comprises a primary index model and a derived index model.

The execution manager also adds the support to the index model on the basis of the business model, and the function responsibility is as follows: 1. constructing related SQL sentences according to the physical model and the adopted physical data warehouse, and then executing the SQL sentences in the physical data warehouse to create a physical structure; 2. and receiving SQL requests from the Web service and the ODBC service, then interpreting SQL statements, performing SQL conversion according to the adopted physical data warehouse and the metadata information inquired, converting the SQL statements into executable SQL statements of the physical data warehouse, then sending the SQL statements to the physical data warehouse for execution, processing a result returned by the physical data warehouse, and then returning the result to the Web service and the ODBC service.

The storage layer realizes data storage of various requirements and is divided into an application database, a service database and a data warehouse according to the function and the function. The functional functions are as follows: 1. the application database mainly stores model data (metadata) and system-related data; 2. the business database is used for storing business data in the business system, and the data in the databases are synchronized to the data warehouse by the ETL operation of the system; 3. the data warehouse stores operation type data extracted from the business system, data for constructing the data warehouse, data for constructing a theme, and the like.

In the above operating environment, according to the first aspect of the present embodiment, a data warehouse-based index model management method is provided, and the method is implemented by the data warehouse management platform 200 shown in fig. 2. Fig. 4 shows a flow diagram of the method, which, with reference to fig. 4, comprises:

s402: receiving first index model parameter information for creating an index model, wherein the index model is used for performing index analysis on data related to a predetermined service in a data warehouse;

s404: determining a business model unit for creating a first index model according to the parameter information of the first index model, and determining measurement related to the first index model from fields of the business model unit, wherein the business model unit comprises fields related to a preset business, the business model unit is bound with a first physical model, and the first physical model is bound with a first data table structure which is arranged in a physical database and used for constructing a data warehouse;

s406: creating a first metric model from the determined metric; and

s408: and determining the physical model and the data table structure bound with the first index model based on the first physical model and the first data table structure.

Specifically, referring to fig. 2, when a business person needs to create a model, first index model parameter information for creating an index model is input to the terminal device 100, so that the terminal device 100 sends the first index model parameter information to the data warehouse management platform 200. The data warehouse management platform 200 receives the first index model parameter information transmitted from the terminal device 100. Wherein the index model is used for index analysis of data related to the predetermined business in the data warehouse (corresponding to step S402).

For example, FIG. 5 shows a schematic diagram of an interface provided to business personnel for entering basic information for the first metric model parameter information. FIG. 6 shows basic information of first index model parameter information related to sales business inputted by business personnel, including: name: "order amount"; and (3) encoding: "order _ amount"; the index model type is as follows: "atomic index model"; data type: "string"; unit: "Yuan"; data field: "transaction Domain"; creation time: "2019-10-30"; updating time: "2019-10-30"; and associated description information, etc.

Further, fig. 7 shows an interface diagram for constructing the first index model displayed on the terminal device 100. Wherein the interface includes a business model unit for determining to build the first metric model and a control for the metric. Thus, the business person determines the metrics associated with the first metric model (i.e., "order amount") from the fields of the business model element associated with the predetermined business (e.g., sales business). Referring to FIG. 7, for example, the "from" column in the interface shows from which business model element the metrics needed to create the "order amount" metric model come. For example, the business model elements may be dimension model elements (i.e., "dimension entities" as shown in the interface) and/or fact model elements (i.e., "fact models" as shown in the interface). With respect to the dimension model unit and the fact model unit, detailed description will be made below.

Continuing with FIG. 7, the field "amount" in the "order" business model element can be seen as a measure of the creation of the first metric model "order amount". Similarly, business personnel can also select related fields in other business model elements as metrics for creating an "order amount" metric model. Wherein a business model element (e.g., an order) contains fields related to a predetermined business (e.g., a sales business).

Thus, the terminal device 100 can transmit the first index model parameter information for creating the first index model "amount of order" input through the interfaces shown in fig. 5 and 7 to the data warehouse management platform 200 in response to the above operation by the business person. Then, the data warehouse management platform 200 receives the first index model parameter information transmitted from the terminal device 100.

Further, the data warehouse management platform 200 determines a business model unit for creating the first index model according to the first index model parameter information, and determines a metric related to the first index model from a field of the business model unit. Wherein the business model unit includes a field related to the predetermined business, the business model unit is bound with the first physical model, and the first physical model is bound with a first data table structure provided in the physical database and used for constructing the data warehouse (S404).

Specifically, the data warehouse management platform 200 determines the relevant business model unit for creating the first index model "order amount" according to the first index model parameter information. For example: the data warehouse management platform 200 determines a business model unit "order" for creating the first index model "order amount" according to the parameters input by the business person through the terminal device 100 on the interface shown in fig. 7, and determines "amount" as a measure related to the first index model "order amount" from fields (user, commodity, amount, time, and region) of the business model unit "order".

Further, referring to FIG. 3, in the service layer, the business model elements are bound to the corresponding physical models. Specifically, for example, the business model unit "order" is bound to the corresponding physical model (e.g., the name of the physical model may also be "order"). For example, the physical model "order" may include fields such as "user", "goods", "amount", "time", and "region" so as to correspond to the field of the business model unit "order". And the physical model order is also bound with the corresponding physical database table structure, so that the data warehouse is constructed through the physical database table structure. And then, associating the physical database table structure with the source end data, thereby realizing the ETL process of transmitting the source end data to the data warehouse. Therefore, index analysis can be carried out on the data related to the sales business in the data warehouse by using the first index model of the order amount.

Further, data warehouse management platform 200 creates a first index model "order amount" based on the determined metric "amount". Specifically, referring to FIG. 3, data warehouse management platform 200 may create a first metric model, "order dollar amount," in the service layer of the system, for example.

And finally, the data warehouse management platform determines a physical model bound with the order amount of the first index model and a physical database table structure based on the physical model of the order of the business model unit and the physical database table structure bound with the physical model.

Specifically, for example, as shown with reference to fig. 8A, since the first index model "order amount" is derived from the business model unit "order" (i.e., fact model "order"), not from other index models, the first index model "order amount" is a native index model. Therefore, the first index model "order amount" and the business model unit "order" have the same finest statistical granularity, and the physical model and the physical database table structure bound by the business model unit "order" can be used as the physical model and the physical database table structure bound by the first index model "order amount".

This has the advantage that redundant physical model data and table structures of the physical database do not have to be built. Index analysis is carried out in a physical database table structure bound with the business model unit order by using the first index model order amount. Thereby saving the data storage resources occupied by the system.

Further, referring to fig. 8B, as another possibility, the data warehouse management platform 200 may also generate the same physical model as the physical model "order" and the same physical database table structure as the physical database table structure "order" and determine them as the physical model and the physical database table structure bound to the first index model "order amount". Furthermore, the physical database table structure bound to the first index model "order amount" and the physical database table structure "order" may be associated with the same source data.

For ease of understanding, the concept of "business model element" presented herein is further described below:

most data warehouse development tools now build a model of a data warehouse in a tri-modal approach to the Inmon data warehouse concept, while a model that builds a data warehouse using the Kimball dimensional modeling concept is built using a counter-modal approach based on a physical database.

Although the created data warehouse model can also be used for data analysis by professional data technicians from a technical perspective, the model only has technical elements and can only reflect the relationship between the table structure and the table structure, and the business meaning is lacked, so that the relationship between the model and the actual business is not reflected from a business perspective. Therefore, when a business person analyzes data based on the model, the business person does not know the business process from which the model and the data originate, the business meaning of the data is not clear, and the data is difficult to analyze and trace.

In view of this, the present solution proposes the concepts of business model elements and physical models. Wherein, referring to fig. 3, the business model unit may be disposed in a model management module of the service layer, for example. And, the business model element can be created according to the information related to the subscribed business inputted by the business person.

Referring to FIG. 9A, a user may enter modeling parameters through a visualization interface provided by the management portal of the access stratum. The modeling parameters may for example comprise basic information for creating relevant business model elements for a predefined business, such as: name, code, category, data field, description, etc., and may further include structural information of a service model unit related to a predetermined service (e.g., field name, field value of a specific service). In one specific example, the predetermined business may be an order business, and the first modeling parameter associated with the order business may include basic information of a business model unit associated with the order business. The business model element may for example be a business model element related to: merchant, group, order status, seller, merchandise information, date, etc.

Taking the basic information entered by the user for creating the "order" business model unit related to the order business as an example, the basic information of the "order" business model unit entered by the user (i.e., "entity information" shown on the interface) is shown in fig. 9B, and includes the following information related to the business model unit: name: "order form"; the category: "common level"; and (3) encoding: "Order"; creation time: "2019-10-30"; scope of action: "transaction Domain"; description of a business model element; and update time: "2019-10-30".

In addition, referring to fig. 9C, the user may further input field information (i.e., "dimension name" and "dimension code") related to the "order" business model unit as part of the modeling parameters through the visualized interface, including: "user", "merchandise", "amount", "time", and "region", etc. Further, as shown with reference to fig. 9C, for each field, an attribute may also be defined. For example, attributes may include: dimension codes, dimension names, data types (e.g., string or var, etc.), constraints (primary key constraints or foreign key constraints, etc.), and associated descriptions, among others.

Further, a model management module of the system creates a business model element based on the modeling parameters, wherein the business model element includes fields associated with the predetermined business. That is, the system creates a business model element from the modeling parameters entered by the user. Further, a model management module of the system constructs a physical model associated with the business model unit and creates a data table structure in the physical database corresponding to the physical model. Wherein a physical model associated with the predetermined business can be created by the system automatically or manually by a technician in accordance with the business model element.

Then, the system binds the business model unit and the physical model to realize the association between the business model unit and the data table structure, thereby constructing a data warehouse based on the business model unit. That is, the fields of the physical data model and the fields of the business model unit are correspondingly bound, for example: the fields of the physical model corresponding to the fields (user, item, amount, time, and region) of the "order" business model element may also include fields such as "user", "item", "amount", "time", and "region". Therefore, the system can associate the business model unit with the data table structure corresponding to the physical model according to the binding relationship between the business model unit and the physical model, so as to associate the business model unit with the data table structure in the physical database.

In addition, referring to fig. 9D, the user may associate a plurality of business models through a visual interface, thereby constructing a business logic model. For example, a user may associate a "merchant" dimension model unit, a "group information" dimension model unit, an "order state" dimension model unit, an "organization information" dimension model unit, a "member information" dimension model unit, and the like with an "order" fact model unit through a visualization interface, so as to generate modeling parameters reflecting an association relationship between the dimension model unit and the order fact model unit. The system can then build a business logic model based on the modeling parameters.

Therefore, through the mode, the data modeling management system firstly receives modeling parameters related to the preset service, then creates a service model unit comprising fields related to the preset service according to the modeling parameters, then creates a physical model according to the service model unit, and finally binds the service model unit and the physical model to construct a data warehouse related to the preset service. Therefore, compared with the prior art that the dimensionality data warehouse is constructed by using the inverse normal mode on the basis of the physical database, the method and the system can construct the business model from the business perspective without being limited by the data table in the physical database. That is, according to the present solution, a business model unit may be first constructed according to an actual business, then a physical model related to a predetermined business is constructed based on the established business model unit (which may be automatically by a system or manually by a technician), and then a user (a business or a technician) may analyze and trace data related to the predetermined business according to the created business model. The modeling process of the data warehouse may thus not be constrained by the data tables in the physical database, and the data analysis is no longer restricted to the technician.

Further, when performing index analysis on the constructed data warehouse, according to the technical solution of this embodiment, firstly, a service person inputs index model number information for creating an index model at the terminal device 100, and the terminal device 100 sends index model parameter information to the data warehouse management platform 200. Then, the data warehouse management platform 200 determines a business model unit for creating the index model according to the index model parameter information. Finally, the data warehouse management platform 200 creates an index model according to the business model unit and binds the index model with the physical database table structure.

The business model unit in this embodiment is established independently of the data warehouse, and thus the index model in this embodiment is also established independently of the data warehouse. Through the way of constructing the index model in the embodiment, ordinary business personnel can complete the creation and management of the index without knowing the relation between the table structure and the underlying technology, so that the labor cost is saved. Moreover, because the index model constructed according to the method is not limited by a specific data table in the data warehouse, the relationship between the index model and the actual business can be reflected in a business view, and the constructed index model can be migrated from one data warehouse to other data warehouses.

Furthermore, the method solves the technical problems that the method for constructing the index model in the prior art needs to solve the table structure and table relationship, can be completed by professional technicians and consumes a large amount of personnel cost, and the method is limited by the specific data tables in the data warehouse, cannot reflect the relationship between the model and the actual business from a business view and cannot transfer the constructed index model from one data warehouse to other data warehouses.

Optionally, the operation of creating a first metric model from the determined metrics comprises: determining a first expression and/or a first statistical granularity for defining a first index model according to the parameter information of the first index model; and creating a first index model from the metrics using the first expression and/or the first statistical granularity.

For example, in the present scheme, the native index model may be defined by the following aspects: metrics, computational expressions, and granularity. Namely, the native index model can calculate the filtered and screened metrics by using the calculation expression on the basis of filtering and screening the metrics by using the granularity information.

Specifically, the business person may input a calculation formula for creating the first index model as part of the first index model parameter information in a "calculation formula" input box of the interface shown in fig. 7. Thus, the data warehouse management platform 200 determines the first expression for defining the first index model according to the information input by the service person at the terminal device 100, and as shown in fig. 7, the calculation formula may be a combination of calculations such as SUM (SUM), COUNT (COUNT), maximum value (MAX), minimum value (MIN), Average Value (AVG), SUM of values meeting a specific condition (SUMIF), and the like. In addition, the business personnel can also determine the dimension for defining the statistical granularity in the column "statistical granularity" of the interface shown in FIG. 7.

Specifically, the dimension for defining the statistical granularity may be selected from the following dimensions: namely, fields (dimensions) that are not determined as metrics among fields (dimensions) of the business model unit for constructing the first metric model.

For example, referring to FIG. 7, the business person determines to build a first metric model "order amount" based on the business model element "order". And the business determines the "amount" of a field (also referred to as a "dimension") in the business model unit "order" as a measure of building the first metric model "order amount". The business may select a dimension for defining the statistical granularity from other fields (also referred to as "dimensions") of the business model element "order". That is, the business may determine the dimensions used to define the statistical granularity from the "user" dimension, the "goods" dimension, the "time" dimension, and the "region".

For example, a first metric model "order amount" that is a native metric model may be defined as the sum of the fields "amount" in the "order" business model unit, which may be expressed as: the order amount & [ [ granularity ] & user dimension + commodity dimension + time dimension + region dimension ]. The data corresponding to the field amount in the order business model unit can be screened by using the statistical granularity defined by the user dimension, the commodity dimension, the time dimension and the region, and then the screened data are summed, so that the numerical value corresponding to the order amount index model is obtained.

Data warehouse management platform 200 may thus create a first index model "amount of order" from the metric "amount" using expressions and/or statistical granularity.

Thus, in this way, the salesperson can create the first index model according to the measurement by means of various ways such as granularity statistics and/or expressions, so that the data related to the subscribed service can be more accurately and comprehensively analyzed by using the first index model.

Optionally, the operations of determining a business model unit for creating the first metric model and determining a metric related to the first metric model from a field of the business model unit include: determining a dimension model unit or a fact model unit which is associated with the predetermined business and is used as a business model unit according to the first index model parameter information, wherein the dimension model unit comprises a field for describing a dimension for analyzing the predetermined business, and the fact model unit comprises a field for describing a fact associated with the predetermined business; and determining a metric associated with the first metric model from a field of the dimension model unit or the fact model unit.

Specifically, referring to fig. 7 and fig. 9A to 9D, the business model unit for constructing the index model may include two types, for example: dimension model elements (i.e., "dimension entities" shown in the interface) and fact model elements (i.e., "fact models" shown in the interface). Wherein the fact model unit includes a field for describing the primary fact. For example, the "order" fact model element shown in FIG. 7 is used to describe the fact of a transaction between a buyer and a seller. And wherein the "order" fact model element includes fields such as "user", "goods", "amount", "time", and "region". So that the fact of a transaction can be described by these fields.

Furthermore, although not shown in the figures, for example, a "members" dimension model unit may be used to analyze the business from the dimension of the members. And wherein the "Member" dimension model element includes fields such as "name", "rating", "points", and "age". Thus, through these fields, the business can be analyzed in the dimension of "membership". For example, information on the name, rating, point, and age of a member related to a business is analyzed.

Therefore, when a business person creates the first index model, the business person can select proper measurement from two different types of business model units, namely a real model unit and a dimension model unit, to create the first index model. The data warehouse management platform 200 may determine a dimension model unit or a fact model unit associated with a predetermined business and serving as a business model unit, and determine a field serving as a metric in the dimension model unit or the fact model unit, according to the first index model parameter information. Further, data warehouse management platform 200 may create a first index model as a native index model from a first expression entered by the business person. Thus, in the above manner, the first index model, which is a native index model, may be created using a preset fact model unit or a dimension model unit.

Therefore, the method for constructing the index model in the embodiment is different from the prior art. The existing index is directly constructed on a data warehouse of a physical database through three-range modeling or dimension modeling. The data warehouse construction index based on the three-model modeling is characterized in that technical personnel analyze indexes and data from the technical perspective, and then the indexes and the data are extracted, converted and loaded and finally summarized to an index result table. When an index is built on a data warehouse built from bottom to top in a mode of a counter form on a physical database based on a Kimball dimension modeling idea, the Kimball dimension modeling idea does not provide an index building method, so a dimension table and a fact table which are used for describing predetermined business and are built on the basis of the physical database, and the index is built from a technical point of view based on the fact table and the dimension table, and business meaning and relevant business information are lacked. The method is still a scheme for constructing and managing indexes from bottom to top, so that the existing method for constructing the index model in the background art needs to solve the relation between a table structure and a table, needs professional technicians to complete the method, and consumes a large amount of personnel cost.

By the method of the embodiment, in the process of creating the data warehouse model, the dimension model unit and the fact model unit are firstly built in a top-down mode, and then the native index model is built based on the built dimension model unit and the fact model unit, so that the built index model can be associated with the business, and the relation between the index model and the business is reflected by the dimension model unit and the fact model unit.

Further, referring to FIG. 9D, fact model elements may be associated with multiple dimension model elements to build a business logic model. For example, a user can associate a "merchant" dimension model unit, a "group information" dimension model unit, an "order state" dimension model unit, an "organization information" dimension model unit, a "member information" dimension model unit and the like with an "order" fact model unit through a visual interface, so that the system can construct a corresponding business logic model.

In this case, when the business builds the metric model, the dimensions used to define the statistical granularity are not limited to only the dimensions in the fact model unit "order," but may also be the dimensions (i.e., fields) in the dimension model unit associated with the fact model unit "order. As long as there are no fields selected as metrics.

Specifically referring to fig. 10, the native index model is created based on a fact model unit (or may be a dimension model unit, which is not described herein). And the fact model unit (or may be a dimension model unit, which is not described herein) a has associated dimension model units B and C to form a business logic model.

The fact model unit a includes, for example, fields 1 to 6, the dimension model unit B includes fields 7 to 9, and the dimension model unit C includes fields 10 to 12. Where fields 1 through 3 of fact model unit A are determined as metrics for building the native metric model, then fields 4 through 6 of fact model unit A and fields 7 through 12 of dimension model units B and C may both be used as dimensions defining the statistical granularity. That is, at least one field from fields 4 to 12 may be selected as a dimension defining the statistical granularity.

Therefore, by the mode, more dimensions can be utilized to define the statistical granularity, so that index analysis can be performed on data from the statistical granularity of a plurality of different angles.

Optionally, the operation of receiving the first metric model parameter information includes: first metric model parameter information is received from a remote terminal device.

Specifically, the data warehouse management platform 200 receiving the first metric model parameter information for creating the native metric model may be receiving the first metric model parameter information from a remote terminal device 100. For example, the first index model parameter information may be input by a terminal device 100 that is remote from a service person, and then the terminal device 100 transmits the first index model parameter information to the data warehouse management platform 200. Of course, the first index model parameter information may be input from the data warehouse management platform 200 by a manager of the data warehouse platform 200.

Data warehouse platform 200 thus obtains the first index model parameter information for use in creating the first index model. In addition, the method only needs business personnel to input the parameter information of the index model, and does not need to pay attention to the underlying technology, so that the labor cost is saved.

Optionally, the operation of receiving the first metric model parameter information includes: providing a first interactive interface provided with a first control, wherein the first control is used for inputting parameter information of a first index model; and receiving first index model parameter information input through the first control in response to a trigger received by the first interactive interface.

Specifically, as shown with reference to fig. 5-7, data warehouse management platform 200 may also provide an interactive interface provided with controls. The business personnel or the manager of the data warehouse management platform 200 can input the parameter information of the first index model in the control, so that the operation efficiency of the business personnel is improved. Data warehouse management platform 200 then receives the metric model parameter information entered via the controls in response to the trigger received by the interface. In the embodiment, the display is performed on the business personnel in the form of the interactive interface, so that the business personnel only need to input the index model parameter information in the control, the operation is convenient, and the use feeling of the business personnel is improved.

Optionally, the method further comprises: receiving second index model parameter information for creating an index model; determining an index model set used for creating a second index model according to the parameter information of the second index model; and creating a second index model according to the index models in the index model set.

Specifically, the business person may create a second index model as a derived index model in addition to the first index model as a native index model. Unlike the native index model constructed based on the business model unit, the derived index model is constructed based on other index models.

For example, when the service person creates the second index model of the index model, the second index model parameter information may be input through the terminal device 100. For example, taking the derived index model "trade amount on double eleven lines" as an example, fig. 11 shows basic information of the second index model parameter information input by the business personnel, including: name: "double eleven on-line transaction amount"; and (3) encoding: "online _ amount"; the index model type is as follows: "derived index model"; data type: "double"; unit: "Yuan"; data field: "transaction Domain"; creation time: "2019-10-30"; updating time: "2019-10-30"; and associated description information, etc. Further, referring to fig. 12, the service personnel may determine the index model for constructing the second index model through the visual interface. Referring to fig. 12, the service person may determine an index model for constructing the second index model from index models such as "order amount", "number of products", "number of consumers", and "order number", for example.

Thus, the data warehouse management platform 200 determines an index model set (i.e., at least one index model of index models such as "order amount", "number of goods", "number of consumers", and "order quantity") for creating the second index model, based on the second index model parameter information received from the terminal device 100. And creating a second index model according to the index models in the determined index model set.

In this manner, a business may thus be allowed to build more complex derived index models in a top-down manner using existing index models. The concept of "derived index" also exists in the prior art. However, as mentioned above, the generation of the "derived index" is still established in a bottom-up manner based on the table structure and table relationships of the database, and thus needs a skilled person to complete. In view of the above, the present application proposes a "derived index model" to allow business personnel to perform index analysis on data in a top-down manner from the business perspective.

Optionally, creating a second index model according to the index models in the index model set, further comprising: determining a second expression for defining a second index model according to the parameter information of the second index model; and creating a second index model according to the index models in the index model set and the second expression.

In particular, data warehouse management platform 200 determines a second expression for defining a second index model based on the second index model parameter information, e.g., the second index model may be determined based on a statistical period, a statistical range, a native index model, a summary granularity, and so on. The statistical period corresponds to the column of "statistical period" shown in fig. 12, and the statistical range corresponds to the column of "statistical range" shown in fig. 12.

Further, when a business person creates a second index model as a derived index model, the data warehouse management platform 200 creates the second index model according to the index model in the index model set and the second expression. For example, the second index model to be created by data warehouse management platform 200 is "money consumed for boys," which may be expressed as: in the case of the man consumption amount, SUM ("consumption amount") and statistical range ("WHERE six") and granularity ("product dimension + time dimension + area dimension") are set, WHERE "consumption amount" is the native index model in the index model set, and "statistical range" is whese six ("male") and corresponds to the statistical range in the second expression. Or, for example, the second index model to be created by data warehouse management platform 200 is "last seven days of andrological spending amount," which may be expressed as: the recent seven-day andreans consumption amount ═ the recent seven-day & SUM ([ consumption amount ]) & [ statistical range ═ WHERE six ═ male & [ granularity ═ commodity dimension + region dimension ].

Therefore, by establishing the complex derivative index model on the basis of the ordinary primary index model, the establishment difficulty of the complex index model can be reduced by establishing the complex index model in the method, and the primary index model can be used for multiple times to increase the reuse rate of the index model. Therefore, the technical problems that the difficulty of establishing a complex index model based on a data warehouse of dimensional modeling is high, and the index model multiplexing rate is not high can be solved.

Optionally, the method further comprises: constructing a second physical model related to the second index model, and creating a second data table structure corresponding to the second physical model in the physical database; and binding the second index model with the second physical model to realize the association between the second index model and the second data table structure.

Specifically, after building the second index model, the data warehouse management platform 200 may continue to build a second physical model associated with the second index model and create a second data table structure in the physical database corresponding to the second physical model. Then, the data warehouse management platform 200 binds the second index model with the second physical model, so as to realize the association between the second index model and the second data table structure.

Specifically, referring to fig. 13, for example, the native index model 1 is created from fields 1 to 3 of a fact model unit (or dimension model unit) a as metrics. The native index model 2 is created as a measure from the fields 13 to 15 of the fact model unit (or dimension model unit) B. The second index model may be created, for example, based on the native index model 1 and the native index model 2. And upon creating the second index model, the data warehouse management platform 200 builds a second physical model associated with the second index model, wherein the fields of the second physical model include, for example, fields 1-3 and fields 13-15 that are metrics of the native index model 1 and the native index model 2. In turn, the data warehouse management platform 200 builds a corresponding second data table structure on the physical database, where the second data table structure may also include, for example, fields 1 through 3 and fields 13 through 15. The data warehouse management platform 200 then binds the second index model to the second physical model, thereby enabling association between the second index model and the second data table structure.

Specifically, the data warehouse management platform 200 determines an associated physical model of the second index model according to the index models in the index set; and constructing a physical database table structure corresponding to the associated physical model of the second index model. For example, data warehouse management platform 200 determines an associated physical model for a second index model (e.g., the last seven days of man spending money) from the index models in the index set, and data warehouse management platform 200 builds a physical database table structure corresponding to the second index model (e.g., the last seven days of man spending money).

In this manner, a business may thus be allowed to build more complex derived index models in a top-down manner using existing index models. The concept of "derived index" also exists in the prior art. However, as mentioned above, the generation of the "derived index" is still established in a bottom-up manner based on the table structure and table relationships of the database, and thus needs a skilled person to complete. In view of the above, the present application proposes a "derived index model" to allow business personnel to perform index analysis on data in a top-down manner from the business perspective.

Optionally, the operation of receiving second metric model parameter information for creating the metric model includes: second indexing model parameter information is received from a remote terminal device.

Specifically, the data warehouse management platform 200 receiving the second index model parameter information for creating the index model may be receiving the second index model parameter information from the remote terminal device 100. For example, the second index model parameter information may be input by the terminal device 100 that is remotely located by the service person, and then the terminal device 100 transmits the second index model parameter information to the data warehouse management platform 200. Of course, the second index model parameter information may also be input from the data warehouse management platform 200 by a manager of the data warehouse platform 200.

Data warehouse platform 200 thus obtains second index model parameter information for use in creating the second index model. In addition, the method only needs business personnel to input the parameter information of the index model, and does not need to pay attention to the underlying technology, so that the labor cost is saved.

Optionally, the operation of receiving second metric model parameter information for creating the metric model includes: providing a second interactive interface provided with a second control, wherein the second control is used for inputting index model parameter information associated with the derived index model to be created; and receiving second index model parameter information input through a second control in response to a trigger received by the second interactive interface.

In particular, as shown with reference to fig. 11-12, the data warehouse management platform 200 receiving information for creating the second index model parameter may also provide a second interactive interface provided with a second control. The business personnel or the manager of the data warehouse management platform 200 can input the index model parameter information associated with the derived index model to be created in the second control, so that the operation efficiency of the business personnel is improved. Data warehouse management platform 200 then receives second index model parameter information entered via the second control in response to a trigger received via the second interface. In the embodiment, the display is performed on the business personnel in the form of the interactive interface, so that the business personnel only need to input the index model parameter information in the second control, the operation is convenient, and the use feeling of the business personnel is improved.

Optionally, the operation of creating a second index model according to the index model in the index model set and the second expression further includes: determining whether the metric models in the set of metric models are created based on the same fact model unit, wherein the fact model unit comprises a field describing a fact associated with a predetermined service; and in the case that the index models in the index model set are determined to be created based on the same fact model unit, creating a second index model according to the index models in the index model set and the second expression.

Specifically, in the process of creating the second index model by the data warehouse management platform 200 according to the index model in the index model set and the second expression, it needs to be determined whether the index models in the index model set are created based on the same fact model unit. Wherein the fact model element includes a field describing a fact associated with the predetermined service. For example, the first index model in the index model set has a spending amount index model and a sales amount index model, and the fact model units of the two first index models are created based on the same order fact model (for example, based on a measure "order amount" selected from the order fact model), that is, the first index model spending amount index model and the first sales amount index model are created based on the same fact model units.

Further, the data warehouse management platform 200 creates a second index model from the index models in the index model set and the second expression in the case where it is determined that the index models in the index model set are created based on the same fact model unit. For example, the first index model spending amount index model and the first index model sales index model described above are created based on the same fact model unit, in which case the data warehouse management platform 200 creates a second index model from the index models in the index model set and the second expression.

Therefore, in this case, since the set of index models for creating the second index model is created based on the same fact model unit, the finest granularity (e.g., the fact model unit) of the second index model is consistent, which is beneficial to managing the second index model and improving the management efficiency.

For example, the native index models "spending amount" and "total number of goods" in the set of index models are both created from the same "order" fact model element. Wherein the "order" fact model element comprises, for example, two fields "amount" and "quantity of goods". The expressions of "consumption amount" and "total number of commodities" are as follows:

the [ consumption amount ], [ SUM ([ amount ]), [ granularity ], [ user dimension + commodity dimension + time dimension + region dimension ];

product sales ═ SUM ([ product quantity ]) & [ [ granularity ] } user dimension + product dimension + time dimension + area dimension ];

further, the expression of the derived index model "average commodity price" created using the native index model "consumption amount" and "commodity sales" is as follows:

the average price of a commodity is AVG ([ amount of consumption, [ quantity of commodity sales ]) & [ granularity ] + user dimension + commodity dimension + time dimension + region dimension ].

As described above, since the native index model "consumption amount" and "commodity sales" for creating the derived index model "commodity average price" are created based on the same "order" fact model unit, the granularity thereof is defined by the user dimension, the commodity dimension, the time dimension, and the region dimension, so that the finest granularity is uniform.

Optionally, the operation of creating the second index model according to the index models in the index model set and the second expression includes, in the case that it is determined that the index models in the index model set are created based on different fact model units, performing the following operations: determining whether different fact model elements are associated with a common dimension, wherein a dimension model element includes a field describing a dimension for analyzing a predetermined business; and under the condition that the fact model units are judged to be associated with the common dimension, creating a second index model according to the index models in the index model set and the second expression.

Specifically, in the process that the data warehouse management platform 200 creates the second index model according to the index model in the index model set and the second expression, the data warehouse management platform 200 determines that the index model in the index model set is created based on different fact model units. For example, the first index model in the index model set comprises a consumption amount index model and a refund amount index model, one of the two first index models is created based on a refund fact model unit model, and the other one of the two first index models is created based on a consumer number fact model unit and is created based on a different fact model unit. In this case, the data warehouse management platform 200 determines whether the index models in the index model set are associated with a common dimension (i.e., whether the dimension for constructing the spending amount index model and the dimension for constructing the refund amount index model intersect), for example, the data warehouse management class platform 200 determines that the spending amount index model and the refund amount index model both have a user dimension, a commodity dimension, a time dimension, and a region dimension.

Further, the data warehouse management platform 200 creates a second index model according to the index models in the index model set and the second expression in the case that it is determined that the index models in the index model set are associated with the common dimension. For example, a first index model "spending amount" and a first index model "refund amount" are associated with a common dimension (e.g., a user dimension, a commodity dimension, a time dimension, and a region dimension), in which case data warehouse management platform 200 creates a second index model from the index models in the set of index models and a second expression.

For example, the native index model "spending amount" in the set of index models is created from the metric "amount" selected from the "order" fact model element.

Another native metric model "refund amount" in the set of metric models is created from a selected metric "amount" from the "refund" fact model. The expressions "spending amount" and "refund amount" are as follows:

the consumption amount is SUM (amount) + the granularity is user dimension + commodity dimension + time dimension + region dimension;

the "refund amount" is SUM (amount) + the "granularity" is user dimension + commodity dimension + region dimension ";

further, the expression of the derived index model "order fulfillment rate" created using the native index models "consumption amount" and "refund amount" is as follows:

the order fulfillment rate is ═ ([ amount of consumption-refund amount ]) + the granularity ═ user dimension + commodity dimension + region dimension ].

As shown above, the native index models "amount consumed" and "amount refunded" due to the creation of the derived index model "order fulfillment rate" are created based on different fact model elements (i.e., "order" fact model element and "refund" fact model). But due to the fact that both model elements are associated with common dimensions "user dimension", "goods dimension" and "region dimension". The derived metric model can be created. And the finest granularity of the derived index model is determined by the public dimension of 'user dimension', 'commodity dimension' and 'region dimension'.

Furthermore, if the "order" fact model unit and the "return" fact model do not have a common dimension, this means that when the data is screened using the dimensions of the two fact model units, the resulting data will be null data. So in this case it will not be possible to create a derived metric model.

Therefore, the index model set used for creating the second index model is created based on the same dimension model unit, and the finest granularity (for example, the dimension model unit) of the second index model is consistent, so that the second index model is managed conveniently, and the management efficiency is improved.

In addition, referring to fig. 14 and fig. 15, version information of the first index model and the second index model is provided in the present embodiment, and different versions are saved, so that the business staff can trace and trace later.

Referring to fig. 16, the index model is divided into three layers in the present embodiment, from bottom to top: the first layer is a data warehouse layer, the data warehouse layer is a data warehouse based on dimension modeling, metadata in the data warehouse comprises business metadata, and the description of the business metadata is based on a star-shaped or snowflake-shaped medium dimension table and a fact table. The second layer is a native index model layer, is used for constructing and maintaining a native index model, and is based on the basis that the first layer data warehouse layer provides service metadata (dimension tables and fact tables) to construct the native index model from a service perspective. The process of constructing the primary index model generally comprises the following steps: 1. analyzing the service requirement; 2. selecting a business process; 3. selecting a fact model; 4. selecting a correlation metric; 5. determining a calculation expression; 6. and determining the statistical granularity. The third layer is a derived index model layer, which is used for constructing and maintaining a derived index model, and is a derived index model required by business construction based on the primary index model provided by the second layer primary index model layer, and the process of constructing the derived index model generally comprises the following steps: 1. analyzing the service requirement; 2. selecting a business process; 3. selecting a related native index model; 4. determining a statistical period; 5. determining a calculation expression; 6. determining a statistical range; 7. and determining the statistical granularity.

Further, referring to fig. 1, according to a second aspect of the present embodiment, a storage medium 104 is provided. The storage medium 104 comprises a stored program, wherein the method of any of the above is performed by a processor when the program is run.

Thus, according to the present embodiment, the business model unit is established independently of the data warehouse, and thus the index model in the present embodiment is also established independently of the data warehouse. By constructing the index model in this embodiment, a general service person can complete the process without knowing the relationship between the table structure and the table structure or knowing the underlying technology, thereby saving the labor cost. Moreover, because the index model constructed according to the method is not limited by a specific data table in the data warehouse, the relationship between the index model and the actual business can be reflected in a business view, and the constructed index model can be migrated from one data warehouse to other data warehouses.

Furthermore, the method solves the technical problems that the method for constructing the index model in the prior art needs to solve the table structure and table relationship, can be completed by professional technicians and consumes a large amount of personnel cost, and the method is limited by the specific data tables in the data warehouse, cannot reflect the relationship between the model and the actual business from a business view and cannot transfer the constructed index model from one data warehouse to other data warehouses.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.

Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.

Example 2

Fig. 17 shows a data warehouse-based index model management apparatus 1700 according to the present embodiment, where the apparatus 1700 corresponds to the method according to the first aspect of embodiment 1. Referring to fig. 13, the apparatus 1700 includes: a first parameter information receiving module 1710, configured to receive first index model parameter information used to create an index model, where the index model is used to perform index analysis on data related to a predetermined service in a data warehouse; a business model unit determining module 1720, configured to determine, according to the first index model parameter information, a business model unit for creating a first index model, and determine a metric related to the first index model from a field of the business model unit, where the business model unit includes a field related to a predetermined business, the business model unit is bound to a first physical model, and the first physical model is bound to a first data table structure that is disposed in the physical database and used for building a data warehouse; a first index model creation module 1730 for creating a first index model based on the determined metric; and a bound object determining module 1740 configured to determine the physical model and the data table structure bound to the first indicator model based on the first physical model and the first data table structure.

Optionally, the first metric model creation module 1330 includes: the first expression submodule is used for determining a first expression and/or a first statistical granularity for defining the first index model according to the parameter information of the first index model; and a create first metric model sub-module configured to create the first metric model according to the metric using the first expression and/or the first statistical granularity.

Optionally, the determine business model unit module 1320 includes: a determining submodule for determining a dimension model unit or a fact model unit associated with the predetermined service and serving as a service model unit according to the first index model parameter information, wherein the dimension model unit includes a field describing a dimension for analyzing the predetermined service, and the fact model unit includes a field describing a fact associated with the predetermined service; and a selection submodule for selecting a field from the dimension model unit or the fact model unit as a metric.

Optionally, the receive first parameter information module 1310 includes: and the receiving submodule is used for receiving the first index model parameter information from the remote terminal equipment.

Optionally, the receive first parameter information module 1310 includes: providing a submodule for providing a first interactive interface provided with a first control, wherein the first control is used for inputting index model parameter information associated with a native index model to be created; and the response submodule is used for receiving the first index model parameter information input through the first control in response to the trigger received by the first interactive interface.

Optionally, the apparatus 1300 further includes: the receiving second parameter information module is used for receiving second index model parameter information used for creating an index model; the index set determining module is used for determining an index model set used for creating a second index model according to the parameter information of the second index model; and the second index model creating module is used for creating a second index model according to the index models in the index model set and the second expression.

Optionally, creating a second index model module, comprising: the second expression determining submodule is used for determining a second expression for defining a second index model according to the parameter information of the second index model; and a second index model creating submodule, configured to create a second index model according to the index model and the second expression in the index model set.

Optionally, the method further comprises: the second physical model building module is used for building a second physical model related to the second index model and creating a second data table structure corresponding to the second physical model in the physical database; and the binding module is used for binding the second index model with the second physical model to realize the association between the second index model and the second data table structure.

Optionally, the module for receiving second parameter information includes: and the receiving submodule is used for receiving the second index model parameter information from the remote terminal equipment.

Optionally, the module for receiving second parameter information includes: providing a submodule for providing a second interactive interface provided with a second control, wherein the second control is used for inputting index model parameter information associated with the derived index model to be created; and the response submodule is used for receiving second index model parameter information input through the second control in response to the trigger received by the second interactive interface.

Optionally, creating a second index model submodule, further comprising: a judging unit configured to judge whether or not index models in an index model set are created based on the same fact model unit, wherein the fact model unit includes a field describing a fact associated with a predetermined service; and creating a second index unit for creating a second index model from the index models in the index model set and the second expression in the case where it is determined that the index models in the index model set are created based on the same fact model unit.

Optionally, the creating a second index model sub-module, in a case that it is determined that the index models in the index model set are created based on different fact model units, further includes the following units: a determining unit for determining whether different fact model units are associated with a common dimension; and a second index model creating unit configured to create a second index model according to the index model and the second expression in the index model set, in a case where it is determined that the different fact model units are associated with the common dimension.

Thus, according to the present embodiment, by the index model management apparatus 1700 based on a data warehouse, the business model unit is established independently of the data warehouse, and thus the index model in the present embodiment is also established independently of the data warehouse. By constructing the index model in this embodiment, a general service person can complete the process without knowing the relationship between the table structure and the table structure or knowing the underlying technology, thereby saving the labor cost. Moreover, because the index model constructed according to the method is not limited by a specific data table in the data warehouse, the relationship between the index model and the actual business can be reflected in a business view, and the constructed index model can be migrated from one data warehouse to other data warehouses.

Furthermore, the method solves the technical problems that the method for constructing the index model in the prior art needs to solve the table structure and table relationship, can be completed by professional technicians and consumes a large amount of personnel cost, and the method is limited by the specific data tables in the data warehouse, cannot reflect the relationship between the model and the actual business from a business view and cannot transfer the constructed index model from one data warehouse to other data warehouses.

Example 3

Fig. 18 shows a data warehouse based metric model management apparatus 1800 according to the present embodiment, the apparatus 1800 corresponding to the method according to the first aspect of embodiment 1. Referring to fig. 18, the apparatus 1800 includes: a processor 1810; and a memory 1820 coupled to the processor 1810 for providing instructions to the processor 1810 for performing the following process steps: receiving first index model parameter information for creating an index model, wherein the index model is used for performing index analysis on data related to a predetermined service in a data warehouse; determining a business model unit for creating a first index model according to the parameter information of the first index model, and determining measurement related to the first index model from fields of the business model unit, wherein the business model unit comprises fields related to a preset business, the business model unit is bound with a first physical model, and the first physical model is bound with a first data table structure which is arranged in a physical database and used for constructing a data warehouse; creating a first metric model from the determined metric; and determining the physical model and the data table structure bound with the first index model based on the first physical model and the first data table structure.

Optionally, the operation of creating a first metric model from the determined metrics comprises: determining a first expression and/or a first statistical granularity for defining a first index model according to the parameter information of the first index model; and creating a first index model from the metrics using the first expression and/or the first statistical granularity.

Optionally, the operations of determining a business model unit for creating the first metric model and determining a metric related to the first metric model from a field of the business model unit include: determining a dimension model unit or a fact model unit which is associated with the predetermined business and is used as a business model unit according to the first index model parameter information, wherein the dimension model unit comprises a field for describing a dimension for analyzing the predetermined business, and the fact model unit comprises a field for describing a fact associated with the predetermined business; and determining a metric associated with the first metric model from a field of the dimension model unit or the fact model unit.

Optionally, the operation of receiving the first metric model parameter information includes: first metric model parameter information is received from a remote terminal device.

Optionally, the operation of receiving the first metric model parameter information includes: providing a first interactive interface provided with a first control, wherein the first control is used for inputting parameter information of a first index model; and receiving first index model parameter information input through the first control in response to a trigger received by the first interactive interface.

Optionally, the memory 1820 is further configured to provide the processor 1810 with instructions to process the following process steps: receiving second index model parameter information for creating an index model; determining an index model set used for creating a second index model according to the parameter information of the second index model; and creating a second index model according to the index models in the index model set.

Optionally, the operation of creating a second index model according to the index models in the index model set includes: determining a second expression for defining a second index model according to the parameter information of the second index model; and creating a second index model according to the index models in the index model set and the second expression.

Optionally, the memory 1820 is further configured to provide the processor 1810 with instructions to process the following process steps: constructing a second physical model related to the second index model, and creating a second data table structure corresponding to the second physical model in the physical database; and binding the second index model with the second physical model to realize the association between the second index model and the second data table structure.

Optionally, the operation of receiving the second index model parameter information includes: second indexing model parameter information is received from a remote terminal device.

Optionally, the operation of receiving the second index model parameter information includes: providing a second interactive interface provided with a second control, wherein the second control is used for inputting index model parameter information associated with the derived index model to be created; and receiving second index model parameter information input through a second control in response to a trigger received by the second interactive interface.

Optionally, the operation of creating a second index model according to the index model in the index model set and the second expression includes: determining whether the metric models in the set of metric models are created based on the same fact model unit, wherein the fact model unit comprises a field describing a fact associated with a predetermined service; and in the case that the index models in the index model set are determined to be created based on the same fact model unit, creating a second index model according to the index models in the index model set and the second expression.

Optionally, the operation of creating the second index model according to the index models in the index model set and the second expression includes, in the case that it is determined that the index models in the index model set are created based on different fact model units, performing the following operations: determining whether different fact model elements are associated with a common dimension; and under the condition that the fact model units are judged to be associated with the common dimension, creating a second index model according to the index models in the index model set and the second expression.

Thus, according to the present embodiment, by the index model management apparatus 1400 based on the data warehouse, the business model unit is established independently of the data warehouse, and thus the index model in the present embodiment is also established independently of the data warehouse. By constructing the index model in this embodiment, a general service person can complete the process without knowing the relationship between the table structure and the table structure or knowing the underlying technology, thereby saving the labor cost. Moreover, because the index model constructed according to the method is not limited by a specific data table in the data warehouse, the relationship between the index model and the actual business can be reflected in a business view, and the constructed index model can be migrated from one data warehouse to other data warehouses.

Furthermore, the method solves the technical problems that the method for constructing the index model in the prior art needs to solve the table structure and table relationship, can be completed by professional technicians and consumes a large amount of personnel cost, and the method is limited by the specific data tables in the data warehouse, cannot reflect the relationship between the model and the actual business from a business view and cannot transfer the constructed index model from one data warehouse to other data warehouses.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.